serial_no int64 1 24.2k | cuda_source stringlengths 11 9.01M |
|---|---|
9,701 | #include "includes.h"
__global__ void FullyConnectedUpdateMovingAveragesKernel( float *weightsGradPtr, float *biasGradPtr, float *weightsGradCurvePtr, float *biasGradCurvePtr, float *avgWeightGradPtr, float *avgBiasGradPtr, float *avgWeightGradVarPtr, float *avgBiasGradVarPtr, float *avgWeightGradCurvePtr, float *avgBiasGradCurvePtr, float *avgWeightGradCurveVarPtr, float *avgBiasGradCurveVarPtr, float *weightMemorySizePtr, float *biasMemorySizePtr, float *dropoutMaskPtr, int prevLayerSize, int thisLayerSize )
{
// i: prev. layer neuron id
// j: current layer neuron id
int i;
int j = blockDim.x * blockIdx.y * gridDim.x //rows preceeding current row in grid
+ blockDim.x * blockIdx.x //blocks preceeding current block
+ threadIdx.x;
if (j < thisLayerSize)
{
if (!dropoutMaskPtr[j])
{
int index = j;
for (i = 0; i < prevLayerSize; i++)
{
// update moving averages according to memory size
avgWeightGradPtr[index] = (1.0f - 1.0f / weightMemorySizePtr[index]) * avgWeightGradPtr[index] + (1.0f / weightMemorySizePtr[index]) * weightsGradPtr[index];
avgWeightGradVarPtr[index] = (1.0f - 1.0f / weightMemorySizePtr[index]) * avgWeightGradVarPtr[index] + (1.0f / weightMemorySizePtr[index]) * weightsGradPtr[index] * weightsGradPtr[index];
avgWeightGradCurvePtr[index] = (1.0f - 1.0f / weightMemorySizePtr[index]) * avgWeightGradCurvePtr[index] + (1.0f / weightMemorySizePtr[index]) * weightsGradCurvePtr[index];
avgWeightGradCurveVarPtr[index] = (1.0f - 1.0f / weightMemorySizePtr[index]) * avgWeightGradCurveVarPtr[index] + (1.0f / weightMemorySizePtr[index]) * weightsGradCurvePtr[index] * weightsGradCurvePtr[index];
index += thisLayerSize;
}
// update moving averages according to memory size
avgBiasGradPtr[j] = (1.0f - 1.0f / biasMemorySizePtr[j]) * avgBiasGradPtr[j] + (1.0f / biasMemorySizePtr[j]) * biasGradPtr[j];
avgBiasGradVarPtr[j] = (1.0f - 1.0f / biasMemorySizePtr[j]) * avgBiasGradVarPtr[j] + (1.0f / biasMemorySizePtr[j]) * biasGradPtr[j] * biasGradPtr[j];
avgBiasGradCurvePtr[j] = (1.0f - 1.0f / biasMemorySizePtr[j]) * avgBiasGradCurvePtr[j] + (1.0f / biasMemorySizePtr[j]) * biasGradCurvePtr[j];
avgBiasGradCurveVarPtr[j] = (1.0f - 1.0f / biasMemorySizePtr[j]) * avgBiasGradCurveVarPtr[j] + (1.0f / biasMemorySizePtr[j]) * biasGradCurvePtr[j] * biasGradCurvePtr[j];
}
}
} |
9,702 | /*
* In his exalted name
*
* Reduction - Sequential Code
* Written by Ahmad Siavashi (siavashi@aut.ac.ir)
* Date: June, 2018
* Language: C++11
*/
#include <cstdlib>
#include <vector>
#include <chrono>
#include <iostream>>
#include <cmath>
#include <numeric>
// N = 2^22
#define N pow(2, 22)
using namespace std;
int main(int argc, char *argv[]) {
// initialize a vector of size N with 1
vector<int> v(N, 1);
// capture start time
auto start_time = chrono::high_resolution_clock::now();
// reduction
auto sum = accumulate(begin(v), end(v), 0);
// capture end time
auto end_time = chrono::high_resolution_clock::now();
// elapsed time in milliseconds
auto duration = chrono::duration_cast<chrono::microseconds>(end_time - start_time);
// print sum and elapsed time
cout << "[-] Sum: " << sum << endl;
cout << "[-] Duration: " << duration.count() << "ms" << endl;
return EXIT_SUCCESS;
}
|
9,703 | #include "includes.h"
__global__ void STREAM_Add_Optimized(float *a, float *b, float *c, size_t len)
{
/*
* Ensure size of thread index space is as large as or greater than
* vector index space else return.
*/
if (blockDim.x * gridDim.x < len) return;
size_t idx = threadIdx.x + blockIdx.x * blockDim.x;
if (idx < len) c[idx] = a[idx]+b[idx];
} |
9,704 | #include "includes.h"
__global__ void ker_sparse_to_dense_assign(int n, const unsigned int *idx, float *src, float *trg) {
// Get our global thread ID
int id = blockIdx.x*blockDim.x+threadIdx.x;
// Make sure we do not go out of bounds
if (id < n)
trg[id] = src[idx[id]];
} |
9,705 | #include <cuda.h>
#include <iostream>
#include <vector>
#include <assert.h>
#include <cstdio>
#include <time.h>
#include <algorithm>
using namespace std;
////// Vector Operations //////
// Vector Addition
template<typename T>
__global__ void cudaAddVec(T *a, T *b, int n)
{
int id = blockIdx.x * blockDim.x + threadIdx.x;
if(id<n)a[id]+=b[id];
}
void deviceError(string msg)
{
cout << msg << endl;
cudaDeviceReset();
}
template<typename T>
vector<T> vectorAdd(vector<T> a, vector<T> b)
{
assert(a.size() == b.size());
int n = a.size();
T *h_a = &a[0];
T *h_b = &b[0];
T *d_a, *d_b;
if(cudaMalloc(&d_a, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMalloc(&d_b, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMemcpy(d_a,h_a,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
if(cudaMemcpy(d_b,h_b,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
cudaAddVec<<<a.size()/256 + 1, 256>>>(d_a, d_b,n);
if(cudaMemcpy(h_a, d_a, sizeof(T) * n, cudaMemcpyDeviceToHost)!=cudaSuccess){deviceError("Error Copying Variables From Device Back To Host"); return vector<T>();};
cudaDeviceReset();
return vector<T>(h_a, h_a+n);
}
template<typename T>
vector<T> operator+(vector<T> const &a, vector<T> const &b)
{
return vectorAdd(a,b);
}
template <typename T>
vector<T>& operator+=(vector<T>& a, const vector<T>& b)
{
a = a + b;
return a;
}
// Vector Sabtraction
template<typename T>
__global__ void cudaSabVec(T *a, T *b, int n)
{
int id = blockIdx.x * blockDim.x + threadIdx.x;
if(id<n)a[id]-=b[id];
}
template<typename T>
vector<T> vectorSab(vector<T> a, vector<T> b)
{
assert(a.size() == b.size());
int n = a.size();
T *h_a = &a[0];
T *h_b = &b[0];
T *d_a, *d_b;
if(cudaMalloc(&d_a, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMalloc(&d_b, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMemcpy(d_a,h_a,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
if(cudaMemcpy(d_b,h_b,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
cudaSabVec<<<a.size()/256 + 1, 256>>>(d_a, d_b,n);
if(cudaMemcpy(h_a, d_a, sizeof(T) * n, cudaMemcpyDeviceToHost)!=cudaSuccess){deviceError("Error Copying Variables From Device Back To Host"); return vector<T>();};
cudaDeviceReset();
return vector<T>(h_a, h_a+n);
}
template<typename T>
vector<T> operator-(vector<T> const &a, vector<T> const &b)
{
return vectorSab(a,b);
}
template <typename T>
vector<T>& operator-=(vector<T>& a, const vector<T>& b)
{
a = a - b;
return a;
}
// Vector Multiplication
template<typename T>
__global__ void cudaMultVec(T *a, T *b, int n)
{
int id = blockIdx.x * blockDim.x + threadIdx.x;
if(id<n)a[id]*=b[id];
}
template<typename T>
__global__ void cudaMultVecScalr(T *a, T *b, int n)
{
int id = blockIdx.x * blockDim.x + threadIdx.x;
if(id<n)a[id]*=b[0];
}
template<typename T>
vector<T> vectorMult(vector<T> a, vector<T> b)
{
assert(a.size() == b.size());
int n = a.size();
T *h_a = &a[0];
T *h_b = &b[0];
T *d_a, *d_b;
if(cudaMalloc(&d_a, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMalloc(&d_b, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMemcpy(d_a,h_a,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
if(cudaMemcpy(d_b,h_b,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
cudaMultVec<<<a.size()/256 + 1, 256>>>(d_a, d_b,n);
if(cudaMemcpy(h_a, d_a, sizeof(T) * n, cudaMemcpyDeviceToHost)!=cudaSuccess){deviceError("Error Copying Variables From Device Back To Host"); return vector<T>();};
cudaDeviceReset();
return vector<T>(h_a, h_a+n);
}
template<typename T>
vector<T> vectorMultScalr(vector<T> a, T b)
{
int n = a.size();
T *h_a = &a[0];
T *h_b = &b;
T *d_a, *d_b;
if(cudaMalloc(&d_a, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMalloc(&d_b, sizeof(T) * n)!=cudaSuccess){deviceError("Error Allocating Memory To Device"); return vector<T>();};
if(cudaMemcpy(d_a,h_a,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
if(cudaMemcpy(d_b,h_b,sizeof(T) * n, cudaMemcpyHostToDevice)!=cudaSuccess){deviceError("Error Copying Variables To Device"); return vector<T>();};
cudaMultVecScalr<<<a.size()/256 + 1, 256>>>(d_a, d_b,n);
if(cudaMemcpy(h_a, d_a, sizeof(T) * n, cudaMemcpyDeviceToHost)!=cudaSuccess){deviceError("Error Copying Variables From Device Back To Host"); return vector<T>();};
cudaDeviceReset();
return vector<T>(h_a, h_a+n);
}
template<typename T>
vector<T> operator*(vector<T> const &a, vector<T> const &b)
{
return vectorMult(a,b);
}
template<typename T>
vector<T> operator*(vector<T> const &a, T const &b)
{
return vectorMultScalr(a,b);
}
template <typename T>
vector<T>& operator*=(vector<T>& a, const vector<T>& b)
{
a = a * b;
return a;
}
template <typename T>
vector<T>& operator*=(vector<T>& a, const T& b)
{
a = a * b;
return a;
}
// Vector Element Summation
template<typename T>
T sumVec(vector<T> const &a)
{
T sum = 0;
for(auto e : a)sum+=e;
return sum;
}
// Vector Inner Product
template<typename T>
T dotProduct(vector<T> a, vector<T> b)
{
vector<T> temp = a * b;
return sumVec(temp);
}
// Vector Print
template<typename T>
void vectorPrint(vector<T> const &a)
{
for(auto e : a)cout << e << " ";
cout << endl;
}
template<typename T>
void operator~(vector<T> const &a)
{
vectorPrint(a);
}
////// Matrix Operations //////
// Transpose
// Transpose
template<typename T>
vector< vector<T> > transpose(vector< vector<T> > const &a)
{
vector<vector<T>> temp;
if (a.size() > 1)
{
if(true)
{
for (int i = 0; i < a.size(); i++)
{
temp.push_back(vector<T>{});
for (int j = 0; j < a[i].size(); j++)
{
temp.back().push_back(a[j][i]);
}
}
}
}
return temp;
}
// Matrix Addition
template<typename T>
__global__ void cudaMatrixAdd(int n, T* a, T* b, T* c)
{
int col = threadIdx.x + blockIdx.x * blockDim.x;
int row = threadIdx.y + blockIdx.y * blockDim.y;
c[row*n + col] = a[row*n + col] + b[row*n + col];
}
template<typename T>
vector< vector<T> > matrixAdd(vector< vector<T> > &va, vector< vector<T> > &vb)
{
assert(va.size() == vb.size() && va[0].size() == vb[0].size());
int n = va.size();
vector<vector<T>> temp(n, vector<T>(n));
T* a = new T[n * n];
T* b = new T[n * n];
T* c = new T[n * n];
T *d_a, *d_b, *d_c;
dim3 dimGrid(n,n, 1);
int ts = va.size()/256 + 1;
cudaMalloc(&d_a, n * n * sizeof(T));
cudaMalloc(&d_b, n * n * sizeof(T));
cudaMalloc(&d_c, n * n * sizeof(T));
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
a[n * i + j] = va[i][j];
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
b[n * i + j] = vb[i][j];
cudaMemcpy(d_a, a, n * n * sizeof(T), cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, n * n * sizeof(T), cudaMemcpyHostToDevice);
cudaMatrixAdd<<<dimGrid, ts>>>(n, d_a, d_b, d_c);
cudaMemcpy(c, d_c, n * n * sizeof(T), cudaMemcpyDeviceToHost);
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
temp[i][j] = c[n * i + j];
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return temp;
}
// Matrix Sabtraction
template<typename T>
__global__ void cudaMatrixSab(int n, T* a, T* b, T* c)
{
int col = threadIdx.x + blockIdx.x * blockDim.x;
int row = threadIdx.y + blockIdx.y * blockDim.y;
c[row*n + col] = a[row*n + col] - b[row*n + col];
}
template<typename T>
vector< vector<T> > matrixSab(vector< vector<T> > &va, vector< vector<T> > &vb)
{
assert(va.size() == vb.size() && va[0].size() == vb[0].size());
int n = va.size();
vector<vector<T>> temp(n, vector<T>(n));
T* a = new T[n * n];
T* b = new T[n * n];
T* c = new T[n * n];
T *d_a, *d_b, *d_c;
dim3 dimGrid(n,n, 1);
int ts = va.size()/256 + 1;
cudaMalloc(&d_a, n * n * sizeof(T));
cudaMalloc(&d_b, n * n * sizeof(T));
cudaMalloc(&d_c, n * n * sizeof(T));
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
a[n * i + j] = va[i][j];
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
b[n * i + j] = vb[i][j];
cudaMemcpy(d_a, a, n * n * sizeof(T), cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, n * n * sizeof(T), cudaMemcpyHostToDevice);
cudaMatrixSab<<<dimGrid, ts>>>(n, d_a, d_b, d_c);
cudaMemcpy(c, d_c, n * n * sizeof(T), cudaMemcpyDeviceToHost);
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
temp[i][j] = c[n * i + j];
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return temp;
}
// Matrix Multiplication
template<typename T>
__global__ void cudaMatrixMult(int m, int n, int k, T* a, T* b, T* c)
{
int row = threadIdx.y + blockIdx.y * blockDim.y;
int col = threadIdx.x + blockIdx.x * blockDim.x;
if (row < m && col < k)
{
T tmp = (T)0;
for (int i = 0; i < n; i++)
tmp += a[row * n + i] * b[col + i * k];
c[row * k + col] = tmp;
}
}
template<typename T>
vector< vector<T> > matrixMult(vector< vector<T> > const& va, vector< vector<T> > const& vb)
{
int m = va.size();
int n = va[0].size();
int k = vb[0].size();
vector<vector<T>> temp(m, vector<T>(k));
T* a = new T[m * n];
T* b = new T[n * k];
T* c = new T[m * k];
T *d_a, *d_b, *d_c;
dim3 dimGrid(k,m, 1);
int ts = va.size()/256 + 1;
cudaMalloc(&d_a, m * n * sizeof(T));
cudaMalloc(&d_b, n * k * sizeof(T));
cudaMalloc(&d_c, m * k * sizeof(T));
for (int i = 0; i < m; i++)
for (int j = 0; j < n; j++)
a[n * i + j] = va[i][j];
for (int i = 0; i < n; i++)
for (int j = 0; j < k; j++)
b[k * i + j] = vb[i][j];
cudaMemcpy(d_a, a, m * n * sizeof(T), cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, n * k * sizeof(T), cudaMemcpyHostToDevice);
cudaMatrixMult<<<dimGrid, ts>>>(m, n, k, d_a, d_b, d_c);
cudaMemcpy(c, d_c, m * k * sizeof(T), cudaMemcpyDeviceToHost);
for (int i = 0; i < m; i++)
for (int j = 0; j < k; j++)
temp[i][j] = c[k * i + j];
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return temp;
}
// Matrix Scalar Mult
template<typename T>
__global__ void cudaMatrixScalarMult(int n, T *a, T *b, T *c)
{
int col = threadIdx.x + blockIdx.x * blockDim.x;
int row = threadIdx.y + blockIdx.y * blockDim.y;
c[row*n + col] = a[row*n + col] * b[0];
}
template<typename T>
vector< vector<T> > matrixScalarMult(vector< vector<T> > va, T vb)
{
int n = va.size();
vector<vector<T>> temp(n, vector<T>(n));
T* a = new T[n * n];
T* b = &vb;
T* c = new T[n * n];
T *d_a, *d_b, *d_c;
dim3 dimGrid(n,n, 1);
int ts = va.size()/256 + 1;
cudaMalloc(&d_a, n * n * sizeof(T));
cudaMalloc(&d_b, sizeof(T));
cudaMalloc(&d_c, n * n * sizeof(T));
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
a[n * i + j] = va[i][j];
cudaMemcpy(d_a, a, n * n * sizeof(T), cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, sizeof(T), cudaMemcpyHostToDevice);
cudaMatrixScalarMult<<<dimGrid, ts>>>(n, d_a, d_b, d_c);
cudaMemcpy(c, d_c, n * n * sizeof(T), cudaMemcpyDeviceToHost);
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
temp[i][j] = c[n * i + j];
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return temp;
}
// Matrix Determinant
template<typename T>
vector< vector<T> > shave(vector< vector<T> > a, int i)
{
a.erase(a.begin() + 0);
for (int j = 0; j < a.size(); j++)
{
a[j].erase(begin(a[j]) + i);
}
return a;
}
template<typename T>
vector< vector<T> > shave(vector< vector<T> > a, int i, int j)
{
a.erase(a.begin() + j);
for (int j = 0; j < a.size(); j++)
{
a[j].erase(begin(a[j]) + i);
}
return a;
}
template<typename T>
float det2x2(vector< vector<T> > const &a)
{
return a[0][0] * a[1][1] - a[0][1] * a[1][0];
}
template<typename T>
float detNxN(vector< vector<T> > const &a);
template<typename T>
float det(vector< vector<T> > const &a)
{
assert(a.size() == a[0].size());
if (a[0].size() == 2 && a.size() == 2)return det2x2(a);
else return detNxN(a);
}
template<typename T>
float detNxN(vector< vector<T> > const &a)
{
float sum = 0;
for (int i = 0; i < a.size(); i++)
{
if ((i + 1) % 2 == 0)
{
sum += a[0][i] * det(shave(a, i)) * (-1);
}
else
{
sum += a[0][i] * det(shave(a, i)) * (1);
}
}
return sum;
}
// Cofactor Matrix
template<typename T>
vector< vector<T> > cof(vector< vector<T> > const &a)
{
vector< vector<T> > cofactors;
for (int i = 0; i < a[0].size(); i++)
{
cofactors.push_back(vector<T>{});
for (int j = 0; j < a.size(); j++)
{
int g = ((i + 1 + j) % 2 == 0) ? -1 : 1;
cofactors.back().push_back(det(shave(a, i, j)) * g);
}
}
cofactors = transpose(cofactors);
return cofactors;
}
// Matrix Inverse
template<typename T>
vector< vector<T> > inv(vector< vector<T> > a)
{
if (a[0].size() >= 3)
{
float detr = det(a);
vector< vector<T> > inv = cof(a);
inv = transpose(inv);
inv = matrixScalarMult(inv,1/detr);
return inv;
}
else
{
vector< vector<T> > inv({ { a[1][1],a[0][1] * -1 },{ a[1][0] * -1, a[0][0] } });
matrixScalarMult(inv, (1/det(a)));
return inv;
}
}
// Printing Matrices
template<typename T>
void printMatrix(vector< vector<T> > const &c)
{
for(int i = 0; i < c.size(); i++)
{
for(int j = 0; j < c[i].size(); j++)
{
cout << c[i][j] << "\t";
}
cout << endl;
}
}
int main()
{
////// Testing //////
vector< vector<float> > a;
vector< vector<float> > b;
for(int i = 1; i <= 4; i++){
a.push_back(vector<float>());
b.push_back(vector<float>());
for(int j = 1; j <= 4; j++){
a.back().push_back(rand()%10);
b.back().push_back(rand()%10);
}
}
vector< vector<float> > test = {{5,7,8},{0,5,4},{6,7,9}};
vector< vector<float> > iTest = inv(test);
printMatrix(iTest);
cout << endl;
cout << "Gaze upon the power of the GPU!" << endl;
vector < vector<float> > ss{ { 8,3 },{ 1,2 } };
vector < vector<float> > result{ {46},{9} };
float detr = det(ss);
ss = inv(ss);
matrixMult(ss,result);
printMatrix(ss);
cout << endl;
vector< vector<float> > c = matrixAdd(a,b);
printMatrix(a);cout << '\n';
printMatrix(b);cout << '\n';
printMatrix(c);
////// (cuda)Success!! ////// \(^o^)/
return 0;
}
|
9,706 | #include <stdio.h>
#define BLOCK_SIZE 32
__global__ void spmv_csr_kernel(unsigned int dim, unsigned int *csrRowPtr,
unsigned int *csrColIdx, float *csrData, float *inVector,
float *outVector) {
// INSERT KERNEL CODE HERE
// Creating the row
int row = blockDim.x*blockIdx.x + threadIdx.x;
if(row < dim)
{
float dot = 0;
int row_start = csrRowPtr[row];
int row_end = csrRowPtr[row + 1];
for(int jj = row_start; jj < row_end; jj++)
{
dot += csrData[jj]*inVector[csrColIdx[jj]];
}
outVector[row] += dot;
}
}
__global__ void spmv_jds_kernel(unsigned int dim, unsigned int *jdsRowPerm,
unsigned int *jdsRowNNZ, unsigned int *jdsColStartIdx,
unsigned int *jdsColIdx, float *jdsData, float* inVector,
float *outVector) {
// INSERT KERNEL CODE HERE
int row = blockDim.x*blockIdx.x + threadIdx.x;
if(row < dim )
{
float dot = 0;
for(int i = 0; i < jdsRowNNZ[row]; i++)
{
dot += jdsData[jdsColStartIdx[i] +row]*inVector[jdsColIdx[jdsColStartIdx[i]+ row]];
}
// transferring the output to out vector
outVector[jdsRowPerm[row]] = dot;
}
}
void spmv_csr(unsigned int dim, unsigned int *csrRowPtr, unsigned int *csrColIdx,
float *csrData, float *inVector, float *outVector) {
// INSERT CODE HERE
// Calling the kernel
int gridsize = dim/BLOCK_SIZE;
if(dim%BLOCK_SIZE != 0)
{
gridsize++;
}
dim3 dimGrid(gridsize, 1,1);
dim3 dimBlock(BLOCK_SIZE,1,1);
spmv_csr_kernel<<<dimGrid,dimBlock>>>(dim,csrRowPtr,csrColIdx,csrData, inVector, outVector);
}
void spmv_jds(unsigned int dim, unsigned int *jdsRowPerm, unsigned int *jdsRowNNZ,
unsigned int *jdsColStartIdx, unsigned int *jdsColIdx, float *jdsData,
float* inVector, float *outVector) {
// INSERT CODE HERE
int gridsize = dim/BLOCK_SIZE;
if(dim%BLOCK_SIZE != 0)
{
gridsize++;
}
dim3 dimGrid(gridsize, 1,1);
dim3 dimBlock(BLOCK_SIZE,1,1);
spmv_jds_kernel<<<dimGrid,dimBlock>>>( dim,jdsRowPerm,jdsRowNNZ,jdsColStartIdx,jdsColIdx,jdsData, inVector,outVector) ;
}
|
9,707 | #include "cuda.h"
#include "stdio.h"
#define BLOCK_X 32
#define BLOCK_Y 32
__global__ void mult_global (int *A, int *B, int *result, int n)
{
int k, sum = 0;
int col = blockIdx.x * blockDim.x + threadIdx.x;
int row = blockIdx.y * blockDim.y + threadIdx.y;
if(col < n && row < n)
{
for (k = 0; k < n; k++)
{
sum += A[row * n + k] * B[k * n + col];
result[row * n + col] = sum;
}
}
}
__global__ void mult_shared( int *A, int *B, int *result, int n)
{ int k;
int kk;
const int bx = BLOCK_X, by = BLOCK_Y;
const int col = blockIdx.x*bx + threadIdx.x;
const int row = blockIdx.y*by + threadIdx.y;
__shared__ int a[BLOCK_X][BLOCK_Y] , b[BLOCK_X][BLOCK_Y];
if ((col < n) && (row < n))
{
int c = 0;
for (k=0; k < n; k++)
{
a[threadIdx.x][threadIdx.y] = A[ col * n + k*by + threadIdx.y];
b[threadIdx.y][threadIdx.x] = B[ row + n * (k*bx+threadIdx.x)];
__syncthreads(); // Synchronizes all threads in a block
for (kk=0; kk< bx; kk++)
c += a[kk][threadIdx.x]*b[kk][threadIdx.y];
__syncthreads(); // Avoids memory hazards
}
result[col*n+row] = c;
}
}
int main() {
const int N = 32;
int *mat1_h = (int *)malloc(sizeof(int) * N * N);
int *mat2_h = (int *)malloc(sizeof(int) * N * N);
int *mat1_d, *mat2_d, *result_d;
cudaMalloc(&mat1_d, sizeof(int) * N * N);
cudaMalloc(&mat2_d, sizeof(int) * N * N);
cudaMalloc(&result_d, sizeof(int) * N * N);
cudaMemcpy(mat1_d, mat1_h, sizeof(int) * N * N, cudaMemcpyHostToDevice);
cudaMemcpy(mat2_d, mat2_h, sizeof(int) * N * N, cudaMemcpyHostToDevice);
dim3 dimBlock(256, 256);
dim3 dimGrid(N/256, N/256);
mult_shared<<<dimGrid, dimBlock>>>(mat1_d, mat2_d, result_d, N);
int *result_h = (int *)malloc(sizeof(int) * N);
cudaMemcpy(result_h, result_d, sizeof(int) * N, cudaMemcpyDeviceToHost);
//print results
cudaFree(result_d);
cudaFree(mat1_d);
cudaFree(mat2_d);
free(mat1_h);
free(mat2_h);
free(result_h);
}
|
9,708 | #include <stdint.h>
#include <string.h>
#define CHUNK_SIZE 64
#define TOTAL_LEN_LEN 8
/*
* ABOUT bool: this file does not use bool in order to be as pre-C99 compatible as possible.
*/
/*
* Comments from pseudo-code at https://en.wikipedia.org/wiki/SHA-2 are reproduced here.
* When useful for clarification, portions of the pseudo-code are reproduced here too.
*/
/*
* Initialize array of round constants:
* (first 32 bits of the fractional parts of the cube roots of the first 64 primes 2..311):
*/
static const uint32_t k[] = {
0x428a2f98, 0x71374491, 0xb5c0fbcf, 0xe9b5dba5, 0x3956c25b, 0x59f111f1, 0x923f82a4, 0xab1c5ed5,
0xd807aa98, 0x12835b01, 0x243185be, 0x550c7dc3, 0x72be5d74, 0x80deb1fe, 0x9bdc06a7, 0xc19bf174,
0xe49b69c1, 0xefbe4786, 0x0fc19dc6, 0x240ca1cc, 0x2de92c6f, 0x4a7484aa, 0x5cb0a9dc, 0x76f988da,
0x983e5152, 0xa831c66d, 0xb00327c8, 0xbf597fc7, 0xc6e00bf3, 0xd5a79147, 0x06ca6351, 0x14292967,
0x27b70a85, 0x2e1b2138, 0x4d2c6dfc, 0x53380d13, 0x650a7354, 0x766a0abb, 0x81c2c92e, 0x92722c85,
0xa2bfe8a1, 0xa81a664b, 0xc24b8b70, 0xc76c51a3, 0xd192e819, 0xd6990624, 0xf40e3585, 0x106aa070,
0x19a4c116, 0x1e376c08, 0x2748774c, 0x34b0bcb5, 0x391c0cb3, 0x4ed8aa4a, 0x5b9cca4f, 0x682e6ff3,
0x748f82ee, 0x78a5636f, 0x84c87814, 0x8cc70208, 0x90befffa, 0xa4506ceb, 0xbef9a3f7, 0xc67178f2
};
struct buffer_state {
const uint8_t* p;
size_t len;
size_t total_len;
int single_one_delivered; /* bool */
int total_len_delivered; /* bool */
};
static inline uint32_t right_rot(uint32_t value, unsigned int count)
{
/*
* Defined behaviour in standard C for all count where 0 < count < 32,
* which is what we need here.
*/
return value >> count | value << (32 - count);
}
static void init_buf_state(struct buffer_state* state, const uint8_t* input, size_t len)
{
state->p = input;
state->len = len;
state->total_len = len;
state->single_one_delivered = 0;
state->total_len_delivered = 0;
}
/* Return value: bool */
static int calc_chunk(uint8_t chunk[CHUNK_SIZE], struct buffer_state* state)
{
size_t space_in_chunk;
if (state->total_len_delivered) {
return 0;
}
if (state->len >= CHUNK_SIZE) {
memcpy(chunk, state->p, CHUNK_SIZE);
state->p += CHUNK_SIZE;
state->len -= CHUNK_SIZE;
return 1;
}
memcpy(chunk, state->p, state->len);
chunk += state->len;
space_in_chunk = CHUNK_SIZE - state->len;
state->p += state->len;
state->len = 0;
/* If we are here, space_in_chunk is one at minimum. */
if (!state->single_one_delivered) {
*chunk++ = 0x80;
space_in_chunk -= 1;
state->single_one_delivered = 1;
}
/*
* Now:
* - either there is enough space left for the total length, and we can conclude,
* - or there is too little space left, and we have to pad the rest of this chunk with zeroes.
* In the latter case, we will conclude at the next invokation of this function.
*/
if (space_in_chunk >= TOTAL_LEN_LEN) {
const size_t left = space_in_chunk - TOTAL_LEN_LEN;
size_t len = state->total_len;
int i;
memset(chunk, 0x00, left);
chunk += left;
/* Storing of len * 8 as a big endian 64-bit without overflow. */
chunk[7] = (uint8_t)(len << 3);
len >>= 5;
for (i = 6; i >= 0; i--) {
chunk[i] = (uint8_t)len;
len >>= 8;
}
state->total_len_delivered = 1;
}
else {
memset(chunk, 0x00, space_in_chunk);
}
return 1;
}
/*
* Limitations:
* - Since input is a pointer in RAM, the data to hash should be in RAM, which could be a problem
* for large data sizes.
* - SHA algorithms theoretically operate on bit strings. However, this implementation has no support
* for bit string lengths that are not multiples of eight, and it really operates on arrays of bytes.
* In particular, the len parameter is a number of bytes.
*/
inline void calc_sha_256(uint8_t hash[32], const uint8_t* input, size_t len)
{
/*
* Note 1: All integers (expect indexes) are 32-bit unsigned integers and addition is calculated modulo 2^32.
* Note 2: For each round, there is one round constant k[i] and one entry in the message schedule array w[i], 0 = i = 63
* Note 3: The compression function uses 8 working variables, a through h
* Note 4: Big-endian convention is used when expressing the constants in this pseudocode,
* and when parsing message block data from bytes to words, for example,
* the first word of the input message "abc" after padding is 0x61626380
*/
/*
* Initialize hash values:
* (first 32 bits of the fractional parts of the square roots of the first 8 primes 2..19):
*/
uint32_t h[] = { 0x6a09e667, 0xbb67ae85, 0x3c6ef372, 0xa54ff53a, 0x510e527f, 0x9b05688c, 0x1f83d9ab, 0x5be0cd19 };
unsigned i, j;
/* 512-bit chunks is what we will operate on. */
uint8_t chunk[64];
struct buffer_state state;
init_buf_state(&state, input, len);
while (calc_chunk(chunk, &state)) {
uint32_t ah[8];
const uint8_t* p = chunk;
/* Initialize working variables to current hash value: */
for (i = 0; i < 8; i++)
ah[i] = h[i];
/* Compression function main loop: */
for (i = 0; i < 4; i++) {
/*
* The w-array is really w[64], but since we only need
* 16 of them at a time, we save stack by calculating
* 16 at a time.
*
* This optimization was not there initially and the
* rest of the comments about w[64] are kept in their
* initial state.
*/
/*
* create a 64-entry message schedule array w[0..63] of 32-bit words
* (The initial values in w[0..63] don't matter, so many implementations zero them here)
* copy chunk into first 16 words w[0..15] of the message schedule array
*/
uint32_t w[16];
for (j = 0; j < 16; j++) {
if (i == 0) {
w[j] = (uint32_t)p[0] << 24 | (uint32_t)p[1] << 16 |
(uint32_t)p[2] << 8 | (uint32_t)p[3];
p += 4;
}
else {
/* Extend the first 16 words into the remaining 48 words w[16..63] of the message schedule array: */
const uint32_t s0 = right_rot(w[(j + 1) & 0xf], 7) ^ right_rot(w[(j + 1) & 0xf], 18) ^ (w[(j + 1) & 0xf] >> 3);
const uint32_t s1 = right_rot(w[(j + 14) & 0xf], 17) ^ right_rot(w[(j + 14) & 0xf], 19) ^ (w[(j + 14) & 0xf] >> 10);
w[j] = w[j] + s0 + w[(j + 9) & 0xf] + s1;
}
const uint32_t s1 = right_rot(ah[4], 6) ^ right_rot(ah[4], 11) ^ right_rot(ah[4], 25);
const uint32_t ch = (ah[4] & ah[5]) ^ (~ah[4] & ah[6]);
const uint32_t temp1 = ah[7] + s1 + ch + k[i << 4 | j] + w[j];
const uint32_t s0 = right_rot(ah[0], 2) ^ right_rot(ah[0], 13) ^ right_rot(ah[0], 22);
const uint32_t maj = (ah[0] & ah[1]) ^ (ah[0] & ah[2]) ^ (ah[1] & ah[2]);
const uint32_t temp2 = s0 + maj;
ah[7] = ah[6];
ah[6] = ah[5];
ah[5] = ah[4];
ah[4] = ah[3] + temp1;
ah[3] = ah[2];
ah[2] = ah[1];
ah[1] = ah[0];
ah[0] = temp1 + temp2;
}
}
/* Add the compressed chunk to the current hash value: */
for (i = 0; i < 8; i++)
h[i] += ah[i];
}
/* Produce the final hash value (big-endian): */
for (i = 0, j = 0; i < 8; i++)
{
hash[j++] = (uint8_t)(h[i] >> 24);
hash[j++] = (uint8_t)(h[i] >> 16);
hash[j++] = (uint8_t)(h[i] >> 8);
hash[j++] = (uint8_t)h[i];
}
} |
9,709 | #include "includes.h"
__global__ void Prepare(float* p_Input, float* p_Output, int p_Width, int p_Height, int p_Display) {
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x < p_Width && y < p_Height) {
const int index = (y * p_Width + x) * 4;
float ramp = (float)x / (float)(p_Width - 1);
p_Output[index] = p_Display == 1 ? ramp : p_Input[index];
p_Output[index + 1] = p_Display == 1 ? ramp : p_Input[index + 1];
p_Output[index + 2] = p_Display == 1 ? ramp : p_Input[index + 2];
p_Output[index + 3] = 1.0f;
if (p_Display == 2) {
p_Input[index] = ramp;
p_Input[index + 1] = ramp;
p_Input[index + 2] = ramp;
}}} |
9,710 | #include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>
#include <device_launch_parameters.h>
// declare device constants
__constant__ float n = 0.0002;
__constant__ float p = 0.5;
__constant__ float G = 0.75;
// declare global constants
const int N = 4;
// parallelize inner element position calculation
__global__ void calculate_inner_elements(float* d_u, float* d_u1, float* d_u2) {
int i = blockIdx.x;
int j = blockIdx.y;
if (i >= 1 && i <= N - 2 && j >= 1 && j <= N - 2) {
// calculate the positions of the inner elements
d_u[N*i+j] = (p * (d_u1[N*(i-1)+j] + d_u1[N*(i+1)+j] + d_u1[N*i+(j-1)] + d_u1[N*i+(j+1)] - (4 * d_u1[N*i+j]))
+ (2 * d_u1[N*i+j]) - ((1 - n) * d_u2[N*i+j])) / (1 + n);
}
}
// parallelize edge element position calculation
__global__ void calculate_edge_elements(float* d_u) {
int i = blockIdx.x;
int j = blockIdx.y;
// top edge
if (i == 0 && j >= 1 && j <= N - 2) {
d_u[N*i+j] = G * d_u[N*(i+1)+j];
}
else if (i >= 1 && i <= N - 2) {
// left edge
if (j == 0) {
d_u[N*i+j] = G * d_u[N*i+1];
}
// right edge
else if (j == N - 1) {
d_u[N*i+j] = G * d_u[N*i+(j-1)];
}
}
// bottom edge
else if (i == N - 1 && j >= 1 && j <= N - 2) {
d_u[N*i+j] = G * d_u[N*(i-1)+j];
}
}
// parallelize corner element position calculation
__global__ void calculate_corner_elements(float* d_u) {
int i = blockIdx.x;
int j = blockIdx.y;
if (i == 0) {
// top left corner
if (j == 0) {
d_u[N*i+j] = G * d_u[N*(i+1)+j];
}
// top right corner
else if (j == N - 1) {
d_u[N*i+j] = G * d_u[N*i+(j-1)];
}
}
else if (i == N - 1) {
// bottom left corner
if (j == 0) {
d_u[N*i+j] = G * d_u[N*(i-1)+j];
}
// bottom right corner
else if (j == N - 1) {
d_u[N*i+j] = G * d_u[N*i+(j-1)];
}
}
}
// parallelize positional array updates u2 = u1 and u1 = u
__global__ void update_positional_arrays(float* d_u, float* d_u1, float* d_u2) {
int i = blockIdx.x;
int j = blockIdx.y;
if(i < N && j < N) {
int index = N * i + j;
d_u2[index] = d_u1[index];
d_u1[index] = d_u[index];
}
}
// parallelize positional array initialization
__global__ void create_positional_arrays(float* d_u, float* d_u1, float* d_u2) {
int i = blockIdx.x;
int j = blockIdx.y;
if(i < N && j < N) {
int index = N * i + j;
d_u[index] = 0;
if (i == N/2 && j == N/2) d_u1[index] = 1;
else d_u1[index] = 0;
d_u2[index] = 0;
}
}
int main(int argc, char* argv[]) {
// check if the iteration value T is provided
if (argc < 2) {
return printf("The iteration value T is not provided!\n");
}
// get the iteration value T from the command line
int iteration = atoi(argv[1]);
// instantiate the 2D u matrix
float* u = (float*) malloc(N * N * sizeof(float));
// print out the size of the grid
printf("Size of grid: %d nodes\n", N*N);
// instantiate device variables
float* d_u;
float* d_u1;
float* d_u2;
// allocate device memory for the variables
cudaMalloc(&d_u, N * N * sizeof(float));
cudaMalloc(&d_u1, N * N * sizeof(float));
cudaMalloc(&d_u2, N * N * sizeof(float));
// 2D block structure
dim3 blocks = dim3(N, N);
create_positional_arrays<<<blocks, 1>>>(d_u, d_u1, d_u2);
cudaDeviceSynchronize();
// start simulation
for (int T = 0; T < iteration; T++) {
// call the device kernel function
calculate_inner_elements<<<blocks, 1>>>(d_u, d_u1, d_u2);
calculate_edge_elements<<<blocks, 1>>>(d_u);
calculate_corner_elements<<<blocks, 1>>>(d_u);
update_positional_arrays<<<blocks, 1>>>(d_u, d_u1, d_u2);
cudaDeviceSynchronize();
// copy the results back to host
cudaMemcpy(u, d_u, N * N * sizeof(float), cudaMemcpyDeviceToHost);
// print u[N/2][N/2]
printf("(%d, %d): %f\n", N/2, N/2, u[N*(N/2)+(N/2)]);
} // end simulation
// free up the host memory used by the positional arrays
free(u);
// free up the device memory used by the positional arrays
cudaFree(d_u);
cudaFree(d_u1);
cudaFree(d_u2);
return 0;
} |
9,711 | #include <cuda_runtime.h>
#include <stdio.h>
int main(int argc, char **argv) {
// define total data elements
int nElem = 1024;
// define grid and block structure
dim3 block (1024);
dim3 grid ((nElem+block.x-1)/block.x);
printf("grid.x %d block.x %d \n",grid.x, block.x);
// reset block
block.x = 512;
grid.x = (nElem+block.x-1)/block.x;
printf("grid.x %d block.x %d \n",grid.x, block.x);
// reset block
block.x = 256;
grid.x = (nElem+block.x-1)/block.x;
printf("grid.x %d block.x %d \n",grid.x, block.x);
// reset block
block.x = 128;
grid.x = (nElem+block.x-1)/block.x;
printf("grid.x %d block.x %d \n",grid.x, block.x);
// reset device before you leave
cudaDeviceReset();
return(0);
}
|
9,712 | // Program for Parallel Binary Search in CUDA
// For Hadoop-CUDA Lab
#include <stdio.h>
#include <stdlib.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <assert.h>
__device__ int get_index_to_check(int thread, int num_threads, int set_size, int offset) {
// Integer division trick to round up
return (((set_size + num_threads) / num_threads) * thread) + offset;
}
__global__ void p_ary_search(int search, int array_length, int *arr, int *ret_val ) {
const int num_threads = blockDim.x * gridDim.x;
const int thread = blockIdx.x * blockDim.x + threadIdx.x;
//ret_val[0] = -1;
//ret_val[1] = offset;
int set_size = array_length;
while(set_size != 0){
// Get the offset of the array, initially set to 0
int offset = ret_val[1];
// I think this is necessary in case a thread gets ahead, and resets offset before it's read
// This isn't necessary for the unit tests to pass, but I still like it here
__syncthreads();
// Get the next index to check
int index_to_check = get_index_to_check(thread, num_threads, set_size, offset);
// If the index is outside the bounds of the array then lets not check it
if (index_to_check < array_length){
// If the next index is outside the bounds of the array, then set it to maximum array size
int next_index_to_check = get_index_to_check(thread + 1, num_threads, set_size, offset);
if (next_index_to_check >= array_length){
next_index_to_check = array_length - 1;
}
// If we're at the mid section of the array reset the offset to this index
if (search > arr[index_to_check] && (search < arr[next_index_to_check])) {
ret_val[1] = index_to_check;
}
else if (search == arr[index_to_check]) {
// Set the return var if we hit it
ret_val[0] = index_to_check;
}
}
// Since this is a p-ary search divide by our total threads to get the next set size
set_size = set_size / num_threads;
// Sync up so no threads jump ahead and get a bad offset
__syncthreads();
}
}
int chop_position(int search, int *search_array, int array_length)
{
// Get the size of the array for future use
int array_size = array_length * sizeof(int);
// Don't bother with small arrays
if (array_size == 0) return -1;
// Setup array to use on device
int *dev_arr;
cudaMalloc((void**)&dev_arr, array_size);
// Copy search array values
cudaMemcpy(dev_arr, search_array, array_size, cudaMemcpyHostToDevice);
// return values here and on device
int *ret_val = (int*)malloc(sizeof(int) * 2);
ret_val[0] = -1; // return value
ret_val[1] = 0; // offset
array_length = array_length % 2 == 0 ? array_length : array_length - 1; // array size
int *dev_ret_val;
cudaMalloc((void**)&dev_ret_val, sizeof(int) * 2);
// Send in some intialized values
cudaMemcpy(dev_ret_val, ret_val, sizeof(int) * 2, cudaMemcpyHostToDevice);
// Launch kernel
// This seems to be the best combo for p-ary search
// Optimized around 10-15 registers per thread
p_ary_search<<<16, 64>>>(search, array_length, dev_arr, dev_ret_val);
// Get results
cudaMemcpy(ret_val, dev_ret_val, 2 * sizeof(int), cudaMemcpyDeviceToHost);
int ret = ret_val[0];
printf("Ret Val %i Offset %i\n", ret, ret_val[1]);
// Free memory on device
cudaFree(dev_arr);
cudaFree(dev_ret_val);
free(ret_val);
return ret;
}
// Test region
static int * build_array(int length) {
int *ret_val = (int*)malloc(length * sizeof(int));
for (int i = 0; i < length; i++)
{
ret_val[i] = i * 2 - 1;
}
return ret_val;
}
static void test_array(int length, int search, int index) {
printf("Length %i Search %i Index %i\n", length, search, index);
// assert(index == chop_position(search, build_array(length), length) && "test_small_array()");
}
static void test_arrays() {
test_array(200, 200, -1);
test_array(200, -1, 0);
test_array(200, 1, 1);
test_array(200, 29, 15);
test_array(200, 129, 65);
test_array(200, 395, 198);
test_array(20000, 395, 198);
test_array(2000000, 394, -1);
test_array(20000000, 394, -1);
}
int main(){
test_arrays();
}
|
9,713 | #include "cuda.h"
#include "stdlib.h"
#include "stdio.h"
#include <iostream>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <ctime>
using namespace std;
__global__ void sum_cuda(int *res, int *mas1, int *mas2, int N, int M)
{
int i = threadIdx.x + blockIdx.x * blockDim.x;
int j = threadIdx.y + blockIdx.y * blockDim.y;
int tx = i * N + j;
res[tx] = mas1[tx] + mas2[tx];
}
void init(int *mas, int size);
void sum(int *res, int *mas1, int *mas2, int N, int M);
void print(int *mas, int N, int M);
int main()
{
int N = 4, M = 4, dimN = 2, dimM = 2;
int mas1[N * M];
init(mas1, N * M);
int mas2[N * M];
init(mas2, N*M);
int *res = new int[N * M];
int *cudaMas1;
int *cudaMas2;
int *cudaRes;
float time = 0;
cudaMalloc((void**)&cudaMas1, sizeof(int) * N * M);
cudaMalloc((void**)&cudaMas2, sizeof(int) * N * M);
cudaMalloc((void**)&cudaRes, sizeof(int) * N * M);
cudaMemcpy(cudaMas1, mas1, sizeof(int) * N * M, cudaMemcpyHostToDevice);
cudaMemcpy(cudaMas2, mas2, sizeof(int) * N * M, cudaMemcpyHostToDevice);
cudaMemcpy(cudaRes, res, sizeof(int) * N * M, cudaMemcpyHostToDevice);
cudaEvent_t start, end;
cudaEventCreate(&start);
cudaEventCreate(&end);
print(mas1, N, M);
print(mas2, N, M);
cudaEventRecord(start);
sum(res, mas1, mas2, N, M);
cudaEventRecord(end);
cudaEventSynchronize(end);
print(res, N, M);
cudaEventElapsedTime(&time, start, end);
cout << "Последовательно " << time << endl;
dim3 blocks(N / dimN, M / dimM);
dim3 threads(dimN, dimM);
cudaEventRecord(start);
sum_cuda<<< blocks, threads >>>(cudaRes, cudaMas1, cudaMas2, N, M);
cudaDeviceSynchronize();
cudaEventRecord(end);
cudaMemcpy(res, cudaRes, sizeof(int) * N * M, cudaMemcpyDeviceToHost);
print(res, N, M);
cudaEventElapsedTime(&time, start, end);
cout << "Параллельно " << time << endl;
cudaFree(cudaMas1);
cudaFree(cudaMas2);
cudaFree(cudaRes);
return 0;
}
void sum(int *res, int *mas1, int *mas2, int N, int M)
{
for (int i = 0; i < N; i++){
for (int j = 0; j < M; j++)
res[i*N + j] = mas1[i*N + j] + mas2[i*N + j];
}
}
void print(int *mas, int N, int M)
{
for (int i = 0; i < N; i++){
for (int j = 0; j < M; j++)
cout << mas[i*N + j] << " ";
cout << endl;
}
cout << endl;
}
void init(int *mas, int size)
{
srand( time(0));
for (int i = 0; i < size; i++)
{
mas[i] = rand() % 1000;
}
}
|
9,714 | #include "includes.h"
extern "C"
extern "C"
__global__ void deltasOne(float *inputs, float *outputs, float *weights, float *weightsDeltas, int offsetInputImages, int inputSize){
int gid = blockIdx.x * blockDim.x + threadIdx.x;
float sum=0;
int offsetDeltas = (inputSize+1)*gid;
int offsetInput = inputSize*(gid+offsetInputImages);
for(int imageIndex=0;imageIndex<=inputSize;imageIndex++){
weightsDeltas[offsetDeltas+imageIndex]=0;
}
for(int imageIndex=0;imageIndex<inputSize;imageIndex++){
sum+=inputs[offsetInput+imageIndex]*weights[imageIndex];
}
sum+=weights[inputSize];
if(sum>0) sum=1;
else sum=0;
sum=outputs[offsetInputImages+gid]-sum;
if(sum!=0){
for(int imageIndex=0;imageIndex<inputSize;imageIndex++){
weightsDeltas[offsetDeltas+imageIndex]+=sum*inputs[offsetInput+imageIndex];
}
weightsDeltas[offsetDeltas+inputSize]+=sum;
}
} |
9,715 | #include <stdio.h>
#include <stdlib.h>
#include <time.h>
// #define TILE_WIDTH 32
void randomArray(int *A, int n, int k){
srand((unsigned) time(NULL));
for(int i=0; i< n; ++i)
for(int j = 0; j<k; ++j)
A[i*k + j] = ((int)rand()% 10) + 1;
}
void printResults(int *h_matA, int *h_matB, int *h_matC, int n, int k, int m){
printf("Matrix A:\n");
for(int i=0; i< (n*k); i++){
// int id = i + floor(i / (int)SQTILE_WIDTH )* (int)SQTILE_WIDTH;
printf("%d ", h_matA[i]);
if( (i+1) % k == 0 ){
printf("\n");
}
}
printf("Matrix B:\n");
for(int i=0; i< (k * m); i++){
// int id = i + floor(i / (int)SQTILE_WIDTH )* (int)SQTILE_WIDTH;
printf("%d ", h_matB[i]);
if( (i+1) % m == 0 ){
printf("\n");
}
}
printf("Matrix C:\n");
for(int i=0; i< (n * m); i++){
// int id = i + floor(i / (int)SQTILE_WIDTH )* (int)SQTILE_WIDTH;
printf("%d ", h_matC[i]);
if( (i+1) % m == 0 ){
printf("\n");
}
}
}
__global__ void matmul_rec_glob(int *a, int *b, int *c, int n, int k, int m) {
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
if( col < m && row < n) {
int sum = 0;
for(int i = 0; i < k; i++) {
sum += a[row * k + i] * b[i * m + col];
}
c[row * m + col] = sum;
}
}
__global__ void matmul_rec_shared(int *a, int *b, int *c, int n, int k, int m, int TILE_WIDTH) {
extern __shared__ int array[];
int* sA = array;
int* sB = &sA[TILE_WIDTH*TILE_WIDTH];
int Row = blockIdx.y * TILE_WIDTH + threadIdx.y,
Col = blockIdx.x * TILE_WIDTH + threadIdx.x;
int Pvalue = 0;
for (int i = 0; i < (k-1)/TILE_WIDTH+1; ++i) {
if (Row < n && i*TILE_WIDTH+threadIdx.x < k)
sA[threadIdx.y*TILE_WIDTH + threadIdx.x] = a[Row*k + i*TILE_WIDTH+threadIdx.x];
else
sA[threadIdx.y*TILE_WIDTH + threadIdx.x] = 0;
if (Col < m && i*TILE_WIDTH+threadIdx.y < k)
sB[threadIdx.y*TILE_WIDTH + threadIdx.x] = b[(i*TILE_WIDTH+threadIdx.y)*m + Col];
else
sB[threadIdx.y*TILE_WIDTH + threadIdx.x] = 0;
__syncthreads();
for (int j = 0; j < TILE_WIDTH; ++j)
Pvalue += sA[threadIdx.y*TILE_WIDTH + j] * sB[j*TILE_WIDTH + threadIdx.x];
__syncthreads();
}
if (Row < n && Col < m)
c[Row*m+Col] = Pvalue;
}
typedef struct dim {
int n,k,m;
dim(int a, int b, int c) : n(a), k(b), m(c) {};
} dim;
int main() {
// Create matrices
// A = nxk, B = kxm, C = nxm
// printf("Enter valid dimension of matrices (A = nxk, B = kxm): \n");
int dev;
printf("[**] Input CUDA device no: ");
scanf("%d", &dev);
dim dim0 = dim(10000,9000,10000),
dim1 = dim(10000,10000,20000),
dim2 = dim(10000,20000,30000),
dim4 = dim(10000,20000,40000),
dim5 = dim(20000,20000,50000),
dim6 = dim(20000,30000,40000);
dim DIM[6] = {dim0, dim1, dim2, dim4, dim5, dim6};
// Multiprocessing constants
int TILE_ARRAY[4] = {16, 32, 48, 64};
// scanf("%d %d %d", &n, &k, &m);
for(int t = 0; t<4; t++) {
int TILE_WIDTH = TILE_ARRAY[t];
for(int j = 0; j<6; j++) {
int n = DIM[j].n, k = DIM[j].k, m = DIM[j].m;
unsigned int grid_rows = ceil(n / TILE_WIDTH) < 1 ? 1 : ceil(n/TILE_WIDTH);
unsigned int grid_cols = ceil(m / TILE_WIDTH) < 1 ? 1 : ceil(m/TILE_WIDTH);
const dim3 threadsPerBlock(TILE_WIDTH,TILE_WIDTH); // Must not exceed 1024 (max thread per block)
const dim3 blocksPerGrid( grid_cols, grid_rows);
// Initialize host matrices
int *h_A, *h_B, *h_C;
clock_t h_alloctime = clock();
h_A = (int*) malloc(sizeof(int)*k*n);
h_B = (int*) malloc(sizeof(int)*m*k);
h_C = (int*) malloc(sizeof(int)*n*m);
printf("[**] Using tile width = %d...\n", TILE_WIDTH);
printf("[**] Creating matrix A with dimension %d x %d...\n", n,k);
randomArray(h_A, n, k);
printf("[**] Creating matrix B with dimension %d x %d...\n", k,m);
randomArray(h_B, k, m);
//printf("[**] CPU Allocation time for the matrices: %.6f sec \n",(double)(clock()-h_alloctime)/CLOCKS_PER_SEC );
// Allocate memory space on the device
int *d_A, *d_B, *d_C;
cudaSetDevice(dev);
cudaError_t err;
clock_t d_alloctime = clock();
err = cudaMalloc((void **) &d_A, sizeof(int)*k*n);
if (err != cudaSuccess)
printf("Error malloc Matrix Ar: %s\n", cudaGetErrorString(err));
err = cudaMalloc((void **) &d_B, sizeof(int)*m*k);
if (err != cudaSuccess)
printf("Error malloc Matrix B: %s\n", cudaGetErrorString(err));
err = cudaMalloc((void **) &d_C, sizeof(int)*n*m);
if (err != cudaSuccess)
printf("Error malloc Matrix C: %s\n", cudaGetErrorString(err));
err = cudaMemcpy(d_A, h_A, sizeof(int)*k*n, cudaMemcpyHostToDevice);
if (err != cudaSuccess)
printf("Error memcpy Matrix A: %s\n", cudaGetErrorString(err));
err = cudaMemcpy(d_B, h_B, sizeof(int)*k*m, cudaMemcpyHostToDevice);
if (err != cudaSuccess)
printf("Error memcpy Matrix B: %s\n", cudaGetErrorString(err));
//printf("[**] GPU Allocation time for the matrices: %.6fsec \n",(double)(clock()-d_alloctime)/CLOCKS_PER_SEC );
cudaEvent_t start,end;
float ms, avems = 0.0;
printf(" Starting kernel program 'matmul_rec_glob' execution\n");
for(int i = 0; i<10; i++) {
cudaEventCreate(&start);
cudaEventCreate(&end);
cudaEventRecord(start, 0);
matmul_rec_glob<<< blocksPerGrid, threadsPerBlock >>>(d_A, d_B, d_C, n, k, m);
err = cudaGetLastError();
if (err != cudaSuccess)
printf("Error: %s\n", cudaGetErrorString(err));
cudaEventRecord(end, 0);
cudaEventSynchronize(end);
cudaEventElapsedTime(&ms, start, end);
// printf("\tIteration no. %d: %.6fsecs\n", i, ms);
avems+=ms;
cudaMemcpy(h_C, d_C, sizeof(int)*m*n, cudaMemcpyDeviceToHost);
cudaEventDestroy(start);
cudaEventDestroy(end);
}
printf("\t >>> Average kernel execution time: %.6fsec.\n", avems/10.0);
// printResults(h_A, h_B, h_C, n, k, m);
printf(" Starting kernel program 'matmul_rec_shared' execution\n");
avems = 0.0;
for(int i = 0; i<10; i++) {
cudaEventCreate(&start);
cudaEventCreate(&end);
cudaEventRecord(start, 0);
matmul_rec_shared<<< blocksPerGrid, threadsPerBlock, 2*TILE_WIDTH*TILE_WIDTH*sizeof(int) >>>(d_A, d_B, d_C, n, k, m, TILE_WIDTH);
cudaError_t err = cudaGetLastError();
if (err != cudaSuccess)
printf("Error: %s\n", cudaGetErrorString(err));
cudaEventRecord(end, 0);
cudaEventSynchronize(end);
cudaEventElapsedTime(&ms, start, end);
// printf("\tIteration no. %d: %.6f sec\n", i, ms);
avems+=ms;
cudaMemcpy(h_C, d_C, sizeof(int)*m*n, cudaMemcpyDeviceToHost);
cudaEventDestroy(start);
cudaEventDestroy(end);
}
printf("\t >>> Average kernel execution time: %.6f sec.\n", avems/10.0);
printf("[**] Freed memory. Done.\n\n");
// printResults(h_A, h_B, h_C, n, k, m);
cudaFree(d_A);
cudaFree(d_B);
cudaFree(d_C);
free(h_A);
free(h_B);
free(h_C);
// printf("[**] Freed memory. Done.\n");
}
}
return 0;
} |
9,716 | //note: please do not modify this file manually!
// this file has been generated automatically by BOAST version 0.99996
// by: make boast_kernels
/*
!=====================================================================
!
! S p e c f e m 3 D G l o b e V e r s i o n 7 . 0
! --------------------------------------------------
!
! Main historical authors: Dimitri Komatitsch and Jeroen Tromp
! Princeton University, USA
! and CNRS / University of Marseille, France
! (there are currently many more authors!)
! (c) Princeton University and CNRS / University of Marseille, April 2014
!
! This program is free software; you can redistribute it and/or modify
! it under the terms of the GNU General Public License as published by
! the Free Software Foundation; either version 2 of the License, or
! (at your option) any later version.
!
! This program is distributed in the hope that it will be useful,
! but WITHOUT ANY WARRANTY; without even the implied warranty of
! MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
! GNU General Public License for more details.
!
! You should have received a copy of the GNU General Public License along
! with this program; if not, write to the Free Software Foundation, Inc.,
! 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
!
!=====================================================================
*/
#ifndef INDEX2
#define INDEX2(isize,i,j) i + isize*j
#endif
#ifndef INDEX3
#define INDEX3(isize,jsize,i,j,k) i + isize*(j + jsize*k)
#endif
#ifndef INDEX4
#define INDEX4(isize,jsize,ksize,i,j,k,x) i + isize*(j + jsize*(k + ksize*x))
#endif
#ifndef INDEX5
#define INDEX5(isize,jsize,ksize,xsize,i,j,k,x,y) i + isize*(j + jsize*(k + ksize*(x + xsize*y)))
#endif
#ifndef NDIM
#define NDIM 3
#endif
#ifndef NGLLX
#define NGLLX 5
#endif
#ifndef NGLL2
#define NGLL2 25
#endif
#ifndef NGLL3
#define NGLL3 125
#endif
#ifndef NGLL3_PADDED
#define NGLL3_PADDED 128
#endif
#ifndef N_SLS
#define N_SLS 3
#endif
#ifndef IREGION_CRUST_MANTLE
#define IREGION_CRUST_MANTLE 1
#endif
#ifndef IREGION_INNER_CORE
#define IREGION_INNER_CORE 3
#endif
#ifndef IFLAG_IN_FICTITIOUS_CUBE
#define IFLAG_IN_FICTITIOUS_CUBE 11
#endif
#ifndef R_EARTH_KM
#define R_EARTH_KM 6371.0f
#endif
#ifndef COLORING_MIN_NSPEC_INNER_CORE
#define COLORING_MIN_NSPEC_INNER_CORE 1000
#endif
#ifndef COLORING_MIN_NSPEC_OUTER_CORE
#define COLORING_MIN_NSPEC_OUTER_CORE 1000
#endif
#ifndef BLOCKSIZE_TRANSFER
#define BLOCKSIZE_TRANSFER 256
#endif
static __device__ void compute_gradient_kernel(const int ijk, const int ispec, const float * scalar_field, float * vector_field_element, const float * hprime_xx, const float * d_xix, const float * d_xiy, const float * d_xiz, const float * d_etax, const float * d_etay, const float * d_etaz, const float * d_gammax, const float * d_gammay, const float * d_gammaz){
float temp1l;
float temp2l;
float temp3l;
float hp1;
float hp2;
float hp3;
float xixl;
float xiyl;
float xizl;
float etaxl;
float etayl;
float etazl;
float gammaxl;
float gammayl;
float gammazl;
int l;
int offset;
int offset1;
int offset2;
int offset3;
int I;
int J;
int K;
K = (ijk) / (NGLL2);
J = (ijk - ((K) * (NGLL2))) / (NGLLX);
I = ijk - ((K) * (NGLL2)) - ((J) * (NGLLX));
temp1l = 0.0f;
temp2l = 0.0f;
temp3l = 0.0f;
for (l = 0; l <= NGLLX - (1); l += 1) {
hp1 = hprime_xx[(l) * (NGLLX) + I];
hp2 = hprime_xx[(l) * (NGLLX) + J];
hp3 = hprime_xx[(l) * (NGLLX) + K];
offset1 = (K) * (NGLL2) + (J) * (NGLLX) + l;
offset2 = (K) * (NGLL2) + (l) * (NGLLX) + I;
offset3 = (l) * (NGLL2) + (J) * (NGLLX) + I;
temp1l = temp1l + (scalar_field[offset1]) * (hp1);
temp2l = temp2l + (scalar_field[offset2]) * (hp2);
temp3l = temp3l + (scalar_field[offset3]) * (hp3);
}
offset = (ispec) * (NGLL3_PADDED) + ijk;
xixl = d_xix[offset];
xiyl = d_xiy[offset];
xizl = d_xiz[offset];
etaxl = d_etax[offset];
etayl = d_etay[offset];
etazl = d_etaz[offset];
gammaxl = d_gammax[offset];
gammayl = d_gammay[offset];
gammazl = d_gammaz[offset];
vector_field_element[0] = (temp1l) * (xixl) + (temp2l) * (etaxl) + (temp3l) * (gammaxl);
vector_field_element[1] = (temp1l) * (xiyl) + (temp2l) * (etayl) + (temp3l) * (gammayl);
vector_field_element[2] = (temp1l) * (xizl) + (temp2l) * (etazl) + (temp3l) * (gammazl);
}
__global__ void compute_acoustic_kernel(const int * ibool, const float * rhostore, const float * kappastore, const float * hprime_xx, const float * d_xix, const float * d_xiy, const float * d_xiz, const float * d_etax, const float * d_etay, const float * d_etaz, const float * d_gammax, const float * d_gammay, const float * d_gammaz, const float * potential_dot_dot_acoustic, const float * b_potential_acoustic, const float * b_potential_dot_dot_acoustic, float * rho_ac_kl, float * kappa_ac_kl, const float deltat, const int NSPEC){
int ispec;
int ijk;
int ijk_ispec;
int ijk_ispec_padded;
int iglob;
float accel_elm[(3)];
float b_displ_elm[(3)];
float rhol;
float kappal;
float div_displ;
float b_div_displ;
__shared__ float scalar_field_displ[(NGLL3)];
__shared__ float scalar_field_accel[(NGLL3)];
ispec = blockIdx.x + (blockIdx.y) * (gridDim.x);
if (ispec < NSPEC) {
ijk = threadIdx.x;
ijk_ispec = ijk + (NGLL3) * (ispec);
ijk_ispec_padded = ijk + (NGLL3_PADDED) * (ispec);
iglob = ibool[ijk_ispec] - (1);
scalar_field_displ[ijk] = b_potential_acoustic[iglob];
scalar_field_accel[ijk] = potential_dot_dot_acoustic[iglob];
__syncthreads();
compute_gradient_kernel(ijk, ispec, scalar_field_displ, b_displ_elm, hprime_xx, d_xix, d_xiy, d_xiz, d_etax, d_etay, d_etaz, d_gammax, d_gammay, d_gammaz);
compute_gradient_kernel(ijk, ispec, scalar_field_accel, accel_elm, hprime_xx, d_xix, d_xiy, d_xiz, d_etax, d_etay, d_etaz, d_gammax, d_gammay, d_gammaz);
rhol = rhostore[ijk_ispec_padded];
rho_ac_kl[ijk_ispec] = rho_ac_kl[ijk_ispec] + ((deltat) * (rhol)) * ((accel_elm[0]) * (b_displ_elm[0]) + (accel_elm[1]) * (b_displ_elm[1]) + (accel_elm[2]) * (b_displ_elm[2]));
kappal = (rhol) / (kappastore[ijk_ispec_padded]);
div_displ = (kappal) * (potential_dot_dot_acoustic[iglob]);
b_div_displ = (kappal) * (b_potential_dot_dot_acoustic[iglob]);
kappa_ac_kl[ijk_ispec] = kappa_ac_kl[ijk_ispec] + ((deltat) * (div_displ)) * (b_div_displ);
}
}
|
9,717 | extern "C" __global__ void
normalize(float2* psi1, float2* psi2)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
float sqAbs1 = psi1[i].x * psi1[i].x + psi1[i].y * psi1[i].y;
float sqAbs2 = psi2[i].x * psi2[i].x + psi2[i].y * psi2[i].y;
float norm = sqrt(sqAbs1 + sqAbs2);
psi1[i].x /= norm;
psi1[i].y /= norm;
psi2[i].x /= norm;
psi2[i].y /= norm;
} |
9,718 | //Author: Manjari Pokala
#include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>
#include <assert.h>
#include <math.h>
//Reading array A from input file inp.txt
typedef struct {
int *array;
size_t used;
size_t size;
} Array;
void initArray(Array *a, size_t initialSize) {
a->array = (int*) malloc(initialSize * sizeof(int));
a->used = 0;
a->size = initialSize;
}
void insertArray(Array *a, int element) {
if (a->used == a->size) {
a->size += 1;
a->array =(int*) realloc(a->array, a->size * sizeof(int));
}
a->array[a->used++] = element;
}
Array initArrayA(){
FILE *fp;
char str[50000];
Array a;
initArray(&a, 1);
/* opening file for reading */
fp = fopen("inp.txt" , "r");
if(fp == NULL) {
printf("%s","error");
return a;
}
while( fgets (str, 50000, fp)!=NULL ) {
/* writing content to stdout */
// printf("%s\n", str);
char* token;
char* rest = str;
while ((token = strtok_r(rest, " , ", &rest)))
insertArray(&a, atoi(token));
}
fclose(fp);
return a;
}
//Asserts for GPU errors
#define gpuErrorCheck(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort=true)
{
if (code != cudaSuccess)
{
printf("GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort) exit(code);
}
}
__global__ void global_reduce_kernel(int * d_out, int * d_in, int size)
{
int myId = threadIdx.x + blockDim.x * blockIdx.x;
int tid = threadIdx.x;
// do reduction in global mem
for (unsigned int s = blockDim.x / 2; s > 0; s >>= 1)
{
if (tid < s && myId < size && myId+s < size)
{
d_in[myId] += d_in[myId + s];
}
__syncthreads(); // make sure all adds at one stage are done!
}
// only thread 0 writes result for this block back to global mem
if (tid == 0)
{
d_out[blockIdx.x] = d_in[myId];
}
}
__global__ void shmem_reduce_kernel(int * d_out, const int * d_in, int size)
{
// sdata is allocated in the kernel call: 3rd arg to <<<b, t, shmem>>>
extern __shared__ int sdata[];
int myId = threadIdx.x + blockDim.x * blockIdx.x;
int tid = threadIdx.x;
// load shared mem from global mem
sdata[tid] = d_in[myId];
__syncthreads(); // make sure entire block is loaded!
// do reduction in shared mem
for (unsigned int s = blockDim.x / 2; s > 0; s >>= 1)
{
if (tid < s && myId < size && myId+s < size)
{
sdata[tid] += sdata[tid + s];
}
__syncthreads(); // make sure all adds at one stage are done!
}
// only thread 0 writes result for this block back to global mem
if (tid == 0)
{
d_out[blockIdx.x] = sdata[0];
}
}
//kernel to create an intermediate array corresponding to given bins of array B
__global__ void global_count_range_bins_kernel(int * d_bins, int * d_binsin, int size, int x, int y)
{
int myId = threadIdx.x + blockDim.x * blockIdx.x;
// stride is the total number of threads in the grid
// Using stride increases the performance and benefits with scalability & thread reusage
int stride = blockDim.x * gridDim.x;
// assign flags in global memory
for (; myId < size; myId += stride)
{
if (d_binsin[myId] >= x && d_binsin[myId] <= y) {
d_bins[myId] = 1;
} else {
d_bins[myId] = 0;
}
__syncthreads(); // make sure all adds at one stage are done!
}
}
//kernel to perform parallel prefix sum
//assumes only 1 block (1 block can be utilized since we have only 10 elements)
__global__ void prefixsum(int *d_out, int * d_in, int size)
{
extern __shared__ int sh_mem[];
int tid = threadIdx.x;
int myId = blockIdx.x * blockDim.x + threadIdx.x;
sh_mem[tid] = d_in[myId];
__syncthreads();
if (myId < size)
{
for (int d = 1; d < blockDim.x; d *=2)
{
if (tid >= d) {
sh_mem[tid] += sh_mem[tid - d];
}
__syncthreads();
}
}
d_out[myId] = sh_mem[tid];
}
//Function to call corresponding kernel based on memory usage
void reduce(int * d_out, int * d_intermediate, int * d_in,
int size, bool usesSharedMemory)
{
const int maxThreadsPerBlock = 512;
int threads = maxThreadsPerBlock;
// handles non power of 2 arrays
int blocks = ceil(float(size) / float(maxThreadsPerBlock));
if (usesSharedMemory)
{
shmem_reduce_kernel<<<blocks, threads, threads * sizeof(int)>>>
(d_intermediate, d_in, size);
}
else
{
global_reduce_kernel<<<blocks, threads>>>
(d_intermediate, d_in, size);
gpuErrorCheck( cudaPeekAtLastError() );
gpuErrorCheck( cudaDeviceSynchronize() );
}
// now we're down to one block left, so reduce it
threads = blocks; // launch one thread for each block in prev step
blocks = 1;
if (usesSharedMemory)
{
shmem_reduce_kernel<<<blocks, threads, threads * sizeof(int)>>>
(d_out, d_intermediate, size);
}
else
{
global_reduce_kernel<<<blocks, threads>>>
(d_out, d_intermediate, size);
}
}
int main(int argc, char **argv)
{
FILE *q2a;
FILE *q2b;
FILE *q2c;
q2a = fopen("q2a.txt", "w");
q2b = fopen("q2b.txt", "w");
q2c = fopen("q2c.txt", "w");
int deviceCount;
cudaGetDeviceCount(&deviceCount);
if (deviceCount == 0) {
fprintf(q2a, "error: no devices supporting CUDA.\n");
exit(EXIT_FAILURE);
}
int dev = 0;
cudaSetDevice(dev);
cudaDeviceProp devProps;
if (cudaGetDeviceProperties(&devProps, dev) == 0)
{
fprintf(q2a, "Using device %d:\n", dev);
fprintf(q2a, "%s; global mem: %dB; compute v%d.%d; clock: %d kHz\n",
devProps.name, (int)devProps.totalGlobalMem,
(int)devProps.major, (int)devProps.minor,
(int)devProps.clockRate);
}
// generate the input array on the host
Array A = initArrayA();
int * h_in = A.array;
const int ARRAY_SIZE = A.size;
const int ARRAY_BYTES = A.size * sizeof(int);
fprintf(q2a, "array size is %d\n", ARRAY_SIZE);
// declare GPU memory pointers
int * d_in, * d_intermediate, * d_out, * d_bins, *d_binsin, *prefix_out, *prefix_in;
// allocate GPU memory
cudaMalloc((void **) &d_in, ARRAY_BYTES);
cudaMalloc((void **) &d_binsin, ARRAY_BYTES);
cudaMalloc((void **) &d_intermediate, ARRAY_BYTES); // overallocated
cudaMalloc((void **) &d_bins, ARRAY_BYTES);
cudaMalloc((void **) &d_out, sizeof(int));
// allocate memory for prefix sum, it has only 10 buckets
cudaMalloc((void **) &prefix_out, 10*sizeof(int));
cudaMalloc((void **) &prefix_in, 10*sizeof(int));
const int maxThreadsPerBlock = 512;
int threads = maxThreadsPerBlock;
// handles non power of 2 arrays
int blocks = ceil(float(ARRAY_SIZE) / float(maxThreadsPerBlock));
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
float elapsedTime;
//Problem 2a - Using Global Memory to get counts(from Reduction)
fprintf(q2a,"Using Global Memory to get counts(from Reduction\n");
// copy back the bin counts from GPU
int b[10];
// transfer the input array to the GPU
gpuErrorCheck( cudaMemcpy(d_binsin, h_in, ARRAY_BYTES, cudaMemcpyHostToDevice));
//fprintf(q2a, "Running global count\n");
//Bin 1
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 0, 99);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
gpuErrorCheck( cudaPeekAtLastError() );
gpuErrorCheck( cudaDeviceSynchronize() );
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 1 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[0], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 2
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 100, 199);
gpuErrorCheck( cudaPeekAtLastError() );
gpuErrorCheck( cudaDeviceSynchronize() );
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 2 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[1], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 3
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 200, 299);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 3 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[2], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 4
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 300, 399);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 4 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[3], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 5
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 400, 499);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 5 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[4], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 6
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 500, 599);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 6 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[5], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 7
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 600, 699);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 7 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[6], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 8
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 700, 799);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 8 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[7], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 9
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 800, 899);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 9 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[8], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 10
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 900, 999);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, false);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2a, "Bin 10 - average time elapsed using global memory: %f\n", elapsedTime);
cudaMemcpy(&b[9], d_out, sizeof(int), cudaMemcpyDeviceToHost);
for(int i = 0; i < 10; i++) {
fprintf(q2a, "Global Memory - count returned by device: %d\n", b[i]);
}
//Problem 2b - Using Shared Memory to get counts(from Reduction)
fprintf(q2b,"Using Shared Memory to get counts(from Reduction\n");
cudaGetDeviceCount(&deviceCount);
if (deviceCount == 0) {
fprintf(q2b, "error: no devices supporting CUDA.\n");
exit(EXIT_FAILURE);
}
dev = 0;
cudaSetDevice(dev);
if (cudaGetDeviceProperties(&devProps, dev) == 0)
{
fprintf(q2b, "Using device %d:\n", dev);
fprintf(q2b, "%s; global mem: %dB; compute v%d.%d; clock: %d kHz\n",
devProps.name, (int)devProps.totalGlobalMem,
(int)devProps.major, (int)devProps.minor,
(int)devProps.clockRate);
}
fprintf(q2b,"array size is %d\n", ARRAY_SIZE);
// copy back the bin counts from GPU
int s[10];
// transfer the input array to the GPU
cudaMemcpy(d_binsin, h_in, ARRAY_BYTES, cudaMemcpyHostToDevice);
//fprintf(q2b, "Running shared count\n");
//Bin 1
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 0, 99);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 1 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[0], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 2
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 100, 199);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 2 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[1], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 3
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 200, 299);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 3 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[2], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 4
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 300, 399);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 4 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[3], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 5
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 400, 499);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 5 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[4], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 6
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 500, 599);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 6 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[5], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 7
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 600, 699);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 7 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[6], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 8
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 700, 799);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 8 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[7], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 9
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 800, 899);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 9 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[8], d_out, sizeof(int), cudaMemcpyDeviceToHost);
//Bin 10
global_count_range_bins_kernel<<<blocks, threads>>>
(d_bins, d_binsin, ARRAY_SIZE, 900, 999);
cudaEventRecord(start, 0);
reduce(d_out, d_intermediate, d_bins, ARRAY_SIZE, true);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
fprintf(q2b, "Bin 10 - average time elapsed using shared memory: %f\n", elapsedTime);
cudaMemcpy(&s[9], d_out, sizeof(int), cudaMemcpyDeviceToHost);
for(int i = 0; i < 10; i++) {
fprintf(q2b, "Shared Memory - count returned by device: %d\n", s[i]);
}
//Problem 2c - Using Parallel Prefix Scan
fprintf(q2c,"Using Parallel Prefix Scan to generate C\n");
cudaGetDeviceCount(&deviceCount);
if (deviceCount == 0) {
fprintf(q2c, "error: no devices supporting CUDA.\n");
exit(EXIT_FAILURE);
}
dev = 0;
cudaSetDevice(dev);
if (cudaGetDeviceProperties(&devProps, dev) == 0)
{
fprintf(q2c, "Using device %d:\n", dev);
fprintf(q2c, "%s; global mem: %dB; compute v%d.%d; clock: %d kHz\n",
devProps.name, (int)devProps.totalGlobalMem,
(int)devProps.major, (int)devProps.minor,
(int)devProps.clockRate);
}
// transfer the input scan array to the GPU
cudaMemcpy(prefix_in, b, 10 * sizeof(int), cudaMemcpyHostToDevice);
cudaEventRecord(start, 0);
prefixsum<<<1, 10, 10 * sizeof(int)>>>(prefix_out, prefix_in, 10);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsedTime, start, stop);
gpuErrorCheck( cudaPeekAtLastError() );
gpuErrorCheck( cudaDeviceSynchronize() );
// copy back the prefix sum from GPU
int c[10];
cudaMemcpy(&c, prefix_out, 10*sizeof(int), cudaMemcpyDeviceToHost);
fprintf(q2c, "Prefix Sum - average time elapsed: %f\n", elapsedTime);
for(int i = 0; i < 10; i++) {
fprintf(q2c, "Prefix Sum returned by device: %d\n", c[i]);
}
// free GPU memory allocation
cudaFree(d_in);
cudaFree(d_intermediate);
cudaFree(d_out);
cudaFree(d_bins);
cudaFree(d_binsin);
cudaFree(prefix_out);
cudaFree(prefix_in);
return 0;
}
// Reference: https://github.com/manjaripokala/sum20-Parallel-algs/blob/master/cuda-examples/reduce.cu
|
9,719 | #include "includes.h"
using namespace std;
#define MEDIAN_DIMENSION 3 // For matrix of 3 x 3. We can Use 5 x 5 , 7 x 7 , 9 x 9......
#define MEDIAN_LENGTH 9 // Shoul be MEDIAN_DIMENSION x MEDIAN_DIMENSION = 3 x 3
#define BLOCK_WIDTH 16 // Should be 8 If matrix is of larger then of 5 x 5 elese error occur as " uses too much shared data " at surround[BLOCK_WIDTH*BLOCK_HEIGHT][MEDIAN_LENGTH]
#define BLOCK_HEIGHT 16// Should be 8 If matrix is of larger then of 5 x 5 elese error occur as " uses too much shared data " at surround[BLOCK_WIDTH*BLOCK_HEIGHT][MEDIAN_LENGTH]
__global__ void MedianFilter_gpu(unsigned short *Device_ImageData, int Image_Width, int Image_Height) {
__shared__ unsigned short surround[BLOCK_WIDTH*BLOCK_HEIGHT][MEDIAN_LENGTH];
int iterator;
const int Half_Of_MEDIAN_LENGTH = (MEDIAN_LENGTH / 2) + 1;
int StartPoint = MEDIAN_DIMENSION / 2;
int EndPoint = StartPoint + 1;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
const int tid = threadIdx.y*blockDim.y + threadIdx.x;
if (x >= Image_Width || y >= Image_Height)
return;
//Fill surround with pixel value of Image in Matrix Pettern of MEDIAN_DIMENSION x MEDIAN_DIMENSION
if (x == 0 || x == Image_Width - StartPoint || y == 0
|| y == Image_Height - StartPoint) {
}
else {
iterator = 0;
for (int r = x - StartPoint; r < x + (EndPoint); r++) {
for (int c = y - StartPoint; c < y + (EndPoint); c++) {
surround[tid][iterator] = *(Device_ImageData + (c*Image_Width) + r);
iterator++;
}
}
//Sort the Surround Array to Find Median. Use Bubble Short if Matrix oF 3 x 3 Matrix
//You can use Insertion commented below to Short Bigger Dimension Matrix
//// bubble short //
for (int i = 0; i<Half_Of_MEDIAN_LENGTH; ++i)
{
// Find position of minimum element
int min = i;
for (int l = i + 1; l<MEDIAN_LENGTH; ++l)
if (surround[tid][l] <surround[tid][min])
min = l;
// Put found minimum element in its place
unsigned short temp = surround[tid][i];
surround[tid][i] = surround[tid][min];
surround[tid][min] = temp;
}//bubble short end
//////insertion sort start //
/*int t,j,i;
for ( i = 1 ; i< MEDIAN_LENGTH ; i++) {
j = i;
while ( j > 0 && surround[tid][j] < surround[tid][j-1]) {
t= surround[tid][j];
surround[tid][j]= surround[tid][j-1];
surround[tid][j-1] = t;
j--;
}
}*/
////insertion sort end
*(Device_ImageData + (y*Image_Width) + x) = surround[tid][Half_Of_MEDIAN_LENGTH - 1]; // it will give value of surround[tid][4] as Median Value if use 3 x 3 matrix
__syncthreads();
}
} |
9,720 | #include "includes.h"
__global__ void calculation( int *a, int *b, int *c, int constant, int vector_size ) {
// write your code here
// Declare shared memory
// Bring in the data from global memory into shared memory
// Synchronize
// Do calculation using the values in shared memory
// Write output
} |
9,721 | __global__ void NormalizeW(float* g_VecW, float * g_NormW, float* g_VecV, int N)
{
// shared memory size declared at kernel launch
extern __shared__ float sNormData[];
unsigned int tid = threadIdx.x;
unsigned int globalid = blockIdx.x*blockDim.x + threadIdx.x;
if(tid==0) sNormData[0] = g_NormW[0];
__syncthreads();
// For thread ids greater than data space
if (globalid < N) {
g_VecV[globalid] = g_VecW[globalid]/sNormData[0];
}
} |
9,722 | #define THREADS 256
__global__ void hamming_matcher(
unsigned* out_idx,
unsigned* out_dist,
const unsigned max_dist,
const unsigned feat_len)
{
unsigned nquery = 6;
unsigned ntrain = 6;
unsigned f = blockDim.x * blockIdx.x + threadIdx.x;
unsigned tid = threadIdx.x;
__shared__ unsigned s_dist[THREADS];
__shared__ unsigned s_idx[THREADS];
s_dist[tid] = max_dist;
s_idx[tid] = 0xffffffff;
bool valid_feat = (f < ntrain);
for (unsigned j = 0; j < nquery; j++) {
s_dist[tid] = max_dist;
// Load one query feature that will be tested against all training
// features in current block
if (tid < feat_len && f < ntrain) {
out_dist[tid] = tid * nquery + j;
}
__syncthreads();
unsigned dist = 0;
if (tid < 32) {
if (s_dist[tid + 128] < s_dist[tid]) {
s_dist[tid] = s_dist[tid + 128];
s_idx[tid] = s_idx[tid + 128];
}
}
__syncthreads();
if (tid < 16) {
if (s_dist[tid + 64] < s_dist[tid]) {
s_dist[tid] = s_dist[tid + 64];
s_idx[tid] = s_idx[tid + 64];
}
}
__syncthreads();
if (tid < 8) {
if (s_dist[tid + 32] < s_dist[tid]) {
s_dist[tid] = s_dist[tid + 32];
s_idx[tid] = s_idx[tid + 32];
}
}
__syncthreads();
// Store best match in training features from block to the current
// query feature
if (f < ntrain) {
out_dist[j * gridDim.x + blockIdx.x] = s_dist[0];
out_idx[j * gridDim.x + blockIdx.x] = s_idx[0];
}
}
} |
9,723 | #include <iostream>
using namespace std;
__global__ void mini(int *a)
{
int tid = threadIdx.x;
int step_size = 1;
int n_thread = blockDim.x;
int f,s;
while(n_thread>0)
{
if(tid<n_thread)
{
f = tid*step_size*2;
s = f + step_size;
if(a[f]>=a[s])
a[f] = a[s];
}
step_size<<=1;
n_thread>>=1;
}
}
int main()
{
int *a,*b,size,n;
int *d_a;
cin>>n;
size = n*sizeof(int);
a = (int *)malloc(size);
b = (int *)malloc(sizeof(int));
cudaMalloc(&d_a,size);
for(int i=0;i<n;i++)
{
a[i] = rand()%100;
}
for(int i=0;i<n;i++)
{
cout<<a[i]<<" ";
}
cudaMemcpy(d_a,a,size,cudaMemcpyHostToDevice);
clock_t start = clock();
mini<<<1,n/2>>>(d_a);
cout<<"time: "<<(float)(clock()-start)/CLOCKS_PER_SEC<<endl;
cudaMemcpy(b,d_a,size,cudaMemcpyDeviceToHost);
cout<<"min is :"<<b[0];
return 0;
} |
9,724 | #include "includes.h"
__global__ void forward_local_avgpool_layer_kernel(int n, int in_h, int in_w, int in_c, int stride_x, int stride_y, int size, int pad, float *input, float *output)
{
int h = (in_h + pad - size) / stride_y + 1;
int w = (in_w + pad - size) / stride_x + 1;
int c = in_c;
int id = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
if (id >= n) return;
int j = id % w;
id /= w;
int i = id % h;
id /= h;
int k = id % c;
id /= c;
int b = id;
int w_offset = -pad / 2;
int h_offset = -pad / 2;
int out_index = j + w*(i + h*(k + c*b));
float avg = 0;
int counter = 0;
int l, m;
for (l = 0; l < size; ++l) {
for (m = 0; m < size; ++m) {
int cur_h = h_offset + i*stride_y + l;
int cur_w = w_offset + j*stride_x + m;
int index = cur_w + in_w*(cur_h + in_h*(k + b*in_c));
int valid = (cur_h >= 0 && cur_h < in_h &&
cur_w >= 0 && cur_w < in_w);
if (valid) {
counter++;
avg += input[index];
}
}
}
output[out_index] = avg / counter; // as CUDNN_POOLING_AVERAGE_COUNT_EXCLUDE_PADDING
} |
9,725 | /* LA-CC-16080
Copyright © 2016 Priscilla Kelly and Los Alamos National Laboratory. All Rights Reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
3. The name of the author may not be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY Priscilla Kelly and Los Alamos National Laboratory "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Priscilla Kelly <priscilla.noreen@gmail.com>
GPULife loadTile in Cuda
*/
#include "stdio.h"
#include "stdlib.h"
/***************************************/
/* External c subroutine for CUDA */
/***************************************/
extern "C" void call_loadTile_CUDA(int flag, int elements, int *Matrix, int **pointer2device) {
size_t matSize = elements*sizeof(int);
cudaError_t err = cudaSuccess;
if (flag == 0) {
/***************************************/
/* Allocate Matrix to the GPU */
/***************************************/
int *device;
err = cudaMalloc(&device, matSize);
if(err != cudaSuccess) {
fprintf(stderr, "Failed to allocate device vector (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// move matrix to device
err = cudaMemcpy(device,Matrix,matSize,cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr, "%s Failed at line %s !\n",__FILE__,__LINE__);
exit(EXIT_FAILURE);
}
*pointer2device = device;
return;
}
if (flag == 1) {
/***************************************/
/* Free Device Global Memory */
/***************************************/
err = cudaFree(*pointer2device);
if (err != cudaSuccess){
fprintf(stderr, "Failed to free device!\n");
exit(EXIT_FAILURE);
}
}
if (flag == 3) {
cudaDeviceSynchronize();
int *host_subMat = (int *)malloc(matSize);
if(host_subMat == NULL) {
fprintf(stderr, "Failed to alocate host vector!\n");
exit(EXIT_FAILURE);
}
err = cudaMemcpy(host_subMat,*pointer2device,matSize,cudaMemcpyDeviceToHost);
if (err != cudaSuccess) {
fprintf(stderr,"Failed to copy the submat from device (error code %s)!\n",cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
int i,j;
int c=0;
printf("New Rank\n");
for(i=0;i<6;i++) {
printf("[");
for(j=0;j<6;j++) {
printf(" %d ",host_subMat[c]);
c++;
}
printf("]\n");
}
printf("\n");
return;
}
}
|
9,726 | #include <stdio.h>
//#include "cuPrintf.cu"
typedef unsigned long long BMType;
typedef unsigned int SAType;
__global__ void binarySearch(BMType array[], int arraySize,
BMType query[], int querySize) {
unsigned int threadId = blockIdx.x * blockDim.x + threadIdx.x;
int left = 0;
int right = arraySize - 1;
const BMType target = query[threadId];
while (left <= right)
{
int mid = (left + right) >> 1;
BMType midValue = array[mid];
if(midValue > target) {
right = mid - 1;
} else if(midValue < target) {
left = mid + 1;
} else {
for (mid = mid - 1; mid >= 0; --mid ) {
if (array[mid] != target) {
break;
}
}
query[threadId] = mid + 1;
return;
}
}
query[threadId] = -1;
}
extern "C" void cudaBinarySearch(BMType* array, int arraySize, BMType* query, int querySize )
{
printf("Starting binary search...\n");
binarySearch <<<querySize / 256 + 1, 256>>> (array, arraySize, query, querySize);
cudaThreadSynchronize();
printf("Binary search is finished...\n");
}
struct ShortReads
{
char* data;
int* offsets;
int* sizes;
int count;
};
struct BMArray
{
BMType* data;
int size;
};
struct SArray
{
SAType* data;
int size;
};
struct AlgSettings
{
BMType bitFilter;
int refStartPos;
int loadedPartSize;
int CMAX;
int w;
};
__device__ int lowerBound(BMType* bmArray, int bmArraySize, BMType target, BMType bitFilter) {
int left = 0;
int right = bmArraySize - 1;
int result = -1;
while (left <= right)
{
int mid = (left + right) >> 1;
long long rc = (bmArray[mid]&bitFilter) - (target&bitFilter);
if(rc > 0) {
right = mid - 1;
} else if(rc < 0) {
left = mid + 1;
} else {
for (mid = mid - 1; mid >= 0; --mid ) {
if ((bmArray[mid]&bitFilter) != (target&bitFilter)) {
break;
}
}
result = mid + 1;
break;
}
}
return result;
}
__device__ BMType calcBitValue(char* readsData, int readOffset, int length, int charsInMask, SAType* bitTable)
{
const int bitCharLen = 2;
BMType bitValue = 0;
//cuPrintf("L = %d, charsInMask = %d\n",length,charsInMask);
//cuPrintf("bw=%ullx\n", bitValue);
for (int i = 0; i < length; i++) {
char c = readsData[readOffset+i];
//cuPrintf("C=%c\n",c);
//cuPrintf("bw=%llx\n", bitValue);
bitValue = (bitValue << bitCharLen) | bitTable[c - 65];
}
bitValue <<= 2*charsInMask - bitCharLen*length;
return bitValue;
}
__device__ void initBitTable(SAType* bitTable)
{
bitTable['A' - 65] = 0x0; //00
bitTable['C' - 65] = 0x1; //01
bitTable['T' - 65] = 0x2; //10
bitTable['G' - 65] = 0x3; //11
}
__device__ bool compare(const char *sourceSeq, const char *querySeq, int startPos, int w, int& c, int CMAX, int length)
{
// forward collect
for (int i=startPos+w; i<length && c <= CMAX; i++) {
char c1 = querySeq[i];
char c2 = sourceSeq[i];
//cuPrintf("F: %c %c pos=%d\n",c1,c2,i);
c += (c1 == c2) ? 0 : 1;
}
if (c>CMAX) {
return false;
}
// backward collect
for (int i=startPos-1; i>=0 && c <= CMAX; i--) {
char c1 = querySeq[i];
char c2 = sourceSeq[i];
c += (c1 == c2) ? 0 : 1;
//cuPrintf("B: %c %c pos=%d\n",c1,c2,i);
}
if (c <= CMAX) {
return true;
}
return false;
}
__global__ void alignReadsKernel(ShortReads reads,
char* refSeq,
int refSeqSize,
SArray sArray,
BMArray bmArray,
AlgSettings s,
SAType* results)
{
const int CHARS_IN_MASK = 31;
unsigned int threadId = blockIdx.x * blockDim.x + threadIdx.x;
if (threadId >= reads.count) {
return;
}
int readOffset = reads.offsets[threadId];
int readSize = reads.sizes[threadId];
unsigned int bitTable[32];
initBitTable(bitTable);
/*
if (threadId == 0) {
cuPrintf("Offset is %d\n", readOffset);
cuPrintf("Read size is: %d\n", readSize);
cuPrintf("Read first symbol is %c\n", reads.data[0]);
cuPrintf("First symbol of ref seq is %c\n", refSeq[0]);
cuPrintf("Read last symbol is %c\n", reads.data[readOffset + readSize - 1]);
}*/
int CMAX = s.CMAX;
int q = readSize / (CMAX + 1);
SAType result = -1;
int bestC = 0;
for (int startPosInRead = 0; startPosInRead < readSize - s.w + 1; startPosInRead += q) {
int len = readSize - startPosInRead > CHARS_IN_MASK ? CHARS_IN_MASK : readSize - startPosInRead;
BMType bitValue = calcBitValue(reads.data, readOffset + startPosInRead, len, CHARS_IN_MASK, bitTable);
SAType bmResult = lowerBound(bmArray.data, bmArray.size, bitValue, s.bitFilter);
//cuPrintf("BW result is %u\n", bmResult);
if (bmResult == -1) {
continue;
}
for (SAType k = bmResult; (k < s.loadedPartSize) && (bitValue & s.bitFilter)==(bmArray.data[k] & s.bitFilter); k++) {
SAType pos = sArray.data[k];
SAType firstSymbolPos = pos - startPosInRead;
/*cuPrintf("pos is %d\n", pos);
cuPrintf("startPosInRead=%d\n", startPosInRead);
cuPrintf("firstSymbolPos=%d\n", firstSymbolPos);*/
if (firstSymbolPos == result) {
continue;
}
//TODO: check if valid pos in sense of sequence ends...
/*
if (!isValidPos( pos + loadedSeqStart, readStartPos, readSize, fisrtSymbol, q)) {
continue;
}
*/
char* refBuff = refSeq + firstSymbolPos;
char* readBuff = reads.data + readOffset;
int c = 0;
if (compare(refBuff, readBuff, startPosInRead, s.w, c, CMAX, readSize)) {
//cuPrintf("c=%d,CMAX=%d\n",c, CMAX);
result = firstSymbolPos;
if (0 == c) {
break;
}
bestC = c;
CMAX = bestC - 1;
}
}
}
//cuPrintf("Result is %d, mismatch rate is %d\n", result,bestC);
results[2*threadId] = result + s.refStartPos;
results[2*threadId + 1] = bestC;
}
extern "C" void cudaAlignReads(char* readsData,
int* readSizes,
int* readOffsets,
int readsNumber,
char* refSeq,
int refSeqSize,
SAType* sArrayData,
int sArraySize,
BMType* bmArrayData,
int bmArraySize,
BMType bitFilter,
int refStartPos,
int loadedPartSize,
int CMAX,
int w,
SAType* results)
{
printf("Starting aligning reads with CUDA...\n");
ShortReads reads;
reads.data = readsData;
reads.sizes = readSizes;
reads.offsets = readOffsets;
reads.count = readsNumber;
BMArray bmArray;
bmArray.data = bmArrayData;
bmArray.size = bmArraySize;
SArray sArray;
sArray.data = sArrayData;
sArray.size = sArraySize;
AlgSettings settings;
settings.bitFilter = bitFilter;
settings.refStartPos = refStartPos;
settings.loadedPartSize = loadedPartSize;
settings.CMAX = CMAX;
settings.w = w;
//cudaPrintfInit(10*1024*1024);
alignReadsKernel <<<readsNumber / 256 + 1, 256>>> (reads, refSeq, refSeqSize,
sArray, bmArray, settings, results);
//cudaPrintfDisplay(stdout, true);
cudaThreadSynchronize();
//cudaPrintfEnd();
printf("Finished aligning reads with CUDA\n");
}
|
9,727 |
/**
* Copyright 1993-2012 NVIDIA Corporation. All rights reserved.
*
* Please refer to the NVIDIA end user license agreement (EULA) associated
* with this source code for terms and conditions that govern your use of
* this software. Any use, reproduction, disclosure, or distribution of
* this software and related documentation outside the terms of the EULA
* is strictly prohibited.
*/
#include <stdio.h>
#include <stdlib.h>
#include <cuda.h>
#define Width 4
#define TILE_WIDTH 2
__global__ void mat_mul(int *a, int *b,int *ab, int width)
{
// shorthand
int tx = threadIdx.x, ty = threadIdx.y;
int bx = blockIdx.x, by = blockIdx.y;
// allocate tiles in __shared__ memory
__shared__ float s_a[TILE_WIDTH][TILE_WIDTH];
__shared__ float s_b[TILE_WIDTH][TILE_WIDTH];
// calculate the row & col index
int row = by*blockDim.y + ty;
int col = bx*blockDim.x + tx;
int result = 0;
// loop over the tiles of the input in phases
for(int p = 0; p < width/TILE_WIDTH; ++p)
{
// collaboratively load tiles into __shared__
s_a[ty][tx] = a[row*width + (p*TILE_WIDTH + tx)];
s_b[ty][tx] = b[(p*TILE_WIDTH + ty)*width + col];
__syncthreads();
// dot product between row of s_a and col of s_b
for(int k = 0; k < TILE_WIDTH; ++k)
result += s_a[ty][k] * s_b[k][tx];
__syncthreads();
}
ab[row*width+col] = result;
}
int main()
{
int mat_size=Width*Width*sizeof(int); //Calculate memory size required for float matrix
//int tot_elements=Width*Width;
int M[Width][Width],N[Width][Width],P[Width][Width]; // Host matrix pointers
int i=0,j=0;
int *Md,*Nd,*Pd; //Matrix Pointer on device memoryi.e GPU
printf("\nEntering elements for matrix");
for(i=0;i<Width;i++)
{
for(j=0;j<Width;j++)
{
M[i][j]=1;
N[i][j]=1;
}
}
printf("Matrix M=\n ");
for(i=0;i<Width;i++)
{
for(j=0;j<Width;j++)
{
printf("%d\t",M[i][j]);
}
printf("\n");
}
printf("Matrix N=\n ");
for(i=0;i<Width;i++)
{
for(j=0;j<Width;j++)
{
printf("%d\t",N[i][j]);
}
printf("\n");
}
cudaMalloc((void**)&Md,mat_size); //Allocate memory on device global memory
cudaMemcpy(Md,M,mat_size,cudaMemcpyHostToDevice); //Copy matrix data from host to device memory
cudaMalloc((void**)&Nd,mat_size);
cudaMemcpy(Nd,N,mat_size,cudaMemcpyHostToDevice);
cudaMalloc((void**)&Pd,mat_size);
dim3 dimGrid(TILE_WIDTH,TILE_WIDTH); //Variable for threads arrangement in a block.
dim3 dimBlock(Width/TILE_WIDTH,Width/TILE_WIDTH); //Variable for blocks arrangement in a grid.
mat_mul<<<dimGrid,dimBlock>>>(Md,Nd,Pd,Width); //Kernel invocation with grid and block specification in angle brackets
cudaMemcpy(P,Pd,mat_size,cudaMemcpyDeviceToHost); //Copy resultant matrix from device to host
//display the resultant matrix
printf("Product=\n ");
for(i=0;i<Width;i++)
{
for(j=0;j<Width;j++)
{
printf("%d\t",P[i][j]);
}
printf("\n");
}
//Free device memory
cudaFree(Md);
cudaFree(Nd);
cudaFree(Pd);
}
|
9,728 | __device__ inline void add(int4& a, const uchar4& b) {
a.x += b.x;
a.y += b.y;
a.z += b.z;
}
extern "C" __global__
void smooth1(const uchar4* d_input, uchar4* d_output,
const int width, const int height, const int depth,
const int windowSize) {
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
const int z = blockIdx.z * blockDim.z + threadIdx.z;
if (x < width && y < height && z < depth) {
int4 a = make_int4(0, 0, 0, 0);
int count = 0;
for (int dz = -windowSize; dz <= windowSize; dz ++) {
for (int dy = -windowSize; dy <= windowSize; dy ++) {
for (int dx = -windowSize; dx <= windowSize; dx ++) {
const int nx = x + dx;
const int ny = y + dy;
const int nz = z + dz;
if (0 <= nx && nx < width
&& 0 <= ny && ny < height
&& 0 <= nz && nz < depth) {
const long idx = nz * (width*height) + ny * width + nx;
#ifdef READ
add(a, d_input[idx]);
#endif
count++;
}
}
}
}
const long idx = z * (width*height) + y * width + x;
#ifdef WRITE
d_output[idx] = make_uchar4(a.x/count, a.y/count, a.z/count, 255);
#endif
}
}
extern "C" __global__
void smooth3(void) {
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
const int z = blockIdx.z * blockDim.z + threadIdx.z;
}
extern "C" __global__
void smooth2(const uchar4* d_input, uchar4* d_output) {
const int width = 1024;
const int height= 1024;
const int depth = 1;
const int windowSize = 1;
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
const int z = blockIdx.z * blockDim.z + threadIdx.z;
/*
if (x < width && y < height && z < depth) {
int4 a = make_int4(0, 0, 0, 0);
int count = 0;
for (int dz = -windowSize; dz <= windowSize; dz ++) {
for (int dy = -windowSize; dy <= windowSize; dy ++) {
for (int dx = -windowSize; dx <= windowSize; dx ++) {
const int nx = x + dx;
const int ny = y + dy;
const int nz = z + dz;
if (0 <= nx && nx < width
&& 0 <= ny && ny < height
&& 0 <= nz && nz < depth) {
const long idx = nz * (width*height) + ny * width + nx;
#ifdef READ
add(a, d_input[idx]);
#endif
count++;
}
}
}
}
const long idx = z * (width*height) + y * width + x;
#ifdef WRITE
d_output[idx] = make_uchar4(a.x/count, a.y/count, a.z/count, 255);
#endif
}
*/
}
|
9,729 | // Implement SSSP on CUDA.
// The graph is not weighted but it is directed. The BFS algorithms is same just have to change the graph to unwieghted.
// Error handler was copied from Dr. Rama's colab file shared to us on google classroom
#include<stdio.h>
#include<stdlib.h>
#include<time.h>
#define HANDLE_ERROR( err ) ( HandleError( err, __FILE__, __LINE__ ) )
__managed__ int n;
static void HandleError( cudaError_t err, const char *file, int line ) {
if (err != cudaSuccess) {
printf( "%s in %s at line %d\n", cudaGetErrorString(err), file, line);
exit(EXIT_FAILURE);
}
}
__global__ void SSSP_Kernel1(int *Va, int *Ea, int *Wa, int *Ma, int *Ca, int *Ua) {
int tid = threadIdx.x;
if (tid < n) {
if (Ma[tid]) {
Ma[tid] = 0;
for (int i = Va[tid]; i < Va[tid + 1]; i++) {
int j = Ea[i];
int k = Ca[tid] + Wa[j];
if (Ua[j] > k) Ua[j] = k;
}
}
}
}
__global__ void SSSP_Kernel2 (int *Va, int *Ea, int *Wa, int *Ma, int *Ca, int *Ua) {
int tid = threadIdx.x;
if (tid < n) {
if(Ca[tid] > Ua[tid]) {
Ca[tid] = Ua[tid];
Ma[tid] = 1;
}
Ua[tid] = Ca[tid];
}
}
int main() {
srand(time(0));
n = 50;
int src = rand() % n;
int limit1 = 5; // Limit on maximum number of edges from a vertex
int limit2 = 500; // Limit on weights
printf("Number of Vertices = %d\nStarting Vertex = %d\n", n, src);
int *Va;
int *c_Va;
int *Ea;
int *c_Ea;
int *Wa;
int *c_Wa;
int end = 0;
Va = (int *)malloc((n + 1) * sizeof(int));
HANDLE_ERROR(cudaMalloc((void **)&c_Va, (n + 1) * sizeof(int)));
for (int i =0; i < n; i++) {
Va[i] = end;
end = end + (rand() % limit1);
}
Va[n] = end;
HANDLE_ERROR(cudaMemcpy(c_Va, Va, (n + 1) * sizeof(int), cudaMemcpyHostToDevice));
Ea = (int *)malloc(end * sizeof(int));
Wa = (int *)malloc(end * sizeof(int));
int tWeight = 0;
HANDLE_ERROR(cudaMalloc((void **)&c_Ea, end * sizeof(int)));
HANDLE_ERROR(cudaMalloc((void **)&c_Wa, end * sizeof(int)));
for (int i = 0; i < end; i++) {
Ea[i] = (rand()) % n;
Wa[i] = (rand()) % limit2;
tWeight = tWeight + Wa[i];
}
tWeight = tWeight * 10;
HANDLE_ERROR(cudaMemcpy(c_Ea, Ea, end * sizeof(int), cudaMemcpyHostToDevice));
HANDLE_ERROR(cudaMemcpy(c_Wa, Wa, end * sizeof(int), cudaMemcpyHostToDevice));
/*
Uncomment this to see the graph
for (int i = 0; i < n; i++) printf("%d ", Va[i]);
puts(" ");
for (int i = 0; i < end; i++) printf("%d ", Ea[i]);
puts(" ");
for (int i = 0; i < end; i++) printf("%d ", Wa[i]);
puts(" ");
/**/
int *T;
T = (int *) malloc(n * sizeof(n));
int *c_Ma;
HANDLE_ERROR(cudaMalloc((void **)&c_Ma, n * sizeof(int)));
memset(T, 0, n * sizeof(int));
T[src] = 1;
HANDLE_ERROR(cudaMemcpy(c_Ma, T, n * sizeof(int), cudaMemcpyHostToDevice));
int *c_Ua;
HANDLE_ERROR(cudaMalloc((void **)&c_Ua, n * sizeof(int)));
for (int i = 0; i < n; i++) T[i] = tWeight;
T[src] = 0;
HANDLE_ERROR(cudaMemcpy(c_Ua, T, n * sizeof(int), cudaMemcpyHostToDevice));
int *c_Ca;
HANDLE_ERROR(cudaMalloc((void **)&c_Ca, n * sizeof(int)));
HANDLE_ERROR(cudaMemcpy(c_Ca, T, n * sizeof(int), cudaMemcpyHostToDevice));
int flag = 1;
do {
flag = 0;
SSSP_Kernel1 <<<1, n>>> (c_Va, c_Ea, c_Wa, c_Ma, c_Ca, c_Ua);
cudaDeviceSynchronize();
SSSP_Kernel2 <<<1, n>>> (c_Va, c_Ea, c_Wa, c_Ma, c_Ca, c_Ua);
cudaDeviceSynchronize();
HANDLE_ERROR(cudaMemcpy(T, c_Ma, n * sizeof(int), cudaMemcpyDeviceToHost));
for (int i = 0; i < n; i++) {
if (T[i]) {
flag = 1;
break;
}
}
} while(flag);
HANDLE_ERROR(cudaMemcpy(T, c_Ca, n * sizeof(int), cudaMemcpyDeviceToHost));
for (int i = 0; i < n; i++)
printf("cost to reach %dth node = %d\n", i, T[i]);
printf("\nNote: Cost = %d, means you can not reach the node from the current starting node\n", tWeight);
free(Va);
free(Ea);
free(Wa);
free(T);
cudaFree(c_Va);
cudaFree(c_Ea);
cudaFree(c_Wa);
cudaFree(c_Ma);
cudaFree(c_Ua);
cudaFree(c_Ca);
return 0;
}
|
9,730 | #include "includes.h"
__global__ void add(int * A, int * B, int * C){
int thread = blockIdx.x*blockDim.x + threadIdx.x;
C[thread] = A[thread] + B[thread];
} |
9,731 | #include<stdio.h>
#include<cuda_runtime.h>
/*#define CHECK(call)
{
const cudaError_t error = call;
if(error!= cudaSuccess)
{
printf("error: %s:%d, ",__FILE__,__LINE__);
printf("code: %d, reason: %s\n",error, cudaGetErrorString(error));
exit(1);
}
}*/
__global__ void hellowfromgpu(void)// GPU
{
printf("hellow world from GPU\n");
}
//for CPU//
int main()
{
printf("hellow from CPU\n");
hellowfromgpu <<<1,10>>>();
cudaDeviceReset();
return 0;
}
|
9,732 | #include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#include "cuda.h"
#include <string.h>
#define MAXBLOCKSIZE 512
int Size;
float *a, *b, *finalVec;
float *m;
FILE *fp;
void ForwardSub();
void BackSub();
void checkCUDAError(const char *msg);
void InitPerRun()
{
int i;
for (i=0; i<Size*Size; i++)
*(m+i) = 0.0;
}
void InitMat(float *ary, int nrow, int ncol)
{
int i, j;
for (i=0; i<nrow; i++) {
for (j=0; j<ncol; j++) {
fscanf(fp, "%f", ary+Size*i+j);
}
}
}
void InitAry(float *ary, int ary_size)
{
int i;
for (i=0; i<ary_size; i++) {
fscanf(fp, "%f", &ary[i]);
}
}
void PrintMat(float *ary, int nrow, int ncol)
{
int i, j;
for (i=0; i<nrow; i++) {
for (j=0; j<ncol; j++) {
printf("%8.2f ", *(ary+Size*i+j));
}
printf("\n");
}
printf("\n");
}
__global__ void Fan1(float *m_cuda, float *a_cuda, int Size, int t)
{
if(threadIdx.x + blockIdx.x * blockDim.x >= Size-1-t) return;
*(m_cuda+Size*(blockDim.x*blockIdx.x+threadIdx.x+t+1)+t) = *(a_cuda+Size*(blockDim.x*blockIdx.x+threadIdx.x+t+1)+t) / *(a_cuda+Size*t+t);
}
__global__ void Fan2(float *m_cuda, float *a_cuda, float *b_cuda,int Size, int j1, int t)
{
if(threadIdx.x + blockIdx.x * blockDim.x >= Size-1-t) return;
if(threadIdx.y + blockIdx.y * blockDim.y >= Size-t) return;
int xidx = blockIdx.x * blockDim.x + threadIdx.x;
int yidx = blockIdx.y * blockDim.y + threadIdx.y;
a_cuda[Size*(xidx+1+t)+(yidx+t)] -= m_cuda[Size*(xidx+1+t)+t] * a_cuda[Size*t+(yidx+t)];
if(yidx == 0){
b_cuda[xidx+1+t] -= m_cuda[Size*(xidx+1+t)+(yidx+t)] * b_cuda[t];
}
}
void ForwardSub()
{
int t;
float *m_cuda,*a_cuda,*b_cuda;
cudaMalloc((void **) &m_cuda, Size * Size * sizeof(float));
cudaMalloc((void **) &a_cuda, Size * Size * sizeof(float));
cudaMalloc((void **) &b_cuda, Size * sizeof(float));
cudaMemcpy(m_cuda, m, Size * Size * sizeof(float),cudaMemcpyHostToDevice );
cudaMemcpy(a_cuda, a, Size * Size * sizeof(float),cudaMemcpyHostToDevice );
cudaMemcpy(b_cuda, b, Size * sizeof(float),cudaMemcpyHostToDevice );
int block_size,grid_size;
block_size = MAXBLOCKSIZE;
grid_size = (Size/block_size) + (!(Size%block_size)? 0:1);
dim3 dimBlock(block_size);
dim3 dimGrid(grid_size);
int blockSize2d, gridSize2d;
blockSize2d = 4;
gridSize2d = (Size/blockSize2d) + (!(Size%blockSize2d?0:1));
dim3 dimBlockXY(blockSize2d,blockSize2d);
dim3 dimGridXY(gridSize2d,gridSize2d);
struct timeval time_start;
gettimeofday(&time_start, NULL);
for (t=0; t<(Size-1); t++) {
Fan1<<<dimGrid,dimBlock>>>(m_cuda,a_cuda,Size,t);
cudaThreadSynchronize();
Fan2<<<dimGridXY,dimBlockXY>>>(m_cuda,a_cuda,b_cuda,Size,Size-t,t);
cudaThreadSynchronize();
checkCUDAError("Fan2");
}
struct timeval time_end;
gettimeofday(&time_end, NULL);
// totalKernelTime = (time_end.tv_sec * 1000000 + time_end.tv_usec) - (time_start.tv_sec * 1000000 + time_start.tv_usec);
cudaMemcpy(m, m_cuda, Size * Size * sizeof(float),cudaMemcpyDeviceToHost );
cudaMemcpy(a, a_cuda, Size * Size * sizeof(float),cudaMemcpyDeviceToHost );
cudaMemcpy(b, b_cuda, Size * sizeof(float),cudaMemcpyDeviceToHost );
cudaFree(m_cuda);
cudaFree(a_cuda);
cudaFree(b_cuda);
}
void BackSub()
{
finalVec = (float *) malloc(Size * sizeof(float));
int i,j;
for(i=0;i<Size;i++){
finalVec[Size-i-1]=b[Size-i-1];
for(j=0;j<i;j++)
{
finalVec[Size-i-1]-=*(a+Size*(Size-i-1)+(Size-j-1)) * finalVec[Size-j-1];
}
finalVec[Size-i-1]=finalVec[Size-i-1]/ *(a+Size*(Size-i-1)+(Size-i-1));
}
}
void checkCUDAError(const char *msg)
{
cudaError_t err = cudaGetLastError();
if( cudaSuccess != err)
{
fprintf(stderr, "Cuda error: %s: %s.\n", msg,
cudaGetErrorString( err) );
exit(EXIT_FAILURE);
}
}
void PrintAry(float *ary, int ary_size)
{
int i;
for (i=0; i<ary_size; i++) {
printf("%8.2f ", ary[i]);
}
printf("\n\n");
}
int main()
{
fp=fopen("samplege.txt","r");
fscanf(fp, "%d", &Size);
a = (float *) malloc(Size * Size * sizeof(float));
InitMat(a, Size, Size);
b = (float *) malloc(Size * sizeof(float));
InitAry(b, Size);
m = (float *) malloc(Size * Size * sizeof(float));
InitPerRun();
printf("Matrix a is: \n");
PrintMat(a, Size, Size);
printf("Array b is: \n");
PrintAry(b, Size);
ForwardSub();
BackSub();
printf("The final solution is: \n");
PrintAry(finalVec,Size);
free(m);
free(a);
free(b);
}
|
9,733 | #include <cuda_runtime.h>
#include <stdio.h>
int main(int argc,char **argv){
int nElem=1024;
dim3 block (1024);
dim3 grid ((nElem+block.x-1)/block.x);
printf("grid.x %d block.x %d \n",grid.x,block.x);
block.x=512;
grid.x=(nElem+block.x-1)/block.x;
printf("grid.x %d block.x %d \n",grid.x,block.x);
block.x=256;
grid.x=(nElem+block.x-1)/block.x;
printf("grid.x %d block.x %d \n",grid.x,block.x);
block.x=128;
grid.x=(nElem+block.x-1)/block.x;
printf("grid.x %d block.x %d \n",grid.x,block.x);
cudaDeviceReset();
return 0;
}
|
9,734 | #include <cuda.h>
#include <iostream>
int main() {
float **Tab2D;
int X=5,Y=10;
Tab2D=new float*[X];
for(int i=0;i<X;i++) {
Tab2D[i]=new float[Y];
}
//intialize with some random values
for(int i=0;i<X;i++) {
for(int j=0;j<Y;j++) {
Tab2D[i][j]=(float)(rand()%10);
}
}
//print
for(int i=0;i<X;i++) {
std::cout<<"\n";
for(int j=0;j<Y;j++) {
std::cout << Tab2D[i][j] << ' ';
}
}
std::cout << std::endl;
//free memory
for(int i=0;i<X;i++)
delete[] Tab2D[i];
delete[] Tab2D;
return 0;
}
|
9,735 | //fail
//--blockDim=64 --gridDim=64 --no-inline
#include "cuda.h"
#include <stdio.h>
#define N 1
__device__ void bar (int *p){
int a = 0;
p = &a;
}
__global__ void foo (int* p, int* q){
if (*p > 10){
bar(p);
//*p = 23; // remove this comment to see that the __device__ function does not work
}
else {
bar(q);
//*q = 23; // remove this comment to see that the __device__ function does not work
}
}
|
9,736 | #include<bits/stdc++.h>
using namespace std;
#define pi (2.0*acos(0.0))
#define eps 1e-6
#define ll long long
#define inf (1<<29)
#define vi vector<int>
#define vll vector<ll>
#define sc(x) scanf("%d",&x)
#define scl(x) scanf("%lld",&x)
#define all(v) v.begin() , v.end()
#define me(a,val) memset( a , val ,sizeof(a) )
#define pb(x) push_back(x)
#define pii pair<int,int>
#define mp(a,b) make_pair(a,b)
#define Q(x) (x) * (x)
#define L(x) ((x<<1) + 1)
#define R(x) ((x<<1) + 2)
#define M(x,y) ((x+y)>>1)
#define fi first
#define se second
#define MOD 1000000007
#define ios ios::sync_with_stdio(0)
#define N 1024
#define TB 32
/*__global__ void suma(int *A, int *S){
S[0] = S[0] + A[threadIdx.x];
printf("A[t]: %d S[0]: %d\n",A[threadIdx.x], S[0]);
__syncthreads();
}*/
__global__ void MatrixMultiplication(int *A,int *B,int *C){
int row = threadIdx.y + blockIdx.y * blockDim.y;
int col = threadIdx.x + blockIdx.x * blockDim.x;;
C[ row * N + col ] = A[ row * N + col ] * B[ row * N + col ];
}
int main(){
clock_t tStart = clock();
int *a , *b , *c;
size_t size = N * N * sizeof(int) ;
a = (int *)malloc( size );
b = (int *)malloc( size );
c = (int *)malloc( size );
for(int i = 0; i < N; i++)
for(int j = 0; j < N; j++)
a[i * N + j] = i + j;
for(int i = 0; i < N; i++)
for(int j = 0; j < N; j++)
b[i * N + j] = 0;
int *A , *B , *C;
cudaMalloc( &A , size );
cudaMalloc( &B , size );
cudaMalloc( &C , size );
dim3 threadsxblock( TB , TB );
dim3 blocksxgrid( N / threadsxblock.x , N / threadsxblock.x );
cudaMemcpy( A , a , size , cudaMemcpyHostToDevice );
cudaMemcpy( B , b , size , cudaMemcpyHostToDevice );
MatrixMultiplication<<< blocksxgrid , threadsxblock >>>( A , B , C );
cudaMemcpy( c , C , size , cudaMemcpyDeviceToHost );
cudaFree(A);
cudaFree(B);
cudaFree(C);
printf("Time taken: %.2fms\n", 1000.0 * (double)(clock() - tStart)/CLOCKS_PER_SEC);
return 0;
}
|
9,737 | #include <stdio.h>
#define BLOCK_SIZE 16
#define DIM 4096
__global__ void calcula_max(double * max)
{
int x = blockIdx.x*blockDim.x + threadIdx.x;
if(x<DIM)
{
max[x]=x;
}
}
int main()
{
int i;
dim3 dimBlock(BLOCK_SIZE,BLOCK_SIZE);
double * g;
double * h;
cudaMalloc((void**)&g,DIM*sizeof(double));
h=(double *)malloc(DIM*sizeof(double));
calcula_max<<<(DIM+BLOCK_SIZE-1)/dimBlock.x,BLOCK_SIZE>>>(g);
cudaMemcpy(h,g,DIM*sizeof(double),cudaMemcpyDeviceToHost);
for(i=0;i<DIM;i++)
printf("%d %f\n",i,h[i]);
cudaFree(g);
free(h);
}
|
9,738 | #include <stdio.h>
#include <sys/time.h>
#include <stdlib.h>
#include <math.h>
#include <cuda_runtime.h>
__global__ void matrixAdd2D(const float *A, const float *B, float *C, int nx,
int ny) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int idx = nx * j + i;
if (i < nx && j < ny) {
C[idx] = A[idx] + B[idx];
}
}
__global__ void matrixAdd1D(const float *A, const float *B, float *C, int n) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
if (idx < n) {
C[idx] = A[idx] + B[idx];
}
}
__global__ void hdamard_2D(const float *A, const float *B, float *C, int nx, int ny) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int idx = nx * j + i;
if (i < nx && j < ny) {
C[idx] = A[idx] * B[idx];
}
}
__global__ void dyadic_2D(const float *A, const float *B, float *C, int n) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int idx = n * j + i;
if (i < n && j < n) {
C[idx] = A[i] * B[j];
}
}
__global__ void dyadic_1D(const float *A, const float *B, float *C, int n) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < n)
for(int j = 0; j< n; j++ ){
C[n * j + i] = A[i] * B[j];
}
}
__global__ void matrixAdd2D(const int *A, const int *B, int *C, int nx,
int ny) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int idx = nx * j + i;
if (i < nx && j < ny) {
C[idx] = A[idx] + B[idx];
}
}
__global__ void matrixAdd1D(const int *A, const int *B, int *C, int n) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
if (idx < n) {
C[idx] = A[idx] + B[idx];
}
}
void add_verification(float* A, float* B, float* C, int number_of_elements){
for (int i = 0; i < number_of_elements; ++i) {
if (fabs(A[i] + B[i] - C[i]) > 1e-5) {
fprintf(stderr, "Result verification failed at element %d!\n", i);
exit(EXIT_FAILURE);
}
}
}
__global__ void hdamard_2D(const int *A, const int *B, int *C, int nx, int ny) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int idx = nx * j + i;
if (i < nx && j < ny) {
C[idx] = A[idx] * B[idx];
}
}
void hdamard_verification(float* A, float* B, float* C, int number_of_elements){
for (int i = 0; i < number_of_elements; ++i) {
if (fabs(A[i] * B[i] - C[i]) > 1e-5) {
fprintf(stderr, "Result verification failed at element %d!\n", i);
exit(EXIT_FAILURE);
}
}
}
__global__ void dyadic_2D(const int *A, const int *B, int *C, int n) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int idx = n * j + i;
if (i < n && j < n) {
C[idx] = A[i] * B[j];
}
}
__global__ void dyadic_1D(const int *A, const int *B, int *C, int n) {
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < n)
for(int j = 0; j< n; j++ ){
C[n * j + i] = A[i] * B[j];
}
}
void dyadic_verification(float* A, float* B, float* C, int number_of_elements){
for (int i = 0; i < number_of_elements; ++i) {
for (int j = 0; j < number_of_elements; ++j) {
if (fabs(A[i] * B[j] - C[number_of_elements * j + i]) > 1e-5) {
fprintf(stderr, "Result verification failed at element %d!\n", i);
exit(EXIT_FAILURE);
}
}
}
}
float timedifference_msec(struct timeval t0, struct timeval t1) {
return (t1.tv_sec - t0.tv_sec) * 1000.0f
+ (t1.tv_usec - t0.tv_usec) / 1000.0f;
}
void prepare_host(float* A, float* B, float* C, int number_of_elements){
size_t size = number_of_elements * sizeof(float);
A = (float *) malloc(size);
B = (float *) malloc(size);
C = (float *) malloc(size);
for(int i = 0; i < number_of_elements; i++){
A[i] = rand() / (float) RAND_MAX;
B[i] = rand() / (float) RAND_MAX;
}
}
void prepare_device(float* A, float* B, float* C, int number_of_elements){
}
void hadamard_verification(float* A, float* B, float* C, int number_of_elements){
for (int i = 0; i < number_of_elements; ++i) {
if (fabs(A[i] * B[i] - C[i]) > 1e-5) {
fprintf(stderr, "Result verification failed at element %d!\n", i);
exit(EXIT_FAILURE);
}
}
}
void free_host(float* A, float* B, float* C){
free(A);
free(B);
free(C);
}
/**
* Host main routine
*/
int main(void) {
cudaError_t err = cudaSuccess;
// Print the vector length to be used, and compute its size
int numElementsInDim = 10;
clock_t start_t, end_t, total_t;
struct timeval t0;
struct timeval t1;
float elapsed;
//We are using this loop to check how long vectors we can process
for (int out = 0; out < 4; out++) {
char bigEnough[64] = "";
sprintf(bigEnough, "%d", numElementsInDim*numElementsInDim);
//strcat(bigEnough, numElementsInDim);
strcat(bigEnough, ".txt");
FILE* execution_time;
execution_time = fopen(bigEnough, "w");
size_t size = numElementsInDim * numElementsInDim * sizeof(float);
printf("[Matrix addition of %d elements]\n",
numElementsInDim * numElementsInDim);
fprintf(execution_time, "Time for add vectors of %d elements:\n",
numElementsInDim * numElementsInDim);
// Allocate the host operating vectors
float *h_A = (float *) malloc(size);
float *h_B = (float *) malloc(size);
float *h_C = (float *) malloc(size);
// Verify that allocations succeeded
if (h_A == NULL || h_B == NULL || h_C == NULL) {
fprintf(stderr, "Failed to allocate host vectors!\n");
exit(EXIT_FAILURE);
}
// Initialize the host input vectors
for (int i = 0; i < numElementsInDim * numElementsInDim; ++i) {
h_A[i] = rand() / (float) RAND_MAX;
h_B[i] = rand() / (float) RAND_MAX;
}
// Allocate the device input vectors A and B
float *d_A = NULL;
err = cudaMalloc((void **) &d_A, size);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to allocate device vector A (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
float *d_B = NULL;
err = cudaMalloc((void **) &d_B, size);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to allocate device vector B (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// Allocate the device output vector C
float *d_C = NULL;
err = cudaMalloc((void **) &d_C, size);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to allocate device vector C (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// Copy the host input vectors A and B in host memory to the device input vectors in
// device memory
printf("Copy input data from the host memory to the CUDA device\n");
err = cudaMemcpy(d_A, h_A, size, cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to copy vector A from host to device (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaMemcpy(d_B, h_B, size, cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to copy vector B from host to device (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
//loop for time measuring:
for (int in = 0; in < 10; in++) {
// Launch the Vector Add CUDA Kernel
int threadsPerBlock = 16;
int blocksPerGrid = (numElementsInDim + threadsPerBlock - 1)
/ threadsPerBlock;
printf("CUDA kernel launch with %d blocks of %d threads\n",
blocksPerGrid, threadsPerBlock);
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
dim3 dimBlock(16, 16);
dim3 dimGrid(blocksPerGrid, blocksPerGrid);
float milliseconds;
cudaEventRecord(start);
matrixAdd2D<<<dimGrid, dimBlock>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
add_verification(h_A,h_B,h_C,numElementsInDim*numElementsInDim);
dim3 dimBlock1(256, 1);
dim3 dimGrid1(blocksPerGrid*blocksPerGrid, 1);
cudaEventRecord(start);
matrixAdd2D<<<dimGrid1, dimBlock1>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
add_verification(h_A,h_B,h_C,numElementsInDim*numElementsInDim);
dim3 dimBlock3(16, 16);
dim3 dimGrid3(blocksPerGrid, blocksPerGrid);
cudaEventRecord(start);
hdamard_2D<<<dimGrid3, dimBlock3>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
hdamard_verification(h_A,h_B,h_C,numElementsInDim*numElementsInDim);
dim3 dimBlock2(256, 1);
dim3 dimGrid2(blocksPerGrid*blocksPerGrid, 1);
cudaEventRecord(start);
hdamard_2D<<<dimGrid2, dimBlock2>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
hdamard_verification(h_A,h_B,h_C,numElementsInDim*numElementsInDim);
dim3 dimBlock4(16, 16);
dim3 dimGrid4(blocksPerGrid, blocksPerGrid);
cudaEventRecord(start);
dyadic_2D<<<dimGrid4, dimBlock4>>>(d_A, d_B, d_C, numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
dyadic_verification(h_A,h_B,h_C,numElementsInDim);
dim3 dimBlock5(256, 1);
dim3 dimGrid5(blocksPerGrid*blocksPerGrid, 1);
cudaEventRecord(start);
dyadic_1D<<<dimGrid5, dimBlock5>>>(d_A, d_B, d_C, numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\n", milliseconds);
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
dyadic_verification(h_A,h_B,h_C,numElementsInDim);
err = cudaGetLastError();
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to launch vectorAdd kernel (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
}
// Copy the device result vector in device memory to the host result vector
// in host memory.
printf("Copy output data from the CUDA device to the host memory\n");
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to copy vector C from device to host (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// // Verify that the result vector is correct
// for (int i = 0; i < numElementsInDim * numElementsInDim; ++i) {
// if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5) {
// fprintf(stderr, "Result verification failed at element %d!\n",
// i);
// exit(EXIT_FAILURE);
// }
// }
//
// printf("Test PASSED\n");
// Free device global memory
err = cudaFree(d_A);
if (err != cudaSuccess) {
fprintf(stderr, "Failed to free device vector A (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaFree(d_B);
if (err != cudaSuccess) {
fprintf(stderr, "Failed to free device vector B (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaFree(d_C);
if (err != cudaSuccess) {
fprintf(stderr, "Failed to free device vector C (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// Free host memory
free(h_A);
free(h_B);
free(h_C);
fprintf(execution_time, "\n\n\n");
numElementsInDim = numElementsInDim * 10;
fclose(execution_time);
}
numElementsInDim= 10;
for (int out = 0; out < 4; out++) {
char bigEnough[64] = "";
sprintf(bigEnough, "%d", numElementsInDim*numElementsInDim);
//strcat(bigEnough, numElementsInDim);
strcat(bigEnough, "int.txt");
FILE* execution_time;
execution_time = fopen(bigEnough, "w");
size_t size = numElementsInDim * numElementsInDim * sizeof(int);
printf("[Matrix addition of %d elements]\n",
numElementsInDim * numElementsInDim);
fprintf(execution_time, "Time for add vectors of %d elements:\n",
numElementsInDim * numElementsInDim);
// Allocate the host operating vectors
int *h_A = (int *) malloc(size);
int *h_B = (int *) malloc(size);
int *h_C = (int *) malloc(size);
// Verify that allocations succeeded
if (h_A == NULL || h_B == NULL || h_C == NULL) {
fprintf(stderr, "Failed to allocate host vectors!\n");
exit(EXIT_FAILURE);
}
// Initialize the host input vectors
for (int i = 0; i < numElementsInDim * numElementsInDim; ++i) {
h_A[i] = rand() / (int) RAND_MAX;
h_B[i] = rand() / (int) RAND_MAX;
}
// Allocate the device input vectors A and B
int *d_A = NULL;
err = cudaMalloc((void **) &d_A, size);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to allocate device vector A (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
int *d_B = NULL;
err = cudaMalloc((void **) &d_B, size);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to allocate device vector B (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// Allocate the device output vector C
int *d_C = NULL;
err = cudaMalloc((void **) &d_C, size);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to allocate device vector C (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// Copy the host input vectors A and B in host memory to the device input vectors in
// device memory
printf("Copy input data from the host memory to the CUDA device\n");
err = cudaMemcpy(d_A, h_A, size, cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to copy vector A from host to device (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaMemcpy(d_B, h_B, size, cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to copy vector B from host to device (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
//loop for time measuring:
for (int in = 0; in < 10; in++) {
// Launch the Vector Add CUDA Kernel
int threadsPerBlock = 16;
int blocksPerGrid = (numElementsInDim + threadsPerBlock - 1)
/ threadsPerBlock;
printf("CUDA kernel launch with %d blocks of %d threads\n",
blocksPerGrid, threadsPerBlock);
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
dim3 dimBlock(16, 16);
dim3 dimGrid(blocksPerGrid, blocksPerGrid);
float milliseconds;
cudaEventRecord(start);
matrixAdd2D<<<dimGrid, dimBlock>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
dim3 dimBlock1(256, 1);
dim3 dimGrid1(blocksPerGrid*blocksPerGrid, 1);
cudaEventRecord(start);
matrixAdd2D<<<dimGrid1, dimBlock1>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
dim3 dimBlock3(16, 16);
dim3 dimGrid3(blocksPerGrid, blocksPerGrid);
cudaEventRecord(start);
hdamard_2D<<<dimGrid3, dimBlock3>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
dim3 dimBlock2(256, 1);
dim3 dimGrid2(blocksPerGrid*blocksPerGrid, 1);
cudaEventRecord(start);
hdamard_2D<<<dimGrid2, dimBlock2>>>(d_A, d_B, d_C, numElementsInDim,
numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
dim3 dimBlock4(16, 16);
dim3 dimGrid4(blocksPerGrid, blocksPerGrid);
cudaEventRecord(start);
dyadic_2D<<<dimGrid4, dimBlock4>>>(d_A, d_B, d_C, numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\t", milliseconds);
dim3 dimBlock5(256, 1);
dim3 dimGrid5(blocksPerGrid*blocksPerGrid, 1);
cudaEventRecord(start);
dyadic_1D<<<dimGrid5, dimBlock5>>>(d_A, d_B, d_C, numElementsInDim);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&milliseconds, start, stop);
fprintf(execution_time, "%f\n", milliseconds);
err = cudaGetLastError();
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to launch vectorAdd kernel (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
}
// Copy the device result vector in device memory to the host result vector
// in host memory.
printf("Copy output data from the CUDA device to the host memory\n");
err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);
if (err != cudaSuccess) {
fprintf(stderr,
"Failed to copy vector C from device to host (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// // Verify that the result vector is correct
// for (int i = 0; i < numElementsInDim * numElementsInDim; ++i) {
// if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5) {
// fprintf(stderr, "Result verification failed at element %d!\n",
// i);
// exit(EXIT_FAILURE);
// }
// }
//
// printf("Test PASSED\n");
// Free device global memory
err = cudaFree(d_A);
if (err != cudaSuccess) {
fprintf(stderr, "Failed to free device vector A (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaFree(d_B);
if (err != cudaSuccess) {
fprintf(stderr, "Failed to free device vector B (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaFree(d_C);
if (err != cudaSuccess) {
fprintf(stderr, "Failed to free device vector C (error code %s)!\n",
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
// Free host memory
free(h_A);
free(h_B);
free(h_C);
fprintf(execution_time, "\n\n\n");
numElementsInDim = numElementsInDim * 10;
fclose(execution_time);
}
printf("Done\n");
return 0;
}
|
9,739 | #include <stdio.h>
#include <string>
#include <iostream>
#include <fstream>
#include <sstream>
#include <cmath>
#include <time.h>
#include <sys/time.h>
#include <stdlib.h>
#include <vector>
#include <queue>
#include <limits.h>
#include "cuda.h"
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
using namespace std;
#define FW_MAX 50000
#define BLOCK_SIZE 16
int nodes; //number of nodes
int* matrix; //Input matrix
int* FWDistanceMatrix; // Distance matrix for Floyd-Warshall
int* FWPathMatrix; // Path Matrix for Floyd-Warshall
//measuring function
double get_wall_time() {
struct timeval time;
if (gettimeofday(&time, NULL)) {
// Handle error
return 0;
}
return (double)time.tv_sec + (double)time.tv_usec * .000001;
}
double get_cpu_time() {
return (double)clock() / CLOCKS_PER_SEC;
}
void TESTPrintMatrix() {
for (int i = 0; i < nodes; i++) {
for (int j = 0; j < nodes; j++) {
cout << FWDistanceMatrix[i * nodes + j] << " ";
}
cout << endl;
}
}
__global__ void GPU_FloydWarshall(int i, int * deviceDistanceMatrix, int * devicePathMatrix, int nodes) {
int idy = blockDim.y * blockIdx.y + threadIdx.y;
int idx = blockDim.x * blockIdx.x + threadIdx.x;
if (idy < nodes && idx < nodes)
{
int actuatPosition = idy * nodes + idx;
int newDistance = deviceDistanceMatrix[idy * nodes + i] + deviceDistanceMatrix[nodes * i + idx];
int oldDistance = deviceDistanceMatrix[actuatPosition];
if (newDistance < oldDistance)
{
deviceDistanceMatrix[actuatPosition] = newDistance;
devicePathMatrix[actuatPosition] = devicePathMatrix[i * nodes + idx];
}
}
}
void FloydWarshall() {
int *deviceDistanceMatrix;
int *devicePathMatrix;
cudaError_t err;
err = cudaSetDevice(0);
if (err != cudaSuccess) cout << "CHYBA!" << endl;
err = cudaMalloc((int**)&deviceDistanceMatrix, nodes * nodes * sizeof(int));
if (err != cudaSuccess) cout << "chyba" << endl;
err = cudaMalloc((int**)&devicePathMatrix, nodes * nodes * sizeof(int));
if (err != cudaSuccess) cout << "chyba" << endl;
err = cudaMemcpy(deviceDistanceMatrix, FWDistanceMatrix, nodes * nodes * sizeof(int), cudaMemcpyHostToDevice);
if (err != cudaSuccess) cout << "chyba" << endl;
err = cudaMemcpy(devicePathMatrix, FWPathMatrix, nodes * nodes * sizeof(int), cudaMemcpyHostToDevice);
if (err != cudaSuccess) cout << "chyba" << endl;
dim3 dimGrid((nodes - 1) / BLOCK_SIZE + 1, (nodes - 1) / BLOCK_SIZE + 1, 1);
dim3 dimBlock(BLOCK_SIZE, BLOCK_SIZE, 1);
for ( int i = 0; i < nodes; i++)
{
GPU_FloydWarshall <<< dimGrid, dimBlock>>>(i, deviceDistanceMatrix, devicePathMatrix, nodes);
err = cudaThreadSynchronize();
if (err != cudaSuccess) cout << "Error" << endl;
}
cudaMemcpy(FWDistanceMatrix, deviceDistanceMatrix, nodes * nodes * sizeof(int), cudaMemcpyDeviceToHost);
cudaMemcpy(FWPathMatrix, devicePathMatrix, nodes * nodes * sizeof(int), cudaMemcpyDeviceToHost);
cudaFree(devicePathMatrix);
cudaFree(deviceDistanceMatrix);
}
bool loadMatrix(const char * matrixPath) {
string line;
ifstream inFile (matrixPath);
if (!inFile.is_open()) {
cout << "Wrong path to file" << endl;
return false;
}
getline(inFile, line);
nodes = atoi(line.c_str());
FWDistanceMatrix = new int [nodes * nodes];
FWPathMatrix = new int [nodes * nodes];
for (int j = 0; j < nodes; j++)
{
getline(inFile, line);
istringstream is(line);
for (int i = 0; i < nodes; i++)
{
is >> FWDistanceMatrix[j * nodes + i];
if (i != j && FWDistanceMatrix[j * nodes + i] == 0)
FWDistanceMatrix[j * nodes + i] = FW_MAX;
}
}
//initialize predecessors
for ( int i = 0; i < nodes; i++)
for ( int j = 0; j < nodes; j++)
FWPathMatrix[i * nodes + j] = ( FWDistanceMatrix[i * nodes + j] == FW_MAX ? -1 : i);
return true;
}
int main( int argc, const char* argv[] )
{
if ( argc != 2 ) {
cout << "Bad Input.. 1st parameter: Path to file." << endl;
return 1;
}
loadMatrix(argv[1]);
//start of measuring
double wall0 = get_wall_time();
double cpu0 = get_cpu_time();
// Initialize CUDA Event
cudaEvent_t start, stop;
float elapsedTime;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start, 0);
FloydWarshall();
// Finish recording
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
// Calculate elasped time
cudaEventElapsedTime(&elapsedTime, start, stop);
elapsedTime /= 1000;
printf ("Timee : %f s\n", elapsedTime);
//end of measuring
double wall1 = get_wall_time();
double cpu1 = get_cpu_time();
//TESTPrintMatrix();
//prints results
/* for (int i = 0; i < ncg.getNodes(); i++) {
ncg.FWShortestPathFrom(i);
}*/
cout << "Wall Time = " << wall1 - wall0 << endl;
cout << "CPU Time = " << cpu1 - cpu0 << endl;
return 0;
}
|
9,740 | #include <cstdio>
#include <cstdlib>
#include <cmath>
#include <cuda_runtime_api.h>
#define BASE_TYPE float
#define INT_TYPE unsigned int
__global__ void monteKarlo(const BASE_TYPE h, INT_TYPE *result)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
int j = blockIdx.y * blockDim.y + threadIdx.y;
BASE_TYPE x = h * i;
BASE_TYPE y = h * j;
BASE_TYPE r = sqrtf(x * x + y * y);
if (r < 100.0)
atomicAdd(result, (INT_TYPE)1);
}
void cuda_init_array(INT_TYPE **dev, const INT_TYPE *host, const size_t size)
{
cudaError_t err;
err = cudaMalloc((void **)dev, size);
if (err != cudaSuccess)
throw err;
if (host != NULL)
{
err = cudaMemcpy(*dev, host, size, cudaMemcpyHostToDevice);
if (err != cudaSuccess)
throw err;
}
}
void init_grid_and_block(dim3 *grid, dim3 *block, const int block_size, const int N)
{
*grid = dim3(N / block_size, N / block_size, 1);
*block = dim3(block_size, block_size, 1);
printf("Block (%d, %d, %d)\n", block->x, block->y, block->z);
printf("Grid (%d, %d, %d)\n", grid->x, grid->y, grid->z);
}
int main()
{
const int N = 1024;
const int block_size = 16;
dim3 blockDim, gridDim;
init_grid_and_block(&blockDim, &gridDim, block_size, N);
BASE_TYPE h = 100.0 / N;
printf("%f\n", h);
INT_TYPE result = 0;
INT_TYPE *dev_result;
try
{
cuda_init_array(&dev_result, &result, sizeof(INT_TYPE));
}
catch (cudaError_t err)
{
fprintf(stderr, "Failed to allocate device (error code: %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
monteKarlo<<<blockDim, gridDim>>>(h, dev_result);
cudaMemcpy(&result, dev_result, sizeof(INT_TYPE), cudaMemcpyDeviceToHost);
printf("%f\n", (double) 4 * result / (N * N));
cudaFree(dev_result);
return 0;
} |
9,741 | #include <iostream>
#include <limits>
#include <cuda.h>
#include <curand_kernel.h>
using std::cout;
using std::endl;
typedef unsigned long long Count;
typedef std::numeric_limits<double> DblLim;
const Count WARP_SIZE = 32; // Warp size
const Count NBLOCKS = 640; // Number of total cuda cores on my GPU
const Count ITERATIONS = 1000000; // Number of points to generate (each thread)
// This kernel is
__global__ void picount(Count *totals) {
// Define some shared memory: all threads in this block
__shared__ Count counter[WARP_SIZE];
// Unique ID of the thread
int tid = threadIdx.x + blockIdx.x * blockDim.x;
// Initialize RNG
curandState_t rng;
curand_init(clock64(), tid, 0, &rng);
// Initialize the counter
counter[threadIdx.x] = 0;
// Computation loop
for (int i = 0; i < ITERATIONS; i++) {
float x = curand_uniform(&rng); // Random x position in [0,1]
float y = curand_uniform(&rng); // Random y position in [0,1]
counter[threadIdx.x] += 1 - int(x * x + y * y); // Hit test
}
// The first thread in *every block* should sum the results
if (threadIdx.x == 0) {
// Reset count for this block
totals[blockIdx.x] = 0;
// Accumulate results
for (int i = 0; i < WARP_SIZE; i++) {
totals[blockIdx.x] += counter[i];
}
}
}
int main(int argc, char **argv) {
int numDev;
cudaGetDeviceCount(&numDev);
if (numDev < 1) {
cout << "CUDA device missing! Do you need to use optirun?\n";
return 1;
}
cout << "Starting simulation with " << NBLOCKS << " blocks, " << WARP_SIZE << " threads, and " << ITERATIONS << " iterations\n";
// Allocate host and device memory to store the counters
Count *hOut, *dOut;
hOut = new Count[NBLOCKS]; // Host memory
cudaMalloc(&dOut, sizeof(Count) * NBLOCKS); // Device memory
// Launch kernel
picount<<<NBLOCKS, WARP_SIZE>>>(dOut);
// Copy back memory used on device and free
cudaMemcpy(hOut, dOut, sizeof(Count) * NBLOCKS, cudaMemcpyDeviceToHost);
cudaFree(dOut);
// Compute total hits
Count total = 0;
for (int i = 0; i < NBLOCKS; i++) {
total += hOut[i];
}
Count tests = NBLOCKS * ITERATIONS * WARP_SIZE;
cout << "Approximated PI using " << tests << " random tests\n";
// Set maximum precision for decimal printing
cout.precision(DblLim::max_digits10);
cout << "PI ~= " << 4.0 * (double)total/(double)tests << endl;
return 0;
}
|
9,742 | #include "includes.h"
__global__ void set_with_value_util_kernel( int4 * __restrict buf, int v, int elem_count)
{
int elem_id = blockDim.x * blockIdx.x + threadIdx.x;
if (elem_id < elem_count)
{
int4 val;
val.x = v;
val.y = v;
val.z = v;
val.w = v;
buf[elem_id] = val;
}
} |
9,743 | // Implement CudaChain convex hull algorithm on the GPU
// Original:
// Gang Mei, Institute of Earth and Enviromental Sciences
// University of Freiburg, April 8, 2014
// gang.mei@geologie.uni-freiburg.de
// gangmeiphd@gmail.com
// Revised:
// Gang Mei, School of Engineeing and Technology,
// China University of Geosciences, December 27, 2015
// gang.mei@cugb.edu.cn
// gangmeiphd@gmail.com
// Warning: Ignore numerical non-robustness and geometrical degeneracies
#include <iostream>
#include <cstdlib>
#include <fstream>
#include <string>
#include <ctime>
#include "CudaChain.cuh"
namespace CudaChain {
/////////////// Input & Output Interface ////////////////
// Input: Use the QHull input forrmat, i.e.,
/* Dimension Number of points
// Corrdinates of Point 1
// Coordinates of Point 2
... */
void importQHull(thrust::host_vector<float> &pts_x,
thrust::host_vector<float> &pts_y,
std::string &path) {
char str1[20];
// cout <<"\nPlease Input File Name of Point Set: ";
// cin >>str1;
ifstream fin(path.c_str());
if (!fin) {
cout << "\nCannot Open File ! " << str1 << endl;
exit(1);
}
float x, y;
int Dim, nVertex;
fin >> Dim >> nVertex;
pts_x.resize(nVertex);
pts_y.resize(nVertex);
for (int i = 0; i < nVertex; i++) {
fin >> x >> y;
pts_x[i] = x;
pts_y[i] = y;
}
fin.close();
}
// Export the resulting convex hull to OFF file
void exportOFF(CudaChainPoint *pts, int n) // Use C/C++ arrays for exporting
{
char str2[20];
cout << "\nPlease Input File Name of Convex Hull: ";
cin >> str2;
ofstream fout(str2);
if (!fout) {
cout << "\nCannot Save File ! " << str2 << endl;
exit(1);
}
float x, y, z;
int nVert = n;
fout << "OFF" << endl;
fout << nVert << " " << 1 << " " << 0 << endl;
for (int i = 0; i < nVert; i++) {
x = pts[i].x;
y = pts[i].y;
z = 0.0;
fout << x << " " << y << " " << z << endl;
}
fout << nVert << " ";
for (int i = 0; i < nVert; i++) {
fout << i << " ";
}
fout.close();
}
void printOFF(CudaChainPoint *pts, int n) // Use C/C++ arrays for exporting
{
float x, y, z;
int nVert = n;
cout << "OFF" << endl;
cout << nVert << " " << 1 << " " << 0 << endl;
for (int i = 0; i < nVert; i++) {
x = pts[i].x;
y = pts[i].y;
z = 0.0;
cout << x << " " << y << " " << z << endl;
}
cout << nVert << " ";
for (int i = 0; i < nVert; i++) {
cout << i << " ";
}
}
// Export the resulting convex hull to OFF file
void exportOFF(CudaChainPoint **pts, int n) // Use C/C++ arrays for exporting
{
char str2[20];
cout << "\nPlease Input File Name of Convex Hull: ";
cin >> str2;
ofstream fout(str2);
if (!fout) {
cout << "\nCannot Save File ! " << str2 << endl;
exit(1);
}
double x, y, z;
int ids[3];
int nVert = n;
fout << "OFF" << endl;
fout << nVert << " " << 1 << " " << 0 << endl;
for (int i = 0; i < nVert; i++) {
x = pts[i]->x;
y = pts[i]->y;
z = 0.0;
fout << x << " " << y << " " << z << endl;
}
fout << nVert << " ";
for (int i = 0; i < nVert; i++) {
fout << i << " ";
}
fout.close();
}
// Export the resulting convex hull to OFF file
void exportOFF(const thrust::host_vector<float> &pts_x,
const thrust::host_vector<float> &pts_y, int n) // Use thrust containers for exporting
{
char str2[20];
cout << "\nPlease Input File Name of Convex Hull: ";
cin >> str2;
ofstream fout(str2);
if (!fout) {
cout << "\nCannot Save File ! " << str2 << endl;
exit(1);
}
float x, y, z;
int nVert = n;
fout << "OFF" << endl;
fout << nVert << " " << 1 << " " << 0 << endl;
for (int i = 0; i < nVert; i++) {
x = pts_x[i];
y = pts_y[i];
z = 0.0;
fout << x << " " << y << " " << z << endl;
}
fout << nVert << " ";
for (int i = 0; i < nVert; i++) {
fout << i << " ";
}
fout.close();
}
/////////////////////////////////////////////////////////
// isLeft():tests if a point is Left|On|Right of an infinite line.
// Input: three points P0, P1, and P2
// Return:
// >0 for P2 left of the line through P0 and P1
// =0 for P2 on the line
// <0 for P2 right of the line
// See: Algorithm 1 on Area of Triangles
__host__ __device__
inline float isLeft(CudaChainPoint *P0, CudaChainPoint *P1, CudaChainPoint *P2) {
return (P1->x - P0->x) * (P2->y - P0->y) - (P2->x - P0->x) * (P1->y - P0->y);
}
__host__ __device__
inline float isLeft(CudaChainPoint *P0, CudaChainPoint *P1, float &P2_x, float &P2_y) {
return (P1->x - P0->x) * (P2_y - P0->y) - (P2_x - P0->x) * (P1->y - P0->y);
}
// Check whether a point locates in a convex quadrilateral, for 1st discarding
__host__ __device__
int isInside(CudaChainPoint *P0, CudaChainPoint *P1, CudaChainPoint *P2, CudaChainPoint *P3, CudaChainPoint *pt) {
if (isLeft(P0, P1, pt) <= 0.0) return 1; // In the sub-region 1
if (isLeft(P1, P2, pt) <= 0.0) return 2; // In the sub-region 2
if (isLeft(P2, P3, pt) <= 0.0) return 3; // In the sub-region 3
if (isLeft(P3, P0, pt) <= 0.0) return 4; // In the sub-region 4
return 0; // In the sub-region 0
}
__host__ __device__
int
isInside(CudaChainPoint *P0, CudaChainPoint *P1, CudaChainPoint *P2, CudaChainPoint *P3, float &pt_x, float &pt_y) {
if (isLeft(P0, P1, pt_x, pt_y) <= 0.0) return 1;
if (isLeft(P1, P2, pt_x, pt_y) <= 0.0) return 2;
if (isLeft(P2, P3, pt_x, pt_y) <= 0.0) return 3;
if (isLeft(P3, P0, pt_x, pt_y) <= 0.0) return 4;
return 0;
}
// Preprocess by discarding interior points, i.e., 1st round of discarding
__global__
void kernelPreprocess(float *h_extreme_x, float *h_extreme_y,
float *v_x, float *v_y, int *pos, int n) {
__shared__ float2 s_extreme[4]; // Stored in shared memory
if (threadIdx.x == 0) {
for (int t = 0; t < 4; t++) {
s_extreme[t].x = h_extreme_x[t];
s_extreme[t].y = h_extreme_y[t];
}
}
__syncthreads();
int i = threadIdx.x + blockDim.x * blockIdx.x;
if (i < n) // Check
{
pos[i] = isInside(&s_extreme[0], &s_extreme[1],
&s_extreme[2], &s_extreme[3], v_x[i], v_y[i]);
}
}
// Make predicate easy to write
typedef thrust::tuple<float, float, int> FloatTuple3;
// Predicate
struct is_interior_tuple {
__host__ __device__
bool operator()(const FloatTuple3 &p) {
return thrust::get<2>(p) > 0;
}
};
struct is_region_1_tuple {
__host__ __device__
bool operator()(const FloatTuple3 &p) {
return thrust::get<2>(p) == 1;
}
};
struct is_region_2_tuple {
__host__ __device__
bool operator()(const FloatTuple3 &p) {
return thrust::get<2>(p) == 2;
}
};
struct is_region_3_tuple {
__host__ __device__
bool operator()(const FloatTuple3 &p) {
return thrust::get<2>(p) == 3;
}
};
struct is_region_4_tuple {
__host__ __device__
bool operator()(const FloatTuple3 &p) {
return thrust::get<2>(p) == 4;
}
};
// Discard invalid points in Region 1 (i.e., the lower left)
__global__
void kernelCheck_R1_device(float *V, int *pos, int base, int length) {
int i, id;
float temp;
int items = (length + BLOCK_SIZE - 1) / BLOCK_SIZE;
if (BLOCK_SIZE == 1024) {
temp = V[base];
for (int t = 0; t < items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] > temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 512) {
temp = V[base];
for (int t = 0; t < 2 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] > temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 256) {
temp = V[base];
for (int t = 0; t < 4 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] > temp) pos[id] = 0;
else temp = V[id];
}
}
}
}
// Discard invalid points in Region 2 (i.e., the lower right)
__global__
void kernelCheck_R2_device(float *V, int *pos, int base, int length) {
int i, id;
float temp;
int items = (length + BLOCK_SIZE - 1) / BLOCK_SIZE;
if (BLOCK_SIZE == 1024) {
temp = V[base];
for (int t = 0; t < items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] < temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 512) {
temp = V[base];
for (int t = 0; t < 2 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] < temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 256) {
temp = V[base];
for (int t = 0; t < 4 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] < temp) pos[id] = 0;
else temp = V[id];
}
}
}
}
// Discard invalid points in Region 3 (i.e., the upper right)
__global__
void kernelCheck_R3_device(float *V, int *pos, int base, int length) {
int i, id;
float temp;
int items = (length + BLOCK_SIZE - 1) / BLOCK_SIZE;
if (BLOCK_SIZE == 1024) {
temp = V[base];
for (int t = 0; t < items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] < temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 512) {
temp = V[base];
for (int t = 0; t < 2 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] < temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 256) {
temp = V[base];
for (int t = 0; t < 4 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] < temp) pos[id] = 0;
else temp = V[id];
}
}
}
}
// Discard invalid points in Region 4 (i.e., the upper left)
__global__
void kernelCheck_R4_device(float *V, int *pos, int base, int length) {
int i, id;
float temp = V[base];
int items = (length + BLOCK_SIZE - 1) / BLOCK_SIZE;
if (BLOCK_SIZE == 1024) {
temp = V[base];
for (int t = 0; t < items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] > temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 512) {
temp = V[base];
for (int t = 0; t < 2 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] > temp) pos[id] = 0;
else temp = V[id];
}
}
}
if (BLOCK_SIZE == 256) {
temp = V[base];
for (int t = 0; t < 4 * items; t++) {
i = threadIdx.x * items + t;
id = i + base;
if (i < length && pos[id] > 0) {
if (V[id] > temp) pos[id] = 0;
else temp = V[id];
}
}
}
}
// Wrapper: CudaChain
int cudaChainNew(const thrust::host_vector<float> &x, const thrust::host_vector<float> &y,
thrust::host_vector<float> &hull_x, thrust::host_vector<float> &hull_y) {
int n = x.size(); // Number of points
// Copy data from host side to device side
thrust::device_vector<float> d_x(x);
thrust::device_vector<float> d_y(y);
typedef thrust::device_vector<float>::iterator FloatIter;
// Find the four extreme points, i.e., min x, max x, min y, and max y
thrust::pair<FloatIter, FloatIter> extremex = thrust::minmax_element(d_x.begin(), d_x.end());
thrust::pair<FloatIter, FloatIter> extremey = thrust::minmax_element(d_y.begin(), d_y.end());
// One method to find min / max (Correct)
thrust::device_vector<float>::iterator minx = extremex.first;
thrust::device_vector<float>::iterator maxx = extremex.second;
thrust::device_vector<float>::iterator miny = extremey.first;
thrust::device_vector<float>::iterator maxy = extremey.second;
/* Another method to find min / max (Correct too)
thrust::device_vector<float>::iterator minx = thrust::min_element(d_x.begin(), d_x.end());
thrust::device_vector<float>::iterator maxx = thrust::max_element(d_x.begin(), d_x.end());
thrust::device_vector<float>::iterator miny = thrust::min_element(d_y.begin(), d_y.end());
thrust::device_vector<float>::iterator maxy = thrust::max_element(d_y.begin(), d_y.end());
*/
// Store the four extreme points temporarily
thrust::device_vector<float> d_extreme_x(4);
thrust::device_vector<float> d_extreme_y(4);
d_extreme_x[0] = *minx;
d_extreme_x[1] = d_x[miny - d_y.begin()];
d_extreme_x[2] = *maxx;
d_extreme_x[3] = d_x[maxy - d_y.begin()];
d_extreme_y[0] = d_y[minx - d_x.begin()];
d_extreme_y[1] = *miny;
d_extreme_y[2] = d_y[maxx - d_x.begin()];
d_extreme_y[3] = *maxy;
thrust::device_vector<int> d_pos(n); // Indicators for points' position
// Get the pointers to the arrays, to be used as launch arguments
float *d_extreme_x_ptr = thrust::raw_pointer_cast(&d_extreme_x[0]);
float *d_extreme_y_ptr = thrust::raw_pointer_cast(&d_extreme_y[0]);
float *d_x_ptr = thrust::raw_pointer_cast(&d_x[0]);
float *d_y_ptr = thrust::raw_pointer_cast(&d_y[0]);
int *d_pos_ptr = thrust::raw_pointer_cast(&d_pos[0]);
// 1st discarding : Block size can be 1024 in this kernel
kernelPreprocess <<< (n + 1023) / 1024, 1024 >>>(d_extreme_x_ptr, d_extreme_y_ptr,
d_x_ptr, d_y_ptr, d_pos_ptr, n);
// Set Extreme Points Specifically
d_pos[minx - d_x.begin()] = 1; // min X
d_pos[miny - d_y.begin()] = 2; // min Y
d_pos[maxx - d_x.begin()] = 3; // max X
d_pos[maxy - d_y.begin()] = 4; // max Y
// Defining a zip_iterator type can be a little cumbersome ...
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::device_vector<int>::iterator IntIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, IntIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
// create some zip_iterators
Float3Iterator P_first = thrust::make_zip_iterator(thrust::make_tuple(d_x.begin(), d_y.begin(), d_pos.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(thrust::make_tuple(d_x.end(), d_y.end(), d_pos.end()));
// pass the zip_iterators into Partion()
// Partion
Float3Iterator first_of_R0 = thrust::partition(P_first, P_last,
is_interior_tuple()); // Find Interior
Float3Iterator first_of_R2 = thrust::partition(P_first, first_of_R0 - 1,
is_region_1_tuple()); // Find Region 1
Float3Iterator first_of_R3 = thrust::partition(first_of_R2, first_of_R0 - 1,
is_region_2_tuple()); // Find Region 2
Float3Iterator first_of_R4 = thrust::partition(first_of_R3, first_of_R0 - 1,
is_region_3_tuple()); // Find Region 3
// CudaChainPoint * first_of_R4 = thrust::partition(first_of_R3, first_of_R0-1, is_region_4()); Not needed // Find Region 4
Float3Iterator first_of_R1 = P_first;
// Get the position of the first points in each sub-region
FloatIteratorTuple pos_R1 = first_of_R1.get_iterator_tuple();
FloatIteratorTuple pos_R2 = first_of_R2.get_iterator_tuple();
FloatIteratorTuple pos_R3 = first_of_R3.get_iterator_tuple();
FloatIteratorTuple pos_R4 = first_of_R4.get_iterator_tuple();
FloatIteratorTuple pos_R0 = first_of_R0.get_iterator_tuple();
// Partly Sort for each sub-regions
// Region 1 : ascending X
FloatIterator first_of_R1_x = thrust::get<0>(pos_R1);
FloatIterator first_of_R2_x = thrust::get<0>(pos_R2);
thrust::sort_by_key(first_of_R1_x, first_of_R2_x, first_of_R1);
// Region 2 : ascending Y
FloatIterator first_of_R2_y = thrust::get<1>(pos_R2);
FloatIterator first_of_R3_y = thrust::get<1>(pos_R3);
thrust::sort_by_key(first_of_R2_y, first_of_R3_y, first_of_R2);
// Region 3 : descending X
FloatIterator first_of_R3_x = thrust::get<0>(pos_R3);
FloatIterator first_of_R4_x = thrust::get<0>(pos_R4);
thrust::sort_by_key(first_of_R3_x, first_of_R4_x, first_of_R3);
// Sort in ascending order, and then reverse
thrust::reverse(thrust::get<0>(pos_R3), thrust::get<0>(pos_R4));
thrust::reverse(thrust::get<1>(pos_R3), thrust::get<1>(pos_R4));
thrust::reverse(thrust::get<2>(pos_R3), thrust::get<2>(pos_R4));
// Region 4 : descending Y
FloatIterator first_of_R4_y = thrust::get<1>(pos_R4);
FloatIterator first_of_R0_y = thrust::get<1>(pos_R0);
thrust::sort_by_key(first_of_R4_y, first_of_R0_y, first_of_R4);
// Sort in ascending order, and then reverse
thrust::reverse(thrust::get<0>(pos_R4), thrust::get<0>(pos_R0));
thrust::reverse(thrust::get<1>(pos_R4), thrust::get<1>(pos_R0));
thrust::reverse(thrust::get<2>(pos_R4), thrust::get<2>(pos_R0));
// Kernel : 2nd round of discarding
d_x_ptr = thrust::raw_pointer_cast(&d_x[0]);
d_y_ptr = thrust::raw_pointer_cast(&d_y[0]);
d_pos_ptr = thrust::raw_pointer_cast(&d_pos[0]);
int base, length;
// For each sub-region: Single Block and Single Pass
// Region 1
base = 0;
length = first_of_R2 - first_of_R1;
kernelCheck_R1_device <<< 1, BLOCK_SIZE >>>(d_y_ptr, d_pos_ptr, base, length); // Only Y
// Region 2
base = first_of_R2 - first_of_R1;
length = first_of_R3 - first_of_R2;
kernelCheck_R2_device <<< 1, BLOCK_SIZE >>>(d_x_ptr, d_pos_ptr, base, length); // Only X
// Region 3
base = first_of_R3 - first_of_R1;
length = first_of_R4 - first_of_R3;
kernelCheck_R3_device <<< 1, BLOCK_SIZE >>>(d_y_ptr, d_pos_ptr, base, length); // Only Y
// Region 4
base = first_of_R4 - first_of_R1;
length = first_of_R0 - first_of_R4;
kernelCheck_R4_device <<< 1, BLOCK_SIZE >>>(d_x_ptr, d_pos_ptr, base, length); // Only X
// Re-Partion, Note that: Use stable partition, rather than partition
Float3Iterator first_of_invalid = thrust::stable_partition(first_of_R1, first_of_R0, is_interior_tuple());
// Copy
n = first_of_invalid - first_of_R1;
thrust::copy_n(thrust::get<0>(pos_R1), n, hull_x.begin());
thrust::copy_n(thrust::get<1>(pos_R1), n, hull_y.begin());
return n;
}
// simpleHull_2D(): Melkman convex hull algorithm for simple polygon
// Input: V[] = polyline array of 2D vertex points (Note : CCW)
// n = the number of points in V[]
// Output: H[] = output convex hull array of vertices (max is n)
// Return: h = the number of points in H[]
__host__ __device__
int simpleHull_2D(CudaChainPoint *V, int n, CudaChainPoint *H) {
// initialize a deque D[] from bottom to top so that the
// 1st three vertices of V[] are a counterclockwise triangle
CudaChainPoint *D = new CudaChainPoint[2 * n + 1];
int bot = n - 2, top = bot + 3; // initial bottom and top deque indices
D[bot] = D[top] = V[2]; // 3rd vertex is at both bot and top
if (isLeft(&V[0], &V[1], &V[2]) > 0) {
D[bot + 1] = V[0];
D[bot + 2] = V[1]; // ccw vertices are: 2,0,1,2
} else {
D[bot + 1] = V[1];
D[bot + 2] = V[0]; // ccw vertices are: 2,1,0,2
}
// compute the hull on the deque D[]
for (int i = 3; i < n; i++) // process the rest of vertices
{
// test if next vertex is inside the deque hull
if ((isLeft(&D[bot], &D[bot + 1], &V[i]) > 0) &&
(isLeft(&D[top - 1], &D[top], &V[i]) > 0))
continue; // skip an interior vertex
// incrementally add an exterior vertex to the deque hull
// get the rightmost tangent at the deque bot
while (isLeft(&D[bot], &D[bot + 1], &V[i]) <= 0)
++bot; // remove bot of deque
D[--bot] = V[i]; // insert V[i] at bot of deque
// get the leftmost tangent at the deque top
while (isLeft(&D[top - 1], &D[top], &V[i]) <= 0)
--top; // pop top of deque
D[++top] = V[i]; // push V[i] onto top of deque
}
// transcribe deque D[] to the output hull array H[]
int h; // hull vertex counter
for (h = 0; h <= (top - bot); h++)
H[h] = D[bot + h];
delete D;
return h - 1;
}
}
////////////////////////////////////////////////////////////////////////////////
|
9,744 | #include "includes.h"
__global__ void dBinaryCrossEntropyCost(float* predictions, float* target, float* dY, int size) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < size) {
dY[index] = -1.0 * ( target[index]/predictions[index] - (1 - target[index])/(1 - predictions[index]) );
}
} |
9,745 | __global__ void multiply
(unsigned int *a, unsigned int *b, unsigned int *c, int n)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
int j = blockIdx.y * blockDim.y + threadIdx.y;
if (i < n && j < n) {
int idx = i * n + j;
c[idx] = a[idx] * b[idx];
}
}
|
9,746 | #include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <sys/time.h>
/* Problem size */
#define NI 5000
#define NJ 5000
#define THREADS_PER_BLOCK_Y 32
#define THREADS_PER_BLOCK_X 32
void Convolution(double* A, double* B)
{
int i, j;
double c11, c12, c13, c21, c22, c23, c31, c32, c33;
c11 = +0.2; c21 = +0.5; c31 = -0.8;
c12 = -0.3; c22 = +0.6; c32 = -0.9;
c13 = +0.4; c23 = +0.7; c33 = +0.10;
for (i = 1; i < NI - 1; ++i) {
for (j = 1; j < NJ - 1; ++j) {
B[i*NJ + j] = c11 * A[(i - 1)*NJ + (j - 1)] + c12 * A[(i + 0)*NJ + (j - 1)] + c13 * A[(i + 1)*NJ + (j - 1)]
+ c21 * A[(i - 1)*NJ + (j + 0)] + c22 * A[(i + 0)*NJ + (j + 0)] + c23 * A[(i + 1)*NJ + (j + 0)]
+ c31 * A[(i - 1)*NJ + (j + 1)] + c32 * A[(i + 0)*NJ + (j + 1)] + c33 * A[(i + 1)*NJ + (j + 1)];
}
}
}
__global__ void Convolution_kernel(double* A, double* B)
{
int j = threadIdx.x + blockDim.x * blockIdx.x+1;
int i = threadIdx.y + blockDim.y * blockIdx.y+1;
double c11, c12, c13, c21, c22, c23, c31, c32, c33;
c11 = +0.2; c21 = +0.5; c31 = -0.8;
c12 = -0.3; c22 = +0.6; c32 = -0.9;
c13 = +0.4; c23 = +0.7; c33 = +0.10;
if(i<NI-1 && j<NJ-1)
B[i*NJ + j] = c11 * A[(i - 1)*NJ + (j - 1)] + c12 * A[(i + 0)*NJ + (j - 1)] + c13 * A[(i + 1)*NJ + (j - 1)]
+ c21 * A[(i - 1)*NJ + (j + 0)] + c22 * A[(i + 0)*NJ + (j + 0)] + c23 * A[(i + 1)*NJ + (j + 0)]
+ c31 * A[(i - 1)*NJ + (j + 1)] + c32 * A[(i + 0)*NJ + (j + 1)] + c33 * A[(i + 1)*NJ + (j + 1)];
}
__global__ void Convolution_Shared(double* A, double* B)
{
int j = threadIdx.x + blockDim.x * blockIdx.x+1;
int i = threadIdx.y + blockDim.y * blockIdx.y+1;
int tx=threadIdx.y+1;
int ty=threadIdx.x+1;
const int sx=THREADS_PER_BLOCK_Y+2;
const int sy=THREADS_PER_BLOCK_X+2;
__shared__ double As[sx*sy];
//if corner element of block matrix, load off block corner neighbor.
if( tx==1 && ty==1 )
As[0]=A[(i-1)*NJ+j-1];
if( tx==sx-2 && ty==sy-2 )
As[(sx-1)*sy+sy-1]=A[(i+1)*NJ+j+1];
if( tx==1 && ty==sy-2 )
As[sy-1]=A[(i-1)*NJ+j+1];
if( tx==sx-2 && ty==1 )
As[(sx-1)*sy]=A[(i+1)*NJ+j-1];
//if border element of block matrix, load off block border neighbor.
if(tx==1)
As[ty]=A[(i-1)*NJ+j];
if(ty==1)
As[tx*sx]=A[i*NJ+j-1];
if(tx==sx-2)
As[(sx-1)*sy+ty]=A[(i+1)*NJ+j];
if(ty==sy-2)
As[tx*sy+sy-1]=A[i*NJ+j+1];
//load cell to shared memory.
As[tx*sy+ty]=A[i*NJ+j];
__syncthreads();
double c11, c12, c13, c21, c22, c23, c31, c32, c33;
c11 = +0.2; c21 = +0.5; c31 = -0.8;
c12 = -0.3; c22 = +0.6; c32 = -0.9;
c13 = +0.4; c23 = +0.7; c33 = +0.10;
if(i<NI-1 && j<NJ-1)
B[i*NJ + j] = c11 * As[(tx - 1)*sy+ty - 1] + c12 * As[(tx + 0)*sy+ty - 1] + c13 * As[(tx + 1)*sy+ty - 1]
+ c21 * As[(tx - 1)*sy+ty + 0] + c22 * As[(tx + 0)*sy+ty + 0] + c23 * As[(tx + 1)*sy+ty + 0]
+ c31 * As[(tx - 1)*sy+ty + 1] + c32 * As[(tx + 0)*sy+ty + 1] + c33 * As[(tx + 1)*sy+ty + 1];
}
void init(double* A_h)
{
int i, j;
for (i = 0; i < NI; ++i) {
for (j = 0; j < NJ; ++j) {
A_h[i*NJ + j] = (double)rand()/RAND_MAX;
}
}
}
int main(int argc, char *argv[])
{
//Serial program variables
double *B;
struct timeval start, end;
//Host and Device variables for CUDA
double *A_h;
double *B_h;
double *A_d;
double *B_d;
//Variables for shared memory implementation
double *A_s;
double *B_s;
//Main Memory allocation
B = (double*)malloc(NI*NJ*sizeof(double));
A_h = (double*)malloc(NI*NJ*sizeof(double));
B_h = (double*)malloc(NI*NJ*sizeof(double));
//Initialize the array
init(A_h);
//GPU Gloval Memory allocation
cudaMalloc((void**)&A_d, NI*NJ*sizeof(double));
cudaMalloc((void**)&B_d, NI*NJ*sizeof(double));
cudaMalloc((void**)&A_s, NI*NJ*sizeof(double));
cudaMalloc((void**)&B_s, NI*NJ*sizeof(double));
fprintf(stdout, "NI: %d NJ: %d\n", NI, NJ);
const unsigned int numBlocksInRow = ceil((double)(NJ-2)/THREADS_PER_BLOCK_X);
const unsigned int numBlocksInCol = ceil((double)(NI-2)/THREADS_PER_BLOCK_Y);
dim3 gridDim(numBlocksInRow, numBlocksInCol, 1), blockDim(THREADS_PER_BLOCK_X, THREADS_PER_BLOCK_Y, 1);
//Start of CUDA code
gettimeofday(&start, NULL);
cudaMemcpy(A_d, A_h, NI*NJ*sizeof(double), cudaMemcpyHostToDevice);
Convolution_kernel <<< gridDim, blockDim >>>(A_d, B_d);
cudaMemcpy(B_h, B_d , sizeof(double)*NI*NJ, cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
gettimeofday(&end, NULL);
fprintf(stdout, "GPU Runtime: %0.6lfs\n", ((end.tv_sec - start.tv_sec) * 1000000.0 + (end.tv_usec - start.tv_usec)) / 1000000.0);
//Start of CUDA shared code
gettimeofday(&start, NULL);
cudaMemcpy(A_s, A_h, NI*NJ*sizeof(double), cudaMemcpyHostToDevice);
Convolution_Shared <<< gridDim, blockDim >>>(A_s, B_s);
cudaMemcpy(B_h, B_s , sizeof(double)*NI*NJ, cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
gettimeofday(&end, NULL);
fprintf(stdout, "GPU Shared Runtime: %0.6lfs\n", ((end.tv_sec - start.tv_sec) * 1000000.0 + (end.tv_usec - start.tv_usec)) / 1000000.0);
//Start of Serial code
gettimeofday(&start, NULL);
Convolution(A_h, B);
gettimeofday(&end, NULL);
fprintf(stdout, "CPU Runtime: %0.6lfs\n", ((end.tv_sec - start.tv_sec) * 1000000.0 + (end.tv_usec - start.tv_usec)) / 1000000.0);
//Error checking CUDA results according to Serial results
int errors = 0;
for (int i = 0; i < NI; ++i) {
for (int j = 0; j < NJ; ++j) {
double error=fabs((B[i*NJ + j] -B_h[i*NJ+j]));
if(error>pow(10,-14)){
printf("Error %.20f in (%d,%d)\n",error,i,j);
errors++;
}
}
}
printf("Matrix\n\tTotal Results: %d\n\tError count: %d\n",NI*NJ,errors);
free(A_h);
free(B_h);
free(B);
cudaFree(A_d);
cudaFree(B_d);
cudaFree(A_s);
cudaFree(B_s);
return 0;
}
|
9,747 | #include "includes.h"
// Possible weight coefficients for tracking cost evaluation :
// Gaussian discretisation
/*
* 1 4 6 4 1
* 4 16 24 16 4
* 6 24 36 24 6
* 4 16 24 16 4
* 1 4 6 4 1
*/
// Compute spatial derivatives using Scharr operator - Naive implementation..
// Compute spatial derivatives using Scharr operator - Naive implementation..
// Compute spatial derivatives using Sobel operator - Naive implementation..
// Compute spatial derivatives using Sobel operator - Naive implementation..
// Low pass gaussian-like filtering before subsampling
// Low pass gaussian-like filtering before subsampling
/*
// Upsample a picture using the "magic" kernel
*/
__global__ void kernelMagicUpsampleX(float *in, int _w, int _h, float *out) {
// Coefficients : 1/4, 3/4, 3/4, 1/4 in each direction (doubles the size of the picture)
int x = blockIdx.x*blockDim.x + threadIdx.x;
int y = blockIdx.y*blockDim.y + threadIdx.y;
if(x >= _w || y >= _h)
return;
// Duplicate the points at the same place (?)
out[y*2*_w + 2*x] = in[y*_w+x];
if ((x < (_w-2)) && (x > 1))
out[y*2*_w + 2*x + 1] = __fdividef(3.0*(in[y*_w+x] + in[y*_w + x + 1]) + in[y*_w+x -1] + in[y*_w+x +2] , 8.0);
} |
9,748 | /*
* Copyright 2019 Australian National University
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either or express implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <cuda.h>
#include <stdio.h>
// this macro checks for errors in CUDA calls
#define Err(ans) \
{ gpucheck((ans), __FILE__, __LINE__); }
inline void gpucheck(cudaError_t code, const char *file, int line) {
if (code != cudaSuccess) {
fprintf(stderr, "GPU Err: %s %s %d\n", cudaGetErrorString(code),
file, line);
exit(code);
}
}
__global__ void hello(char *res, int size) {
char str[] = "Hello World!";
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if (idx < size)
res[idx] = str[idx];
}
int main(void) {
char *str_h, *str_d;
const int size = 13;
Err(cudaMallocHost(&str_h, size)); // note we could just use a normal
// malloc although this gives us
// pinned memory
Err(cudaMalloc(&str_d, size));
hello<<<1, 13>>>(str_d, size);
Err(cudaMemcpy(str_h, str_d, size, cudaMemcpyDeviceToHost));
printf("Result : %s\n", str_h);
cudaFree(str_h);
cudaFree(str_d);
}
|
9,749 | #include "includes.h"
__global__ void average_snips_v2(const double *Params, const int *iC, const int *call, const int *id, const float *uproj, const float *cmax, float *WU){
// jic, version with no threading over features, to avoid
// collisions when summing WU
// run
int my_chan, this_chan, bid, ind, Nspikes, NrankPC, NchanNear, Nchan;
float xsum = 0.0f;
int chanIndex, pcIndex;
Nspikes = (int) Params[0];
NrankPC = (int) Params[1];
Nchan = (int) Params[7];
NchanNear = (int) Params[6];
bid = blockIdx.x;
for(ind=0; ind<Nspikes;ind++)
if (id[ind]==bid){
my_chan = call[ind];
for (chanIndex = 0; chanIndex < NchanNear; ++chanIndex) {
this_chan = iC[chanIndex + NchanNear * my_chan];
for (pcIndex = 0; pcIndex < NrankPC; ++pcIndex) {
xsum = uproj[pcIndex + NrankPC*chanIndex + NrankPC*NchanNear * ind];
WU[pcIndex + NrankPC*this_chan + NrankPC*Nchan * bid] += xsum;
}
}
}
} |
9,750 | float h_A[]= {
0.8552914606559113, 0.5923296169583743, 0.8438793928444253, 0.8853316390569399, 0.5339562358056305, 0.8916040565318042, 0.5947898872673318, 0.5781849456814542, 0.5403457418228683, 0.6857724146065405, 0.5212960968115419, 0.7573433715717581, 0.773139626821338, 0.5886431052075701, 0.644953882013223, 0.8860718419697964, 0.9669948666354775, 0.6703767957021706, 0.7489377010310379, 0.9097591778172218, 0.5294498124538793, 0.899415605859927, 0.5116107302012385, 0.803518384237736, 0.6575517769850224, 0.6312062338227928, 0.8213741318424488, 0.5444261127584205, 0.6094712538653517, 0.5970027677685226, 0.5913756779365171, 0.8680674569758016, 0.5442881657322967, 0.9998708161974531, 0.9331836747194973, 0.9371188659452498, 0.987511034552633, 0.5900450127186042, 0.575565415250364, 0.5668992534256405, 0.7911796303478579, 0.7332256260332621, 0.6634172044997682, 0.8852920862949688, 0.9812675245637106, 0.851656838005556, 0.5130266149520026, 0.8564868705557078, 0.7505449194027255, 0.817767395276817, 0.9775335185324432, 0.708076130787376, 0.607344558752865, 0.8577364476779719, 0.5695110987244378, 0.8969073000166186, 0.744250369814371, 0.8569072278362877, 0.7913472125504628, 0.6780865637820372, 0.5973312707691849, 0.6579673380073123, 0.7901115138233272, 0.5844962364103774, 0.8080759404805662, 0.5729863246593099, 0.8652679942718013, 0.7387531517657737, 0.7577101568136786, 0.8606329765175526, 0.9643750547722778, 0.7614212387586731, 0.6053867300982567, 0.8639986236404394, 0.8707554467581833, 0.7989696209412447, 0.5701522482603216, 0.7300218575443711, 0.7562617855436586, 0.7355036573612701, 0.8514504556966944, 0.8018709104608999, 0.5948411770671695, 0.6539980247813431, 0.924868239766563, 0.9848012056337951, 0.7971582472246592, 0.7409997389203586, 0.7712763087111898, 0.6950704619036766, 0.5628076094633594, 0.6151778991259303, 0.5135547787012715, 0.7375433189727896, 0.7889949278454242, 0.5403456133711846, 0.7913950549327741, 0.5070730496982959, 0.8710363571859305, 0.5324758464996234, 0.7242663784898422, 0.7205531167637149, 0.7457149044948759, 0.621638558350492, 0.7169050101198777, 0.8542111606134606, 0.9198210522569643, 0.600657371972375, 0.9231497420870052, 0.6511169382051945, 0.6940395440281653, 0.8686479201949797, 0.7540107828205906, 0.954819259382805, 0.8971269910382051, 0.9895058221265471, 0.9514739168414448, 0.9445579123544143, 0.9862974002270355, 0.8810971317417515, 0.566167657592384, 0.9877479989785528, 0.8560931473354902, 0.6479616963274182, 0.8257488337374501, 0.872425732431376, 0.7157794699427147, 0.733443266475811, 0.8756745890792985, 0.6929885279537547, 0.5753312686903607, 0.7447028245274349, 0.9919301730115015, 0.9456643598258534, 0.9411605255575894, 0.9907733502190582, 0.6289748437164773, 0.6974684069394608, 0.9470241273488119, 0.8645001936781522, 0.9728993891715665, 0.5945744110332496, 0.9516727286011095, 0.6360283340767254, 0.75000717657955, 0.5704308147183266, 0.5018517770430411, 0.6848683482424488, 0.5596066086449278, 0.8178829914085004, 0.9324127828099447, 0.9721086764278226, 0.6387682588704979, 0.83656094580153, 0.8318502048862568, 0.8067481206101468, 0.7385918748036402, 0.7670894147504511, 0.5578075755744452, 0.7145256503710792, 0.8227283796106548, 0.7236590058723891, 0.6837112039346726, 0.6020347264942549, 0.8994287715813682, 0.5117782283278844, 0.61645806668123, 0.9382456709734496, 0.6868518928286782, 0.6122226304411428, 0.76058926520563, 0.6930265116427686, 0.5493946467061639, 0.5371156061403395, 0.8470653481357744, 0.9281268052725005, 0.6747658662117542, 0.6152965795313653, 0.8942136187625183, 0.638702797050216, 0.5469048336301936, 0.6117626023243823, 0.6060795760394071, 0.6157465146435147, 0.7138691137977484, 0.5472252159208092, 0.6027141544513348, 0.85313110140723, 0.5523946253567729, 0.9219764466345073, 0.9381579579849585, 0.8138102157882079, 0.6493824458429596, 0.8621610863502904, 0.567799718680229, 0.5322261797322172, 0.7973077770167046, 0.8547957080200983, 0.955870051674877, 0.7780412550594596, 0.7176070702673873, 0.9794752998056031, 0.952569720734671, 0.988940003405637, 0.6643486027388834, 0.9445963548561602, 0.849439368190245, 0.7168060942099733, 0.9979970761195824, 0.9274304504486292, 0.6234009723666344, 0.83327878521099, 0.7201574863927459, 0.5993127879020097, 0.5319385135639172, 0.6599840176612914, 0.7984044312413117, 0.9910404090463927, 0.9193691476415717, 0.7346156309065383, 0.7036432033987556, 0.5075355955921825, 0.5592802362349597, 0.7165347035895024, 0.966627700919767, 0.8468532404533885, 0.9239854296078917, 0.6552104743342584, 0.7716318117425189, 0.819677320496977, 0.77611679594386, 0.6977941959985732, 0.9519400728531004, 0.8870895158618441, 0.9004639371624151, 0.9195482314314958, 0.6257993849389232, 0.6813417124023791, 0.641743409568892, 0.7827721378010366, 0.7456561312270165, 0.8058723490864051, 0.9918880080028823, 0.6203094992497815, 0.9334856499047632, 0.6512030292232891, 0.8559578713819374, 0.7043950421128291, 0.6786680765205382, 0.5144967613200844, 0.5991092908283863, 0.763925124066626, 0.6692101018225243, 0.9705919177314013, 0.7973460094568832, 0.7288334863697796, 0.7870332864318796, 0.5823432019236596, 0.9841025574422817, 0.6737869846058664, 0.5491193681086302, 0.9599756348625824, 0.8534483355633525, 0.707280259224065, 0.8948826533417981, 0.8976520261478511, 0.9940722710088998, 0.7677602137374732, 0.6854065023478124, 0.6128172366359848, 0.9443311332921358, 0.9159709413272556, 0.9536978821053619, 0.8050718324985999, 0.6141252548675182, 0.8121132830100795, 0.8348313529098881, 0.7718084880694944, 0.977825025815352, 0.7724646913519021, 0.6601378583370568, 0.6380557529891356, 0.8861936474487304, 0.8536737054447974, 0.9852322322163571, 0.5228566622888734, 0.531521759501173, 0.8266748374652391, 0.6015471187292285, 0.9714700125256706, 0.5884938585935282, 0.539023782931323, 0.5770178586860077, 0.849822778296498, 0.8178684103575804, 0.6658255199450116, 0.5223923067814256, 0.886259425080691, 0.9529722592566829, 0.6376840880378198, 0.6831106879890456, 0.9907955001908837, 0.915621670182625, 0.9142227837002954, 0.7557967668840386, 0.898547574869123, 0.9369024156031915, 0.9901398137514257, 0.8278485559285267, 0.6465458401742599, 0.7112419936998956, 0.7497443735982382, 0.9102535708159228, 0.5573856622637985, 0.9225580090685143, 0.9322437485638634, 0.9729732053475502, 0.834793350751886, 0.8525353458149836, 0.9900883766894195, 0.8284470159338844, 0.9338228482757337, 0.7301135042695577, 0.7021459573777835, 0.9692579156469061, 0.5213700829824384, 0.5645856506569946, 0.6692395084404626, 0.5419800379762685, 0.769498155505731, 0.6600432882612699, 0.5957673643451651, 0.7044836980305904, 0.8209891442684718, 0.729916643340752, 0.6404085440176114, 0.9868334536855581, 0.9713007894640133, 0.9097350800880277, 0.8787327248584529, 0.5618240211671606, 0.7248869716798159, 0.8209552713091358, 0.8176574070437843, 0.7009576406798068, 0.9192390212198818, 0.9945798129732799, 0.8360640678643803, 0.9252898506845897, 0.9356158740961418, 0.5108280842161668, 0.5840147543436738, 0.7373628075164458, 0.5283598938180256, 0.7238807917511194, 0.6367515244369528, 0.971982022009227, 0.6971183730732275, 0.5887450865487525, 0.8014428867242778, 0.7416757225549089, 0.9000871040624858, 0.5280461337008239, 0.9830829019362726, 0.8499037314376936, 0.9841054759146295, 0.8995485891719925, 0.5017616073380963, 0.5766002880332017, 0.9286374248947598, 0.8898661510285373, 0.9923861972278842, 0.6663271828989026, 0.5144541021460076, 0.7178204559896197, 0.6049673229773087, 0.5709940280574868, 0.5691503346438467, 0.8499862068322386, 0.9134310390906629, 0.9071783798760704, 0.8171688615388438, 0.9979368293416115, 0.9027625218257558, 0.9669359003992583, 0.8812762172910653, 0.761403444810713, 0.9427991989862088, 0.6455106033063356, 0.9205538420542743, 0.5794996646195716, 0.7685726985058199, 0.5842572196269096, 0.5463702350719737, 0.6813489604103877, 0.8095169801001143, 0.9448714468411503, 0.5796856593606239, 0.8728428081804662, 0.5063527072356895, 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0.6441152196661138, 0.8272779940519193, 0.8625141095209217, 0.9518748907380618, 0.5493001985989481, 0.7629089030229318, 0.8956740645723325, 0.6519763412979213, 0.6669481457606838, 0.9600300482547983, 0.5301814958251598, 0.9600404701726408, 0.5055117055579995, 0.5210551797061085, 0.7083112944173384, 0.5085657953423555, 0.9016222488594192, 0.6203214795811809, 0.5550167289402577, 0.9531880498103452, 0.8078189641135842, 0.9307205847108347, 0.9488470403550902, 0.5460585137325458, 0.8400050872205546, 0.7471183332111808, 0.9652976891320548, 0.5016113390787834, 0.7588331944226012, 0.8166815982790818, 0.9271979775950598, 0.5917251280335833, 0.5081508997014992, 0.5729064575434735, 0.9210075423771017, 0.9664738359680973, 0.8613442687466395, 0.9062965610428987, 0.5948079583122929, 0.6546642574292276, 0.9178243691562578, 0.8760467407984724, 0.8766652424750774, 0.5149292886781767, 0.8987156058862277, 0.780218404311096, 0.8387946645926219, 0.9635611790887597, 0.5857949581247368, 0.6507061784950892, 0.5742100038360275, 0.9709026475982645, 0.7051938299857625, 0.5822264561245609, 0.6961557138165075, 0.9240732395646813, 0.5770297088812437, 0.856552570590476, 0.7083194175078431, 0.9083784483836526, 0.9103661929990596, 0.9392526472791137, 0.7837604708112317, 0.5907673785236744, 0.7351199805781177, 0.8760173756825707, 0.6813923307817122, 0.6064619245702465, 0.7286020593749377, 0.5758217679572213, 0.6515977823823365, 0.6608793691253634, 0.699467551679083, 0.9954058109682693, 0.7750420857968199, 0.5815993966476583, 0.7924076688940465, 0.6580555626206525, 0.8746956840532816, 0.6724050517343789, 0.9842807134303287, 0.7261709069197829, 0.8658607530657983, 0.6122228846541582, 0.8742962540734285, 0.5444646962902681, 0.6255754008829062, 0.700814882918244, 0.6388903513268235, 0.5539693948153144, 0.8872661391610582, 0.8830716321620158, 0.637704878821892, 0.6044129881433085, 0.7058751129922562, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0};
int h_B[]= {
0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 64, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98, 100, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134, 136, 138, 140, 142, 144, 146, 148, 150, 152, 154, 156, 158, 160, 162, 164, 166, 168, 170, 172, 174, 176, 178, 180, 182, 184, 186, 188, 190, 192, 194, 196, 198, 200, 202, 204, 206, 208, 210, 212, 214, 216, 218, 220, 222, 224, 226, 228, 230, 232, 234, 236, 238, 240, 242, 244, 246, 248, 250, 252, 254, 256, 258, 260, 262, 264, 266, 268, 270, 272, 274, 276, 278, 280, 282, 284, 286, 288, 290, 292, 294, 296, 298, 300, 302, 304, 306, 308, 310, 312, 314, 316, 318, 320, 322, 324, 326, 328, 330, 332, 334, 336, 338, 340, 342, 344, 346, 348, 350, 352, 354, 356, 358, 360, 362, 364, 366, 368, 370, 372, 374, 376, 378, 380, 382, 384, 386, 388, 390, 392, 394, 396, 398, 400, 402, 404, 406, 408, 410, 412, 414, 416, 418, 420, 422, 424, 426, 428, 430, 432, 434, 436, 438, 440, 442, 444, 446, 448, 450, 452, 454, 456, 458, 460, 462, 464, 466, 468, 470, 472, 474, 476, 478, 480, 482, 484, 486, 488, 490, 492, 494, 496, 498, 500, 502, 504, 506, 508, 510, 512, 514, 516, 518, 520, 522, 524, 526, 528, 530, 532, 534, 536, 538, 540, 542, 544, 546, 548, 550, 552, 554, 556, 558, 560, 562, 564, 566, 568, 570, 572, 574, 576, 578, 580, 582, 584, 586, 588, 590, 592, 594, 596, 598, 600, 602, 604, 606, 608, 610, 612, 614, 616, 618, 620, 622, 624, 626, 628, 630, 632, 634, 636, 638, 640, 642, 644, 646, 648, 650, 652, 654, 656, 658, 660, 662, 664, 666, 668, 670, 672, 674, 676, 678, 680, 682, 684, 686, 688, 690, 692, 694, 696, 698, 700, 702, 704, 706, 708, 710, 712, 714, 716, 718, 720, 722, 724, 726, 728, 730, 732, 734, 736, 738, 740, 742, 744, 746, 748, 750, 752, 754, 756, 758, 760, 762, 764, 766, 768, 770, 772, 774, 776, 778, 780, 782, 784, 786, 788, 790, 792, 794, 796, 798, 800, 802, 804, 806, 808, 810, 812, 814, 816, 818, 820, 822, 824, 826, 828, 830, 832, 834, 836, 838, 840, 842, 844, 846, 848, 850, 852, 854, 856, 858, 860, 862, 864, 866, 868, 870, 872, 874, 876, 878, 880, 882, 884, 886, 888, 890, 892, 894, 896, 898, 900, 902, 904, 906, 908, 910, 912, 914, 916, 918, 920, 922, 924, 926, 928, 930, 932, 934, 936, 938, 940, 942, 944, 946, 948, 950, 952, 954, 956, 958, 960, 962, 964, 966, 968, 970, 972, 974, 976, 978, 980, 982, 984, 986, 988, 990, 992, 994, 996, 998, 1000, 1002, 1004, 1006, 1008, 1010, 1012, 1014, 1016, 1018, 1020, 1022, 1024, 1026, 1028, 1030, 1032, 1034, 1036, 1038, 1040, 1042, 1044, 1046, 1048, 1050, 1052, 1054, 1056, 1058, 1060, 1062, 1064, 1066, 1068, 1070, 1072, 1074, 1076, 1078, 1080, 1082, 1084, 1086, 1088, 1090, 1092, 1094, 1096, 1098, 1100, 1102, 1104, 1106, 1108, 1110, 1112, 1114, 1116, 1118, 1120, 1122, 1124, 1126, 1128, 1130, 1132, 1134, 1136, 1138, 1140, 1142, 1144, 1146, 1148, 1150, 1152, 1154, 1156, 1158, 1160, 1162, 1164, 1166, 1168, 1170, 1172, 1174, 1176, 1178, 1180, 1182, 1184, 1186, 1188, 1190, 1192, 1194, 1196, 1198, 1200, 1202, 1204, 1206, 1208, 1210, 1212, 1214, 1216, 1218, 1220, 1222, 1224, 1226, 1228, 1230, 1232, 1234, 1236, 1238, 1240, 1242, 1244, 1246, 1248, 1250, 1252, 1254, 1256, 1258, 1260, 1262, 1264, 1266, 1268, 1270, 1272, 1274, 1276, 1278, 1280, 1282, 1284, 1286, 1288, 1290, 1292, 1294, 1296, 1298, 1300, 1302, 1304, 1306, 1308, 1310, 1312, 1314, 1316, 1318, 1320, 1322, 1324, 1326, 1328, 1330, 1332, 1334, 1336, 1338, 1340, 1342, 1344, 1346, 1348, 1350, 1352, 1354, 1356, 1358, 1360, 1362, 1364, 1366, 1368, 1370, 1372, 1374, 1376, 1378, 1380, 1382, 1384, 1386, 1388, 1390, 1392, 1394, 1396, 1398, 1400, 1402, 1404, 1406, 1408, 1410, 1412, 1414, 1416, 1418, 1420, 1422, 1424, 1426, 1428, 1430, 1432, 1434, 1436, 1438, 1440, 1442, 1444, 1446, 1448, 1450, 1452, 1454, 1456, 1458, 1460, 1462, 1464, 1466, 1468, 1470, 1472, 1474, 1476, 1478, 1480, 1482, 1484, 1486, 1488, 1490, 1492, 1494, 1496, 1498, 1500, 1502, 1504, 1506, 1508, 1510, 1512, 1514, 1516, 1518, 1520, 1522, 1524, 1526, 1528, 1530, 1532, 1534, 1536, 1538, 1540, 1542, 1544, 1546, 1548, 1550, 1552, 1554, 1556, 1558, 1560, 1562, 1564, 1566, 1568, 1570, 1572, 1574, 1576, 1578, 1580, 1582, 1584, 1586, 1588, 1590, 1592, 1594, 1596, 1598, 1600, 1602, 1604, 1606, 1608, 1610, 1612, 1614, 1616, 1618, 1620, 1622, 1624, 1626, 1628, 1630, 1632, 1634, 1636, 1638, 1640, 1642, 1644, 1646, 1648, 1650, 1652, 1654, 1656, 1658, 1660, 1662, 1664, 1666, 1668, 1670, 1672, 1674, 1676, 1678, 1680, 1682, 1684, 1686, 1688, 1690, 1692, 1694, 1696, 1698, 1700, 1702, 1704, 1706, 1708, 1710, 1712, 1714, 1716, 1718, 1720, 1722, 1724, 1726, 1728, 1730, 1732, 1734, 1736, 1738, 1740, 1742, 1744, 1746, 1748, 1750, 1752, 1754, 1756, 1758, 1760, 1762, 1764, 1766, 1768, 1770, 1772, 1774, 1776, 1778, 1780, 1782, 1784, 1786, 1788, 1790, 1792, 1794, 1796, 1798, 1800, 1802, 1804, 1806, 1808, 1810, 1812, 1814, 1816, 1818, 1820, 1822, 1824, 1826, 1828, 1830, 1832, 1834, 1836, 1838, 1840, 1842, 1844, 1846, 1848, 1850, 1852, 1854, 1856, 1858, 1860, 1862, 1864, 1866, 1868, 1870, 1872, 1874, 1876, 1878, 1880, 1882, 1884, 1886, 1888, 1890, 1892, 1894, 1896, 1898, 1900, 1902, 1904, 1906, 1908, 1910, 1912, 1914, 1916, 1918, 1920, 1922, 1924, 1926, 1928, 1930, 1932, 1934, 1936, 1938, 1940, 1942, 1944, 1946, 1948, 1950, 1952, 1954, 1956, 1958, 1960, 1962, 1964, 1966, 1968, 1970, 1972, 1974, 1976, 1978, 1980, 1982, 1984, 1986, 1988, 1990, 1992, 1994, 1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2013, 2015, 2017, 2019, 2021, 2023, 2025, 2027, 2029, 2031, 2033, 2035, 2037, 2039, 2042, 2044, 2046, 2048, 2050, 2052, 2054, 2056, 2058, 2060, 2062, 2064, 2066, 2068, 2070, 2072, 2074, 2076, 2078, 2080, 2082, 2084, 2086, 2088, 2090, 2092, 2094, 2096, 2098, 2100, 2102, 2104, 2106, 2108, 2110, 2112, 2114, 2116, 2118, 2120, 2122, 2124, 2126, 2128, 2130, 2132, 2134, 2136, 2138, 2140, 2142, 2144, 2146, 2148, 2150, 2152, 2154, 2156, 2158, 2160, 2162, 2164, 2166, 2168, 2170, 2172, 2174, 2176, 2178, 2180, 2182, 2184, 2186, 2188, 2190, 2192, 2194, 2196, 2198, 2200, 2202, 2204, 2206, 2208, 2210, 2212, 2214, 2216, 2218, 2220, 2222, 2224, 2226, 2228, 2230, 2232, 2234, 2236, 2238, 2240, 2242, 2244, 2246, 2248, 2250, 2252, 2254, 2256, 2258, 2260, 2262, 2264, 2266, 2268, 2271, 2273, 2275, 2277, 2280, 2282, 2284, 2286, 2288, 2290, 2292, 2294, 2296, 2298, 2300, 2302, 2304, 2306, 2308, 2310, 2312, 2314, 2316, 2318, 2320, 2322, 2324, 2326, 2328, 2330, 2332, 2334, 2336, 2338, 2340, 2342, 2344, 2346, 2348, 2350, 2352, 2354, 2356, 2358, 2360, 2362, 2364, 2366, 2368, 2370, 2372, 2374, 2376, 2378, 2380, 2382, 2384, 2386, 2388, 2390, 2392, 2394, 2396, 2398, 2400, 2402, 2404, 2406, 2408, 2410, 2412, 2414, 2416, 2418, 2420, 2422, 2424, 2426, 2428, 2430, 2432, 2434, 2436, 2438, 2440, 2442, 2444, 2446, 2448, 2450, 2452, 2454, 2456, 2458, 2460, 2462, 2464, 2466, 2468, 2470, 2472, 2474, 2476, 2478, 2480, 2482, 2484, 2486, 2488, 2490, 2492, 2494, 2496, 2498, 2500, 2502, 2504, 2506, 2508, 2510, 2512, 2514, 2516, 2518, 2520, 2522, 2524, 2526, 2528, 2530, 2532, 2534, 2536, 2538, 2540, 2542, 2544, 2546, 2548, 2550, 2552, 2554, 2556, 2558, 2560, 2562, 2564, 2566, 2568, 2570, 2572, 2574, 2576, 2578, 2580, 2582, 2584, 2586, 2588, 2590, 2592, 2594, 2596, 2598, 2600, 2602, 2604, 2606, 2608, 2610, 2612, 2614, 2616, 2618, 2620, 2622, 2624, 2626, 2628, 2630, 2632, 2634, 2636, 2638, 2640, 2642, 2644, 2646, 2648, 2650, 2652, 2654, 2656, 2658, 2660, 2662, 2664, 2666, 2668, 2670, 2672, 2674, 2676, 2678, 2680, 2682, 2684, 2686, 2688, 2690, 2692, 2694, 2696, 2698, 2700, 2702, 2704, 2706, 2708, 2710, 2712, 2714, 2716, 2718, 2720, 2722, 2724, 2726, 2728, 2730, 2732, 2734, 2736, 2738, 2740, 2742, 2744, 2746, 2748, 2750, 2752, 2754, 2756, 2758, 2760, 2762, 2764, 2766, 2768, 2770, 2772, 2774, 2776, 2778, 2780, 2782, 2784, 2786, 2788, 2790, 2792, 2794, 2796, 2798, 2800, 2802, 2804, 2806, 2808, 2810, 2812, 2814, 2816, 2818, 2820, 2822, 2824, 2826, 2828, 2830, 2832, 2834, 2836, 2838, 2840, 2842, 2844, 2846, 2848, 2850, 2852, 2854, 2856, 2858, 2860, 2862, 2864, 2866, 2868, 2870, 2872, 2874, 2876, 2878, 2880, 2882, 2884, 2886, 2888, 2890, 2892, 2894, 2896, 2898, 2900, 2902, 2904, 2906, 2908, 2910, 2912, 2914, 2916, 2918, 2920, 2922, 2924, 2926, 2928, 2930, 2932, 2934, 2936, 2938, 2940, 2942, 2944, 2946, 2948, 2950, 2952, 2954, 2956, 2958, 2960, 2962, 2964, 2966, 2968, 2970, 2972, 2974, 2976, 2978, 2980, 2982, 2984, 2986, 2988, 2990, 2992, 2994, 2996, 2998, 3000, 3002, 3004, 3006, 3008, 3010, 3012, 3014, 3016, 3018, 3020, 3022, 3024, 3026, 3028, 3030, 3032, 3034, 3036, 3038, 3040, 3042, 3044, 3046, 3048, 3050, 3052, 3054, 3056, 3058, 3060, 3062, 3064, 3066, 3068, 3070, 3072, 3074, 3076, 3078, 3080, 3082, 3084, 3086, 3088, 3090, 3092, 3094, 3096, 3098, 3100, 3102, 3104, 3106, 3108, 3110, 3112, 3114, 3116, 3118, 3120, 3122, 3124, 3126, 3128, 3130, 3132, 3134, 3136, 3138, 3140, 3142, 3144, 3146, 3148, 3150, 3152, 3154, 3156, 3158, 3160, 3162, 3164, 3166, 3168, 3170, 3172, 3174, 3176, 3178, 3180, 3182, 3184, 3186, 3188, 3190, 3192, 3194, 3196, 3198, 3200, 3202, 3204, 3206, 3208, 3210, 3212, 3214, 3216, 3218, 3220, 3222, 3224, 3226, 3228, 3230, 3232, 3234, 3236, 3238, 3240, 3242, 3244, 3246, 3248, 3250, 3252, 3254, 3256, 3258, 3260, 3262, 3264, 3266, 3268, 3270, 3272, 3274, 3276, 3278, 3280, 3282, 3284, 3286, 3288, 3290, 3292, 3294, 3296, 3298, 3300, 3302, 3304, 3306, 3308, 3310, 3312, 3314, 3316, 3318, 3320, 3322, 3324, 3326, 3328, 3330, 3332, 3334, 3336, 3338, 3340, 3342, 3344, 3346, 3348, 3350, 3352, 3354, 3356, 3358, 3360, 3362, 3364, 3366, 3368, 3370, 3372, 3374, 3376, 3378, 3380, 3382, 3384, 3386, 3388, 3390, 3392, 3394, 3396, 3398, 3400, 3402, 3404, 3406, 3408, 3410, 3412, 3414, 3416, 3418, 3420, 3422, 3424, 3426, 3428, 3430, 3432, 3434, 3436, 3438, 3440, 3442, 3444, 3446, 3448, 3450, 3452, 3454, 3456, 3458, 3460, 3462, 3464, 3466, 3468, 3470, 3472, 3474, 3476, 3478, 3480, 3482, 3484, 3486, 3488, 3490, 3492, 3494, 3496, 3498, 3500, 3502, 3504, 3506, 3508, 3510, 3512, 3514, 3516, 3518, 3520, 3522, 3524, 3526, 3528, 3530, 3532, 3534, 3536, 3538, 3540, 3542, 3544, 3546, 3548, 3550, 3552, 3554, 3556, 3558, 3560, 3562, 3564, 3566, 3568, 3570, 3572, 3574, 3576, 3578, 3580, 3582, 3584, 3586, 3588, 3590, 3592, 3594, 3596, 3598, 3600, 3602, 3604, 3606, 3608, 3610, 3612, 3614, 3616, 3618, 3620, 3622, 3624, 3626, 3628, 3630, 3632, 3634, 3636, 3638, 3640, 3642, 3644, 3646, 3648, 3650, 3652, 3654, 3656, 3658, 3660, 3662, 3664, 3666, 3668, 3670, 3672, 3674, 3676, 3678, 3680, 3682, 3684, 3686, 3688, 3690, 3692, 3694, 3696, 3698, 3700, 3702, 3704, 3706, 3708, 3710, 3712, 3714, 3716, 3718, 3720, 3722, 3724, 3726, 3728, 3730, 3732, 3734, 3736, 3738, 3740, 3742, 3744, 3746, 3748, 3750, 3752, 3754, 3756, 3758, 3760, 3762, 3764, 3766, 3768, 3770, 3772, 3774, 3776, 3778, 3780, 3782, 3784, 3786, 3788, 3790, 3792, 3794, 3796, 3798, 3800, 3802, 3804, 3806, 3808, 3810, 3812, 3814, 3816, 3818, 3820, 3822, 3824, 3826, 3828, 3830, 3832, 3834, 3836, 3838, 3840, 3842, 3844, 3846, 3848, 3850, 3852, 3854, 3857, 3859, 3861, 3863, 3865, 3867, 3869, 3871, 3873, 3875, 3877, 3879, 3881, 3883, 3885, 3887, 3889, 3891, 3893, 3895, 3897, 3899, 3901, 3903, 3905, 3907, 3909, 3911, 3913, 3915, 3917, 3919, 3921, 3923, 3925, 3927, 3929, 3931, 3933, 3935, 3937, 3939, 3941, 3943, 3945, 3947, 3949, 3951, 3953, 3955, 3957, 3959, 3961, 3963, 3965, 3967, 3969, 3971, 3973, 3975, 3977, 3979, 3981, 3983, 3985, 3987, 3989, 3991, 3993, 3995, 3997, 3999, 4001, 4003, 4005, 4007, 4009, 4011, 4013, 4015, 4017, 4019, 4021, 4023, 4025, 4027, 4029, 4031, 4033, 4035, 4037, 4039, 4041, 4043, 4045, 4047, 4049, 4051, 4053, 4055, 4057, 4059, 4061, 4063, 4065, 4067, 4069, 4071, 4073, 4075, 4077, 4079, 4081, 4083, 4085, 4087, 4089, 4091, 4093, 4095, 4097, 4099, 4101, 4103, 4105, 4107, 4109, 4111, 4113, 4115, 4117, 4119, 4121, 4123, 4125, 4127, 4129, 4131, 4133, 4135, 4137, 4139, 4141, 4143, 4145, 4147, 4149, 4151, 4153, 4155, 4157, 4159, 4161, 4163, 4165, 4167, 4169, 4171, 4173, 4175, 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5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 34032, 34033, 34034, 34035, 34036, 34038, 34039, 34040, 34041, 34042, 34044, 34045, 34046, 34047, 34048, 34051, 34053, 34054, 34055, 34056, 34057, 34058, 34059, 34060, 34062, 34064, 34065, 34066, 34067, 34068, 34071, 34073, 34076, 34077, 34078, 34079, 34081, 34082, 34083, 34084, 34085, 34086, 34088, 34089, 34090, 34091, 34092, 34093, 34095, 34096, 34097, 34098, 34099, 34100, 34102, 34103, 34104, 34105, 34106, 34107, 34109, 34110, 34111, 34112, 34113, 34114, 34116, 34117, 34119, 34122, 34123, 34124, 34125, 34127, 34128, 34129, 34130, 34131, 34132, 34134, 34135, 34136, 34137, 34138, 34139, 34141, 34143, 34144, 34145, 34146, 34148, 34151, 34152, 34153, 34154, 34155, 34157, 34159, 34160, 34161, 34162, 34164, 34166, 34168, 34171, 34172, 34173, 34174, 34175, 34177, 34178, 34179, 34180, 34181, 34183, 34184, 34185, 34186, 34187, 34190, 34192, 34193, 34194, 34195, 34197, 34198, 34199, 34201, 34202, 34203, 34204, 34206, 34207, 34208, 34209, 34210, 34211, 34212, 34214, 34215, 34216, 34218, 34219, 34220, 34222, 34223, 34224, 34225, 34227, 34228, 34229, 34230, 34231, 34233, 34234, 34235, 34237, 34238, 34239, 34241, 34242, 34243, 34244, 34246, 34247, 34248, 34249, 34250, 34251, 34252, 34254, 34255, 34256, 34257, 34258, 34259, 34260, 34261, 34263, 34264, 34265, 34266, 34267, 34268, 34269, 34270, 34271, 34272, 34273, 34274, 34275, 34276, 34277, 34278, 34281, 34282, 34284, 34285, 34286, 34287, 34288, 34289, 34290, 34291, 34292, 34293, 34294, 34295, 34296, 34299, 34300, 34302, 34303, 34304, 34305, 34306, 34307, 34309, 34310, 34311, 34314, 34315, 34317, 34319, 34320, 34321, 34322, 34324, 34325, 34326, 34327, 34328, 34330, 34331, 34332, 34333, 34334, 34335, 34336, 34338, 34339, 34340, 34341, 34342, 34343, 34344, 34345, 34346, 34347, 34348, 34350, 34351, 34352, 34353, 34354, 34355, 34357, 34358, 34359, 34360, 34361, 34362, 34363, 34364, 34365, 34366, 34367, 34368, 34369, 34370, 34371, 34373, 34374, 34375, 34376, 34377, 34378, 34379, 34380, 34381, 34382, 34384, 34385, 34386, 34387, 34388, 34389, 34391, 34392, 34393, 34394, 34395, 34396, 34397, 34398, 34399, 34400, 34401, 34402, 34403, 34405, 34406, 34407, 34408, 34409, 34410, 34411, 34412, 34413, 34415, 34416, 34417, 34418, 34419, 34420, 34421, 34422, 34423, 34424, 34426, 34427, 34428, 34429, 34430, 34431, 34432, 34434, 34435, 34436, 34437, 34438, 34439, 34440, 34442, 34443, 34445, 34448, 34449, 34450, 34451, 34452, 34453, 34454, 34455, 34456, 34457, 34458, 34459, 34460, 34462, 34463, 34464, 34465, 34466, 34467, 34468, 34469, 34471, 34472, 34474, 34477, 34478, 34479, 34480, 34481, 34482, 34483, 34484, 34485, 34486, 34487, 34488, 34489, 34491, 34492, 34493, 34494, 34495, 34496, 34497, 34498, 34499, 34500, 34501, 34502, 34503, 34504, 34505, 34506, 34507, 34509, 34510, 34511, 34512, 34513, 34514, 34515, 34516, 34518, 34519, 34520, 34521, 34522, 34523, 34524, 34526, 34527, 34528, 34530, 34531, 34533, 34534, 34535, 34537, 34538, 34539, 34540, 34541, 34542, 34544, 34546, 34547, 34548, 34549, 34551, 34552, 34553, 34555, 34556, 34557, 34559, 34560, 34561, 34562, 34564, 34565, 34566, 34567, 34568, 34571, 34572, 34573, 34574, 34575, 34578, 34579, 34580, 34581, 34583, 34584, 34585, 34586, 34587, 34589, 34590, 34593, 34596, 34597, 34599, 34600, 34601, 34602, 34604, 34606, 34607, 34608, 34609, 34611, 34613, 34614, 34615, 34616, 34618, 34620, 34622, 34625, 34626, 34627, 34628, 34629, 34631, 34633, 34636, 34637, 34638, 34639, 34641, 34643, 34644, 34645, 34646, 34647, 34650, 34652, 34655, 34656, 34657, 34658, 34659, 34660, 34661, 34662, 34663, 34664, 34665, 34666, 34667, 34668, 34669, 34670, 34672, 34674, 34677, 34678, 34679, 34680, 34682, 34683, 34684, 34685, 34686, 34687, 34688, 34689, 34690, 34691, 34692, 34693, 34695, 34697, 34700, 34701, 34702, 34703, 34704, 34705, 34706, 34707, 34708, 34709, 34710, 34711, 34712, 34713, 34714, 34715, 34716, 34717, 34718, 34719, 34720, 34721, 34723, 34725, 34728, 34729, 34731, 34732, 34733, 34734, 34735, 34737, 34738, 34739, 34741, 34742, 34743, 34745, 34746, 34747, 34748, 34750, 34751, 34753, 34755, 34756, 34757, 34758, 34760, 34762, 34763, 34764, 34767, 34768, 34769, 34770, 34771, 34772, 34773, 34774, 34775, 34776, 34777, 34778, 34780, 34781, 34782, 34783, 34784, 34785, 34786, 34787, 34788, 34789, 34791, 34792, 34793, 34794, 34795, 34797, 34799, 34800, 34801, 34802, 34804, 34805, 34806, 34807, 34808, 34809, 34810, 34811, 34812, 34814, 34121, 34815, 34699, 34816, 34817, 34819, 34823, 34825, 34827, 34828, 34832, 34833, 34834, 34476, 34835, 34447, 34836, 34837, 34838, 34839, 34840, 34841, 34842, 34843, 34845, 34635, 34699, 34848, 34676, 34850, 34851, 34852, 34853, 34854, 34856, 34862, 34476, 34868, 34447, 34869, 34870, 34871, 34872, 34873, 34874, 34875, 34876, 34878, 34879, 34447, 34882, 34883, 34476, 34884, 34885, 34886, 34887, 34888, 34889, 34890, 34892, 34893, 34894, 34895, 34896, 34897, 34635, 34899, 34676, 34699, 34901, 34902, 34905, 34907, 34908, 34914, 33947, 33945, 33961, 33959, 34859, 33984, 33982, 34865, 34867, 33998, 34000, 34904, 34911, 34022, 34020, 34916, 12, 13, 14, 15, 34928, 34930, 34932, 34933, 34935, 34937, 34938, 34940, 34942, 34945, 34948, 34950, 34061, 34953, 34955, 34957, 34960, 34962, 34080, 34966, 34968, 34087, 34972, 34974, 34094, 34978, 34980, 34101, 34984, 34986, 34108, 34990, 34992, 34115, 34997, 34999, 34126, 35003, 35005, 34133, 35009, 35011, 34140, 35014, 35016, 34147, 35020, 35022, 34156, 35025, 35027, 34163, 35032, 35034, 35036, 35037, 35039, 35041, 35042, 35044, 35046, 35049, 34196, 34200, 35057, 35058, 35059, 35062, 34213, 35067, 34217, 34221, 35074, 35078, 34232, 35082, 34236, 34240, 35089, 35091, 35094, 34253, 35099, 35103, 34262, 35107, 35109, 35111, 35113, 35115, 35117, 33757, 35122, 35124, 35126, 35128, 35130, 35132, 33764, 35137, 35141, 35144, 35145, 35148, 34318, 33776, 35157, 34329, 35161, 35163, 35165, 35168, 35170, 35174, 35176, 34349, 35180, 35182, 34356, 35186, 35188, 35190, 35192, 35194, 35196, 35200, 35203, 35205, 35209, 35211, 35215, 35217, 35219, 35221, 35223, 35225, 35229, 35234, 34414, 35238, 35243, 35246, 35247, 35251, 34433, 35255, 35257, 35259, 34441, 35264, 35266, 35268, 35270, 35272, 35274, 35278, 35281, 35283, 34470, 35288, 35290, 35292, 35294, 35296, 35298, 35302, 35305, 35307, 35309, 35311, 35313, 35315, 35319, 35322, 35324, 35327, 35329, 35337, 35340, 35342, 35344, 35348, 35351, 35352, 35354, 35356, 34558, 35360, 35362, 35364, 35366, 35367, 35369, 35371, 35372, 35374, 34582, 35377, 35379, 34588, 35384, 35386, 35388, 34603, 35391, 35393, 34610, 35396, 35398, 34617, 35403, 35405, 35407, 35410, 35412, 34640, 35415, 35417, 35419, 35422, 35424, 35428, 35430, 35434, 35436, 35440, 35442, 35445, 35447, 35451, 35453, 35455, 35458, 35460, 33908, 35464, 35466, 33909, 35470, 35472, 33910, 35476, 35478, 34722, 35482, 35486, 34736, 35490, 34740, 34744, 35497, 35499, 34754, 33926, 35506, 35509, 35511, 35513, 35515, 35518, 34779, 35523, 35525, 35528, 34790, 35533, 35535, 34798, 33936, 35544, 35547, 35549, 34944, 34075, 34072, 35552, 34996, 35554, 35019, 34170, 34167, 35048, 33217, 35077, 33224, 35102, 35326, 35332, 35336, 35334, 35563, 35565, 35287, 35567, 35263, 34280, 34298, 35571, 32289, 35573, 35140, 35233, 35577, 35409, 35444, 35450, 35578, 35457, 35427, 35433, 35438, 35580, 35439, 34654, 34651, 34624, 34621, 34313, 34727, 29960, 29966, 35156, 35485, 35167, 35173, 35588, 35287, 35590, 35263, 35199, 35208, 35214, 35326, 35336, 35334, 35593, 35228, 32289, 35596, 35233, 35599, 35242, 35250, 35601, 35263, 35277, 35604, 35287, 35301, 35318, 35326, 35332, 35336, 35334, 35608, 35610, 34545, 34543, 35612, 32289, 35614, 34595, 34592, 34624, 34621, 35618, 35409, 34654, 34651, 35427, 35433, 35438, 35620, 35439, 35444, 35450, 35621, 35457, 34727, 35485, 30151, 30160, 30197, 35543, 34820, 35628, 35629, 34824, 34826, 33954, 34829, 35630, 35631, 33962, 33967, 33970, 34855, 34857, 35632, 35633, 35634, 34863, 35635, 35636, 33995, 35637, 35638, 35639, 34906, 34013, 34909, 35640, 35641, 35642, 34025, 35643, 35710, 35715, 35718, 35724, 35728, 35751, 35825, 35832, 35896, 35899, 35902, 35903, 35907, 35911, 35914, 35649, 34037, 35652, 34043, 35655, 34050, 34947, 35920, 35659, 34063, 35662, 34070, 35921, 35922, 35665, 34965, 35668, 34971, 35671, 34977, 35674, 34983, 35677, 34989, 35680, 34995, 35924, 35683, 35002, 35686, 35008, 35689, 34142, 35692, 34149, 35926, 35695, 34158, 35698, 34165, 35927, 35928, 35701, 34176, 35704, 34182, 35707, 34189, 35051, 35929, 35056, 33210, 32112, 35061, 32121, 32120, 33215, 32128, 35073, 35930, 32132, 35080, 35931, 33220, 32141, 35088, 35932, 32149, 35093, 32158, 32157, 35105, 35933, 33229, 32165, 35822, 35934, 35824, 35935, 35936, 35937, 35805, 35286, 35940, 35795, 35262, 35942, 35735, 35114, 35738, 35120, 34283, 35943, 35742, 35129, 35745, 35135, 34301, 35944, 35341, 32269, 32268, 35359, 35946, 32288, 35143, 35948, 33240, 32184, 35236, 35949, 33259, 32220, 35859, 35408, 35951, 35874, 35952, 35876, 35953, 35878, 35456, 35955, 35868, 35956, 35870, 35957, 35872, 35958, 35960, 35862, 34642, 35865, 34649, 35961, 35962, 35850, 34605, 35853, 34612, 35856, 34619, 35963, 35964, 35837, 34570, 35840, 34577, 35843, 33859, 35846, 33861, 34598, 35965, 35881, 35463, 35884, 35469, 35887, 35475, 35890, 34724, 34730, 35966, 29958, 29957, 35496, 35967, 29959, 35517, 29962, 29961, 35527, 29964, 29963, 35152, 35968, 29965, 35159, 35969, 29975, 29974, 35488, 35970, 29979, 29978, 35758, 35971, 35760, 35972, 35974, 35762, 35179, 35765, 35185, 35976, 35768, 35191, 35771, 35197, 35202, 35977, 35775, 35978, 35777, 35979, 35822, 35980, 35981, 35982, 35779, 35220, 35782, 35226, 35231, 35984, 35359, 35985, 32288, 35236, 35987, 33259, 32220, 35341, 32269, 32268, 35245, 35989, 33263, 32231, 35253, 35990, 33265, 32236, 35795, 35262, 35992, 35798, 35269, 35801, 35275, 35280, 35993, 35805, 35286, 35995, 35808, 35293, 35811, 35299, 35304, 35996, 35815, 35310, 35818, 35316, 35321, 35997, 35822, 35998, 35824, 35999, 36000, 36001, 35341, 32269, 32268, 35350, 36004, 36005, 32279, 32278, 35359, 36007, 32288, 35837, 34570, 35840, 34577, 35843, 33859, 35846, 33861, 34598, 36009, 36010, 35850, 34605, 35853, 34612, 35856, 34619, 36011, 36012, 35859, 35408, 36014, 35862, 34642, 35865, 34649, 36015, 36016, 35868, 36017, 35870, 36018, 35872, 36019, 36021, 35874, 36022, 35876, 36023, 35878, 35456, 36025, 35881, 35463, 35884, 35469, 35887, 35475, 35890, 34724, 34730, 36026, 35488, 36027, 30142, 30141, 35496, 36028, 30150, 35503, 36029, 30159, 30168, 30167, 35517, 30178, 30177, 35527, 30185, 30184, 35539, 36030, 30196, 35546, 36031, 30205, 30204, 36032, 36033, 36035, 36036, 36037, 36038, 36039, 36041, 33963, 33964, 36042, 36043, 36044, 36045, 36047, 36049, 33992, 36052, 33996, 34891, 34002, 34003, 36056, 36057, 36058, 36060, 36062, 10, 11, 12, 13, 14, 15, 36079, 36080, 36081, 36082, 36083, 36084, 36085, 36087, 36088, 36089, 36090, 36091, 36093, 36094, 36095, 36096, 36097, 36098, 36099, 36100, 36101, 36102, 36103, 36104, 35923, 36106, 36107, 36108, 36109, 36110, 36111, 36112, 36113, 35925, 36115, 36116, 36117, 36118, 36119, 36121, 36122, 36123, 36124, 36125, 36126, 36127, 36129, 35054, 36130, 36131, 35065, 36132, 36133, 36134, 35510, 35508, 36135, 36136, 36137, 35071, 36139, 36140, 36142, 36143, 36144, 35086, 36146, 35097, 36147, 36148, 36149, 36150, 36152, 36153, 36154, 36156, 36158, 36160, 36161, 35939, 36163, 36164, 35941, 36166, 36167, 36168, 36169, 36170, 36172, 36173, 36174, 36175, 36176, 36178, 35339, 36179, 36180, 36181, 35833, 36183, 36184, 36186, 36187, 36188, 36190, 36191, 36192, 36193, 35950, 36195, 36197, 36199, 36200, 35954, 36202, 36204, 36206, 35959, 36209, 36210, 36211, 36212, 36213, 36215, 36216, 36217, 36218, 36219, 36220, 36221, 36223, 36224, 36225, 36226, 36227, 36228, 36229, 36230, 36231, 36233, 36234, 36235, 36236, 36237, 36238, 36239, 36240, 36241, 35510, 35508, 36243, 36244, 36245, 35494, 36247, 35521, 36248, 36249, 36250, 35531, 36251, 36252, 36253, 36254, 35150, 36256, 36257, 36259, 36260, 36261, 36263, 36264, 36265, 36267, 35973, 36270, 36271, 36272, 36273, 35975, 36275, 36276, 36277, 36278, 36279, 36281, 36283, 36285, 36287, 36289, 36290, 36291, 36292, 36293, 36295, 35833, 36297, 36298, 36300, 36301, 36302, 35240, 36303, 36304, 36305, 36307, 36308, 36309, 36311, 36312, 36313, 36314, 35991, 36316, 36317, 36318, 36319, 36320, 36322, 36323, 35994, 36325, 36326, 36327, 36328, 36329, 36331, 36332, 36333, 36334, 36335, 36337, 36339, 36341, 36343, 35339, 36344, 36345, 36346, 36349, 36350, 36351, 35833, 36353, 36354, 36355, 36356, 36357, 36358, 36359, 36360, 36361, 36362, 36365, 36366, 36367, 36368, 36369, 36370, 36371, 36373, 36374, 36013, 36376, 36377, 36378, 36379, 36380, 36382, 36384, 36386, 36020, 36389, 36391, 36393, 36394, 36024, 36396, 36397, 36398, 36399, 36400, 36401, 36402, 36403, 36404, 36406, 36408, 36409, 36410, 35494, 36412, 36413, 35501, 36415, 35510, 35508, 36416, 36417, 35521, 36418, 36419, 36420, 35531, 36421, 36422, 36423, 36424, 35537, 36426, 36427, 36429, 36430, 36439, 36440, 36447, 36449, 36450, 36451, 36452, 36470, 36509, 36511, 36512, 36514, 36516, 36518, 36519, 36520, 36523, 36138, 36525, 36526, 36529, 36145, 36531, 36533, 36535, 36536, 36551, 36556, 36558, 36559, 36562, 36182, 36564, 36565, 36567, 36568, 36602, 36611, 36612, 36613, 36614, 36617, 36246, 36619, 36621, 36623, 36625, 36628, 36255, 36630, 36631, 36633, 36634, 36648, 36657, 36659, 36296, 36661, 36662, 36665, 36666, 36668, 36669, 36671, 36672, 36681, 36689, 36694, 36699, 36700, 36702, 36703, 36706, 36352, 36716, 36749, 36750, 36751, 36754, 36411, 36757, 36414, 36759, 36760, 36761, 36763, 36765, 36767, 36769, 36772, 36425, 36774, 36775, 36469, 36467, 36465, 36474, 36472, 35551, 36479, 36477, 36487, 36483, 36485, 36481, 35553, 36496, 36494, 36492, 36490, 35555, 36501, 36499, 35556, 36508, 36506, 36504, 36157, 36155, 35938, 36542, 35566, 36545, 35568, 36550, 36548, 36555, 36553, 36571, 34847, 36576, 36198, 36196, 35579, 36207, 36205, 36203, 34849, 36585, 36583, 35581, 36592, 36590, 36588, 35582, 36601, 36599, 36597, 36595, 36610, 36608, 36606, 36604, 36268, 36266, 35589, 36642, 36640, 35591, 36647, 36645, 36286, 36284, 36282, 35983, 36656, 36654, 36675, 35602, 36680, 36678, 36683, 35605, 36688, 36686, 36693, 36691, 36340, 36338, 36002, 36715, 36713, 36711, 36709, 36722, 36720, 36718, 35617, 36725, 34898, 36730, 36728, 35619, 36387, 36385, 36383, 34900, 36739, 36392, 36390, 35622, 36748, 36746, 36744, 36742, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 36510, 36788, 36790, 36522, 36528, 36799, 36557, 36561, 36815, 36616, 36820, 36822, 36627, 36658, 36664, 36698, 36847, 36705, 36851, 36753, 36756, 36859, 36862, 36864, 36771, 36870, 36871, 36872, 34813, 36873, 36874, 36875, 36876, 36877, 36878, 36879, 36880, 36881, 36882, 36883, 36884, 36885, 36886, 36887, 36888, 36889, 36890, 36891, 36892, 36893, 34818, 36796, 36802, 36894, 36895, 36896, 36897, 36898, 36899, 36900, 36901, 36902, 35569, 36903, 36904, 35570, 36810, 36812, 36905, 36906, 36907, 36908, 36909, 36910, 36911, 36912, 36913, 36914, 36915, 36916, 36917, 36918, 36919, 36920, 36921, 36922, 36923, 36924, 36925, 35583, 36926, 36927, 36928, 36929, 35584, 36827, 36829, 36930, 36931, 36932, 36933, 36934, 36935, 36936, 36937, 35592, 36938, 36939, 36940, 36941, 36942, 36943, 35595, 36835, 36839, 36841, 36944, 36945, 36946, 36947, 35603, 36948, 36949, 36950, 36951, 35606, 36952, 36953, 35607, 36954, 36955, 36956, 36957, 36958, 36959, 36960, 36961, 36962, 36963, 36964, 36965, 36966, 36967, 36968, 36969, 36970, 36971, 36972, 36973, 36974, 36975, 36976, 36977, 36978, 36979, 36980, 36981, 35623, 36854, 36869, 37017, 37020, 37021, 37024, 37026, 37028, 37031, 37033, 37036, 37039, 37042, 36787, 36789, 36792, 36794, 37043, 36798, 36800, 37044, 37045, 37052, 37054, 37055, 37057, 36806, 36808, 37058, 37059, 37062, 37066, 37070, 37073, 37077, 37079, 37081, 37082, 37084, 37086, 36817, 36819, 36821, 36823, 36825, 37087, 37088, 37089, 37092, 37095, 37097, 37098, 37102, 37104, 36833, 37105, 36837, 37106, 37107, 37110, 37112, 37115, 37117, 37118, 37120, 37121, 36846, 36848, 36850, 37124, 37126, 35616, 37128, 37134, 37137, 37141, 37145, 37147, 37149, 37150, 36856, 36858, 36861, 36863, 36865, 36867, 37151, 37051, 37049, 37061, 37114, 37109, 37133, 11, 12, 13, 14, 15, 37152, 37155, 37158, 37161, 37163, 37164, 37165, 37166, 37168, 37169, 37176, 37177, 37180, 37181, 37183, 37184, 37187, 37190, 37191, 37192, 37193, 37194, 37201, 37204, 37206, 37216, 37217, 37218, 37219, 37221, 37222, 37224, 37225, 37226, 37230, 37231, 37232, 37233, 37234, 37235, 37038, 37023, 36435, 36438, 37047, 37175, 37237, 37173, 37238, 36442, 36441, 37239, 37072, 36051, 36050, 37200, 37203, 37094, 37091, 36054, 36053, 36448, 37212, 37240, 37123, 37241, 37210, 37214, 37242, 37136, 36063, 36055, 8, 9, 10, 11, 12, 13, 14, 15, 37249, 37035, 37288, 37289, 37153, 37162, 37290, 36434, 36437, 36432, 36431, 36433, 37291, 36436, 37292, 37293, 37295, 37297, 37298, 36778, 36777, 37069, 37076, 37065, 37186, 37189, 37300, 36445, 36444, 37301, 36443, 37302, 36046, 36446, 37101, 37303, 37304, 37305, 37306, 37307, 37308, 37309, 36779, 36780, 37310, 37312, 37314, 37315, 36783, 36782, 36781, 37277, 37131, 37144, 37317, 37228, 37140, 36059, 37318, 36455, 36453, 36456, 37319, 36454, 36457, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37329, 37332, 37333, 37030, 37335, 37336, 37337, 37338, 37339, 37341, 37342, 37294, 37347, 37348, 37345, 37349, 37350, 37351, 37352, 37353, 37355, 37356, 37358, 37360, 37361, 37362, 37364, 37370, 37371, 37367, 37372, 37373, 37374, 37376, 37377, 37378, 37379, 37380, 37381, 37383, 37384, 37385, 37387, 37388, 37389, 37391, 37392, 15, 37411, 37408, 37331, 37334, 37413, 37415, 37340, 37418, 37420, 37423, 37425, 37299, 37428, 37357, 37359, 37433, 37369, 37438, 37441, 37444, 37446, 37382, 37449, 37450, 37452, 37453, 10, 11, 12, 13, 14, 15, 37410, 37457, 37459, 37461, 37463, 37422, 37465, 37467, 37468, 37470, 37471, 37437, 37473, 37474, 37475, 37477, 37478, 37480, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37489, 37490, 37494, 37496, 37498, 37499, 37502, 37504, 37493, 37501, 10, 11, 12, 13, 14, 15, 37525, 37528, 37523, 37527, 37521, 37529, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37536, 37538, 37539, 37540, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37552, 37553, 37555, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37568, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37584, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};
int h_C[]= {
1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113, 115, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 137, 139, 141, 143, 145, 147, 149, 151, 153, 155, 157, 159, 161, 163, 165, 167, 169, 171, 173, 175, 177, 179, 181, 183, 185, 187, 189, 191, 193, 195, 197, 199, 201, 203, 205, 207, 209, 211, 213, 215, 217, 219, 221, 223, 225, 227, 229, 231, 233, 235, 237, 239, 241, 243, 245, 247, 249, 251, 253, 255, 257, 259, 261, 263, 265, 267, 269, 271, 273, 275, 277, 279, 281, 283, 285, 287, 289, 291, 293, 295, 297, 299, 301, 303, 305, 307, 309, 311, 313, 315, 317, 319, 321, 323, 325, 327, 329, 331, 333, 335, 337, 339, 341, 343, 345, 347, 349, 351, 353, 355, 357, 359, 361, 363, 365, 367, 369, 371, 373, 375, 377, 379, 381, 383, 385, 387, 389, 391, 393, 395, 397, 399, 401, 403, 405, 407, 409, 411, 413, 415, 417, 419, 421, 423, 425, 427, 429, 431, 433, 435, 437, 439, 441, 443, 445, 447, 449, 451, 453, 455, 457, 459, 461, 463, 465, 467, 469, 471, 473, 475, 477, 479, 481, 483, 485, 487, 489, 491, 493, 495, 497, 499, 501, 503, 505, 507, 509, 511, 513, 515, 517, 519, 521, 523, 525, 527, 529, 531, 533, 535, 537, 539, 541, 543, 545, 547, 549, 551, 553, 555, 557, 559, 561, 563, 565, 567, 569, 571, 573, 575, 577, 579, 581, 583, 585, 587, 589, 591, 593, 595, 597, 599, 601, 603, 605, 607, 609, 611, 613, 615, 617, 619, 621, 623, 625, 627, 629, 631, 633, 635, 637, 639, 641, 643, 645, 647, 649, 651, 653, 655, 657, 659, 661, 663, 665, 667, 669, 671, 673, 675, 677, 679, 681, 683, 685, 687, 689, 691, 693, 695, 697, 699, 701, 703, 705, 707, 709, 711, 713, 715, 717, 719, 721, 723, 725, 727, 729, 731, 733, 735, 737, 739, 741, 743, 745, 747, 749, 751, 753, 755, 757, 759, 761, 763, 765, 767, 769, 771, 773, 775, 777, 779, 781, 783, 785, 787, 789, 791, 793, 795, 797, 799, 801, 803, 805, 807, 809, 811, 813, 815, 817, 819, 821, 823, 825, 827, 829, 831, 833, 835, 837, 839, 841, 843, 845, 847, 849, 851, 853, 855, 857, 859, 861, 863, 865, 867, 869, 871, 873, 875, 877, 879, 881, 883, 885, 887, 889, 891, 893, 895, 897, 899, 901, 903, 905, 907, 909, 911, 913, 915, 917, 919, 921, 923, 925, 927, 929, 931, 933, 935, 937, 939, 941, 943, 945, 947, 949, 951, 953, 955, 957, 959, 961, 963, 965, 967, 969, 971, 973, 975, 977, 979, 981, 983, 985, 987, 989, 991, 993, 995, 997, 999, 1001, 1003, 1005, 1007, 1009, 1011, 1013, 1015, 1017, 1019, 1021, 1023, 1025, 1027, 1029, 1031, 1033, 1035, 1037, 1039, 1041, 1043, 1045, 1047, 1049, 1051, 1053, 1055, 1057, 1059, 1061, 1063, 1065, 1067, 1069, 1071, 1073, 1075, 1077, 1079, 1081, 1083, 1085, 1087, 1089, 1091, 1093, 1095, 1097, 1099, 1101, 1103, 1105, 1107, 1109, 1111, 1113, 1115, 1117, 1119, 1121, 1123, 1125, 1127, 1129, 1131, 1133, 1135, 1137, 1139, 1141, 1143, 1145, 1147, 1149, 1151, 1153, 1155, 1157, 1159, 1161, 1163, 1165, 1167, 1169, 1171, 1173, 1175, 1177, 1179, 1181, 1183, 1185, 1187, 1189, 1191, 1193, 1195, 1197, 1199, 1201, 1203, 1205, 1207, 1209, 1211, 1213, 1215, 1217, 1219, 1221, 1223, 1225, 1227, 1229, 1231, 1233, 1235, 1237, 1239, 1241, 1243, 1245, 1247, 1249, 1251, 1253, 1255, 1257, 1259, 1261, 1263, 1265, 1267, 1269, 1271, 1273, 1275, 1277, 1279, 1281, 1283, 1285, 1287, 1289, 1291, 1293, 1295, 1297, 1299, 1301, 1303, 1305, 1307, 1309, 1311, 1313, 1315, 1317, 1319, 1321, 1323, 1325, 1327, 1329, 1331, 1333, 1335, 1337, 1339, 1341, 1343, 1345, 1347, 1349, 1351, 1353, 1355, 1357, 1359, 1361, 1363, 1365, 1367, 1369, 1371, 1373, 1375, 1377, 1379, 1381, 1383, 1385, 1387, 1389, 1391, 1393, 1395, 1397, 1399, 1401, 1403, 1405, 1407, 1409, 1411, 1413, 1415, 1417, 1419, 1421, 1423, 1425, 1427, 1429, 1431, 1433, 1435, 1437, 1439, 1441, 1443, 1445, 1447, 1449, 1451, 1453, 1455, 1457, 1459, 1461, 1463, 1465, 1467, 1469, 1471, 1473, 1475, 1477, 1479, 1481, 1483, 1485, 1487, 1489, 1491, 1493, 1495, 1497, 1499, 1501, 1503, 1505, 1507, 1509, 1511, 1513, 1515, 1517, 1519, 1521, 1523, 1525, 1527, 1529, 1531, 1533, 1535, 1537, 1539, 1541, 1543, 1545, 1547, 1549, 1551, 1553, 1555, 1557, 1559, 1561, 1563, 1565, 1567, 1569, 1571, 1573, 1575, 1577, 1579, 1581, 1583, 1585, 1587, 1589, 1591, 1593, 1595, 1597, 1599, 1601, 1603, 1605, 1607, 1609, 1611, 1613, 1615, 1617, 1619, 1621, 1623, 1625, 1627, 1629, 1631, 1633, 1635, 1637, 1639, 1641, 1643, 1645, 1647, 1649, 1651, 1653, 1655, 1657, 1659, 1661, 1663, 1665, 1667, 1669, 1671, 1673, 1675, 1677, 1679, 1681, 1683, 1685, 1687, 1689, 1691, 1693, 1695, 1697, 1699, 1701, 1703, 1705, 1707, 1709, 1711, 1713, 1715, 1717, 1719, 1721, 1723, 1725, 1727, 1729, 1731, 1733, 1735, 1737, 1739, 1741, 1743, 1745, 1747, 1749, 1751, 1753, 1755, 1757, 1759, 1761, 1763, 1765, 1767, 1769, 1771, 1773, 1775, 1777, 1779, 1781, 1783, 1785, 1787, 1789, 1791, 1793, 1795, 1797, 1799, 1801, 1803, 1805, 1807, 1809, 1811, 1813, 1815, 1817, 1819, 1821, 1823, 1825, 1827, 1829, 1831, 1833, 1835, 1837, 1839, 1841, 1843, 1845, 1847, 1849, 1851, 1853, 1855, 1857, 1859, 1861, 1863, 1865, 1867, 1869, 1871, 1873, 1875, 1877, 1879, 1881, 1883, 1885, 1887, 1889, 1891, 1893, 1895, 1897, 1899, 1901, 1903, 1905, 1907, 1909, 1911, 1913, 1915, 1917, 1919, 1921, 1923, 1925, 1927, 1929, 1931, 1933, 1935, 1937, 1939, 1941, 1943, 1945, 1947, 1949, 1951, 1953, 1955, 1957, 1959, 1961, 1963, 1965, 1967, 1969, 1971, 1973, 1975, 1977, 1979, 1981, 1983, 1985, 1987, 1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003, 2005, 2007, 2009, 2011, 2014, 2016, 2018, 2020, 2022, 2024, 2026, 2028, 2030, 2032, 2034, 2036, 2038, 2040, 2043, 2045, 2047, 2049, 2051, 2053, 2055, 2057, 2059, 2061, 2063, 2065, 2067, 2069, 2071, 2073, 2075, 2077, 2079, 2081, 2083, 2085, 2087, 2089, 2091, 2093, 2095, 2097, 2099, 2101, 2103, 2105, 2107, 2109, 2111, 2113, 2115, 2117, 2119, 2121, 2123, 2125, 2127, 2129, 2131, 2133, 2135, 2137, 2139, 2141, 2143, 2145, 2147, 2149, 2151, 2153, 2155, 2157, 2159, 2161, 2163, 2165, 2167, 2169, 2171, 2173, 2175, 2177, 2179, 2181, 2183, 2185, 2187, 2189, 2191, 2193, 2195, 2197, 2199, 2201, 2203, 2205, 2207, 2209, 2211, 2213, 2215, 2217, 2219, 2221, 2223, 2225, 2227, 2229, 2231, 2233, 2235, 2237, 2239, 2241, 2243, 2245, 2247, 2249, 2251, 2253, 2255, 2257, 2259, 2261, 2263, 2265, 2267, 2269, 2272, 2274, 2276, 2278, 2281, 2283, 2285, 2287, 2289, 2291, 2293, 2295, 2297, 2299, 2301, 2303, 2305, 2307, 2309, 2311, 2313, 2315, 2317, 2319, 2321, 2323, 2325, 2327, 2329, 2331, 2333, 2335, 2337, 2339, 2341, 2343, 2345, 2347, 2349, 2351, 2353, 2355, 2357, 2359, 2361, 2363, 2365, 2367, 2369, 2371, 2373, 2375, 2377, 2379, 2381, 2383, 2385, 2387, 2389, 2391, 2393, 2395, 2397, 2399, 2401, 2403, 2405, 2407, 2409, 2411, 2413, 2415, 2417, 2419, 2421, 2423, 2425, 2427, 2429, 2431, 2433, 2435, 2437, 2439, 2441, 2443, 2445, 2447, 2449, 2451, 2453, 2455, 2457, 2459, 2461, 2463, 2465, 2467, 2469, 2471, 2473, 2475, 2477, 2479, 2481, 2483, 2485, 2487, 2489, 2491, 2493, 2495, 2497, 2499, 2501, 2503, 2505, 2507, 2509, 2511, 2513, 2515, 2517, 2519, 2521, 2523, 2525, 2527, 2529, 2531, 2533, 2535, 2537, 2539, 2541, 2543, 2545, 2547, 2549, 2551, 2553, 2555, 2557, 2559, 2561, 2563, 2565, 2567, 2569, 2571, 2573, 2575, 2577, 2579, 2581, 2583, 2585, 2587, 2589, 2591, 2593, 2595, 2597, 2599, 2601, 2603, 2605, 2607, 2609, 2611, 2613, 2615, 2617, 2619, 2621, 2623, 2625, 2627, 2629, 2631, 2633, 2635, 2637, 2639, 2641, 2643, 2645, 2647, 2649, 2651, 2653, 2655, 2657, 2659, 2661, 2663, 2665, 2667, 2669, 2671, 2673, 2675, 2677, 2679, 2681, 2683, 2685, 2687, 2689, 2691, 2693, 2695, 2697, 2699, 2701, 2703, 2705, 2707, 2709, 2711, 2713, 2715, 2717, 2719, 2721, 2723, 2725, 2727, 2729, 2731, 2733, 2735, 2737, 2739, 2741, 2743, 2745, 2747, 2749, 2751, 2753, 2755, 2757, 2759, 2761, 2763, 2765, 2767, 2769, 2771, 2773, 2775, 2777, 2779, 2781, 2783, 2785, 2787, 2789, 2791, 2793, 2795, 2797, 2799, 2801, 2803, 2805, 2807, 2809, 2811, 2813, 2815, 2817, 2819, 2821, 2823, 2825, 2827, 2829, 2831, 2833, 2835, 2837, 2839, 2841, 2843, 2845, 2847, 2849, 2851, 2853, 2855, 2857, 2859, 2861, 2863, 2865, 2867, 2869, 2871, 2873, 2875, 2877, 2879, 2881, 2883, 2885, 2887, 2889, 2891, 2893, 2895, 2897, 2899, 2901, 2903, 2905, 2907, 2909, 2911, 2913, 2915, 2917, 2919, 2921, 2923, 2925, 2927, 2929, 2931, 2933, 2935, 2937, 2939, 2941, 2943, 2945, 2947, 2949, 2951, 2953, 2955, 2957, 2959, 2961, 2963, 2965, 2967, 2969, 2971, 2973, 2975, 2977, 2979, 2981, 2983, 2985, 2987, 2989, 2991, 2993, 2995, 2997, 2999, 3001, 3003, 3005, 3007, 3009, 3011, 3013, 3015, 3017, 3019, 3021, 3023, 3025, 3027, 3029, 3031, 3033, 3035, 3037, 3039, 3041, 3043, 3045, 3047, 3049, 3051, 3053, 3055, 3057, 3059, 3061, 3063, 3065, 3067, 3069, 3071, 3073, 3075, 3077, 3079, 3081, 3083, 3085, 3087, 3089, 3091, 3093, 3095, 3097, 3099, 3101, 3103, 3105, 3107, 3109, 3111, 3113, 3115, 3117, 3119, 3121, 3123, 3125, 3127, 3129, 3131, 3133, 3135, 3137, 3139, 3141, 3143, 3145, 3147, 3149, 3151, 3153, 3155, 3157, 3159, 3161, 3163, 3165, 3167, 3169, 3171, 3173, 3175, 3177, 3179, 3181, 3183, 3185, 3187, 3189, 3191, 3193, 3195, 3197, 3199, 3201, 3203, 3205, 3207, 3209, 3211, 3213, 3215, 3217, 3219, 3221, 3223, 3225, 3227, 3229, 3231, 3233, 3235, 3237, 3239, 3241, 3243, 3245, 3247, 3249, 3251, 3253, 3255, 3257, 3259, 3261, 3263, 3265, 3267, 3269, 3271, 3273, 3275, 3277, 3279, 3281, 3283, 3285, 3287, 3289, 3291, 3293, 3295, 3297, 3299, 3301, 3303, 3305, 3307, 3309, 3311, 3313, 3315, 3317, 3319, 3321, 3323, 3325, 3327, 3329, 3331, 3333, 3335, 3337, 3339, 3341, 3343, 3345, 3347, 3349, 3351, 3353, 3355, 3357, 3359, 3361, 3363, 3365, 3367, 3369, 3371, 3373, 3375, 3377, 3379, 3381, 3383, 3385, 3387, 3389, 3391, 3393, 3395, 3397, 3399, 3401, 3403, 3405, 3407, 3409, 3411, 3413, 3415, 3417, 3419, 3421, 3423, 3425, 3427, 3429, 3431, 3433, 3435, 3437, 3439, 3441, 3443, 3445, 3447, 3449, 3451, 3453, 3455, 3457, 3459, 3461, 3463, 3465, 3467, 3469, 3471, 3473, 3475, 3477, 3479, 3481, 3483, 3485, 3487, 3489, 3491, 3493, 3495, 3497, 3499, 3501, 3503, 3505, 3507, 3509, 3511, 3513, 3515, 3517, 3519, 3521, 3523, 3525, 3527, 3529, 3531, 3533, 3535, 3537, 3539, 3541, 3543, 3545, 3547, 3549, 3551, 3553, 3555, 3557, 3559, 3561, 3563, 3565, 3567, 3569, 3571, 3573, 3575, 3577, 3579, 3581, 3583, 3585, 3587, 3589, 3591, 3593, 3595, 3597, 3599, 3601, 3603, 3605, 3607, 3609, 3611, 3613, 3615, 3617, 3619, 3621, 3623, 3625, 3627, 3629, 3631, 3633, 3635, 3637, 3639, 3641, 3643, 3645, 3647, 3649, 3651, 3653, 3655, 3657, 3659, 3661, 3663, 3665, 3667, 3669, 3671, 3673, 3675, 3677, 3679, 3681, 3683, 3685, 3687, 3689, 3691, 3693, 3695, 3697, 3699, 3701, 3703, 3705, 3707, 3709, 3711, 3713, 3715, 3717, 3719, 3721, 3723, 3725, 3727, 3729, 3731, 3733, 3735, 3737, 3739, 3741, 3743, 3745, 3747, 3749, 3751, 3753, 3755, 3757, 3759, 3761, 3763, 3765, 3767, 3769, 3771, 3773, 3775, 3777, 3779, 3781, 3783, 3785, 3787, 3789, 3791, 3793, 3795, 3797, 3799, 3801, 3803, 3805, 3807, 3809, 3811, 3813, 3815, 3817, 3819, 3821, 3823, 3825, 3827, 3829, 3831, 3833, 3835, 3837, 3839, 3841, 3843, 3845, 3847, 3849, 3851, 3853, 3855, 3858, 3860, 3862, 3864, 3866, 3868, 3870, 3872, 3874, 3876, 3878, 3880, 3882, 3884, 3886, 3888, 3890, 3892, 3894, 3896, 3898, 3900, 3902, 3904, 3906, 3908, 3910, 3912, 3914, 3916, 3918, 3920, 3922, 3924, 3926, 3928, 3930, 3932, 3934, 3936, 3938, 3940, 3942, 3944, 3946, 3948, 3950, 3952, 3954, 3956, 3958, 3960, 3962, 3964, 3966, 3968, 3970, 3972, 3974, 3976, 3978, 3980, 3982, 3984, 3986, 3988, 3990, 3992, 3994, 3996, 3998, 4000, 4002, 4004, 4006, 4008, 4010, 4012, 4014, 4016, 4018, 4020, 4022, 4024, 4026, 4028, 4030, 4032, 4034, 4036, 4038, 4040, 4042, 4044, 4046, 4048, 4050, 4052, 4054, 4056, 4058, 4060, 4062, 4064, 4066, 4068, 4070, 4072, 4074, 4076, 4078, 4080, 4082, 4084, 4086, 4088, 4090, 4092, 4094, 4096, 4098, 4100, 4102, 4104, 4106, 4108, 4110, 4112, 4114, 4116, 4118, 4120, 4122, 4124, 4126, 4128, 4130, 4132, 4134, 4136, 4138, 4140, 4142, 4144, 4146, 4148, 4150, 4152, 4154, 4156, 4158, 4160, 4162, 4164, 4166, 4168, 4170, 4172, 4174, 4176, 4178, 4180, 4182, 4184, 4186, 4188, 4190, 4192, 4194, 4196, 4198, 4200, 4202, 4204, 4206, 4208, 4210, 4212, 4214, 4216, 4218, 4220, 4222, 4224, 4226, 4228, 4230, 4232, 4234, 4236, 4238, 4240, 4242, 4244, 4246, 4248, 4251, 4253, 4255, 4257, 4259, 4261, 4263, 4265, 4267, 4269, 4271, 4273, 4275, 4277, 4279, 4281, 4283, 4285, 4287, 4289, 4291, 4293, 4296, 4298, 4302, 4304, 4306, 4308, 4310, 4312, 4314, 4316, 4319, 4321, 4324, 4326, 4332, 4334, 4336, 4338, 4341, 4343, 4345, 4347, 4351, 4353, 4355, 4357, 4359, 4361, 4363, 4365, 4367, 4369, 4371, 4373, 4375, 4377, 4379, 4381, 4383, 4385, 4387, 4389, 4391, 4393, 4395, 4397, 4400, 4402, 4404, 4406, 4408, 4410, 4413, 4415, 4417, 4419, 4422, 4424, 4427, 4429, 4434, 4436, 4438, 4440, 4443, 4445, 4448, 4450, 4455, 4457, 4459, 4461, 4464, 4466, 4468, 4470, 4474, 4476, 4478, 4480, 4482, 4484, 4487, 4489, 4491, 4493, 4495, 4497, 4499, 4501, 4504, 4506, 4509, 4511, 4514, 4516, 4518, 4520, 4522, 4524, 4526, 4528, 4531, 4533, 4536, 4538, 4543, 4545, 4547, 4549, 4552, 4554, 4557, 4559, 4572, 4574, 4576, 4578, 4580, 4582, 4584, 4586, 4588, 4590, 4592, 4594, 4596, 4598, 4600, 4602, 4604, 4606, 4608, 4610, 4612, 4614, 4616, 4618, 4620, 4622, 4624, 4626, 4628, 4630, 4632, 4634, 4636, 4638, 4640, 4642, 4644, 4646, 4648, 4650, 4652, 4654, 4656, 4658, 4661, 4663, 4665, 4667, 4669, 4671, 4673, 4675, 4677, 4679, 4681, 4683, 4685, 4687, 4689, 4691, 4693, 4695, 4697, 4699, 4701, 4703, 4705, 4707, 4709, 4711, 4714, 4716, 4718, 4720, 4723, 4725, 4727, 4729, 4733, 4735, 4738, 4740, 4743, 4745, 4748, 4750, 4753, 4755, 4758, 4760, 4763, 4765, 4767, 4769, 4772, 4774, 4777, 4779, 4784, 4786, 4788, 4790, 4793, 4795, 4798, 4800, 4805, 4807, 4809, 4811, 4813, 4815, 4817, 4819, 4821, 4823, 4825, 4827, 4829, 4831, 4833, 4835, 4837, 4839, 4841, 4843, 4845, 4847, 4849, 4851, 4853, 4855, 4857, 4859, 4861, 4863, 4865, 4867, 4869, 4871, 4873, 4875, 4877, 4879, 4881, 4883, 4885, 4887, 4889, 4891, 4893, 4895, 4897, 4899, 4901, 4903, 4905, 4907, 4909, 4911, 4913, 4915, 4917, 4919, 4921, 4923, 4925, 4927, 4929, 4931, 4933, 4935, 4937, 4939, 4941, 4943, 4945, 4947, 4949, 4951, 4953, 4955, 4957, 4959, 4961, 4963, 4965, 4967, 4969, 4971, 4973, 4975, 4977, 4979, 4981, 4983, 4985, 4987, 4989, 4991, 4993, 4995, 4997, 4999, 5001, 5003, 5005, 5007, 5009, 5011, 5013, 5015, 5017, 5019, 5021, 5023, 5025, 5027, 5029, 5031, 5033, 5035, 5037, 5039, 5041, 5043, 5045, 5047, 5049, 5051, 5053, 5055, 5057, 5059, 5061, 5063, 5065, 5067, 5069, 5071, 5073, 5075, 5077, 5079, 5081, 5083, 5085, 5087, 5089, 5091, 5093, 5095, 5097, 5099, 5101, 5103, 5105, 5107, 5109, 5111, 5113, 5115, 5117, 5119, 5121, 5123, 5125, 5127, 5129, 5131, 5133, 5135, 5137, 5139, 5141, 5143, 5145, 5147, 5149, 5151, 5153, 5155, 5157, 5159, 5161, 5163, 5165, 5167, 5169, 5171, 5173, 5175, 5177, 5179, 5181, 5183, 5185, 5187, 5189, 5191, 5193, 5195, 5197, 5199, 5201, 5203, 5205, 5207, 5209, 5211, 5213, 5215, 5217, 5219, 5221, 5223, 5225, 5227, 5229, 5231, 5233, 5235, 5237, 5239, 5241, 5243, 5245, 5247, 5249, 5251, 5253, 5255, 5257, 5259, 5261, 5263, 5265, 5267, 5269, 5271, 5273, 5275, 5277, 5279, 5281, 5283, 5285, 5287, 5289, 5291, 5293, 5295, 5297, 5299, 5301, 5303, 5305, 5307, 5309, 5311, 5313, 5315, 5317, 5319, 5321, 5323, 5325, 5327, 5329, 5331, 5333, 5335, 5337, 5339, 5341, 5343, 5345, 5347, 5349, 5351, 5353, 5355, 5357, 5359, 5361, 5363, 5365, 5367, 5369, 5371, 5373, 5375, 5377, 5379, 5381, 5383, 5385, 5387, 5389, 5391, 5393, 5395, 5397, 5399, 5401, 5403, 5405, 5407, 5409, 5411, 5413, 5415, 5417, 5419, 5421, 5423, 5425, 5427, 5429, 5431, 5433, 5435, 5437, 5439, 5441, 5443, 5445, 5447, 5449, 5451, 5453, 5455, 5457, 5459, 5461, 5463, 5465, 5467, 5469, 5471, 5473, 5475, 5477, 5479, 5481, 5483, 5485, 5487, 5489, 5491, 5493, 5495, 5497, 5499, 5501, 5503, 5505, 5507, 5509, 5511, 5513, 5515, 5517, 5519, 5521, 5523, 5525, 5527, 5529, 5531, 5533, 5535, 5537, 5539, 5541, 5543, 5545, 5547, 5549, 5551, 5553, 5555, 5557, 5559, 5561, 5563, 5565, 5567, 5569, 5571, 5573, 5575, 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35594, 35227, 35361, 35597, 35232, 35600, 35241, 35249, 14145, 34444, 35276, 14157, 34473, 35300, 35317, 34517, 35331, 35335, 35333, 35609, 35611, 35347, 35346, 35613, 35361, 35615, 35383, 35382, 35402, 35401, 14227, 34632, 35421, 35420, 35426, 35432, 34671, 14243, 34673, 34681, 35449, 14252, 34696, 35481, 35484, 35498, 35505, 35541, 35542, 35557, 14349, 14350, 35558, 35559, 35560, 35561, 14360, 14361, 35562, 35575, 35576, 35585, 35586, 14417, 14419, 14420, 35587, 14424, 14426, 35598, 14450, 14452, 14503, 35624, 35625, 35626, 14511, 14513, 14514, 35627, 14518, 35053, 35064, 35070, 35085, 35096, 34316, 35338, 35355, 35493, 34752, 35507, 34766, 35520, 35530, 34796, 35648, 35650, 35651, 35653, 35654, 35656, 35657, 13795, 35658, 35660, 35661, 35663, 13801, 13802, 35664, 35666, 35667, 35669, 35670, 35672, 35673, 35675, 35676, 35678, 35679, 35681, 13817, 35682, 35684, 35685, 35687, 35688, 35690, 35691, 35693, 13828, 35694, 35696, 35697, 35699, 13834, 13835, 35700, 35702, 35703, 35705, 35706, 35708, 35709, 13844, 35711, 35713, 35712, 35714, 35717, 35716, 35905, 35904, 35719, 13871, 35720, 35721, 13877, 35723, 35722, 35725, 13884, 35726, 35727, 35730, 35729, 35731, 13899, 35733, 35732, 35821, 13905, 35823, 13907, 13908, 13909, 35804, 35806, 13915, 35794, 35796, 13920, 35734, 35736, 35737, 35739, 35740, 13927, 35741, 35743, 35744, 35746, 35747, 13934, 35826, 35828, 35827, 35834, 13945, 35835, 35748, 13951, 35750, 35749, 35785, 13958, 35787, 35786, 35858, 35860, 13967, 35873, 13970, 35875, 13972, 35877, 35879, 13976, 35867, 13979, 35869, 13981, 35871, 13983, 13985, 35861, 35863, 35864, 35866, 13991, 13992, 35849, 35851, 35852, 35854, 35855, 35857, 14000, 14001, 35836, 35838, 35839, 35841, 35842, 35844, 35845, 35847, 35848, 14012, 35880, 35882, 35883, 35885, 35886, 35888, 35889, 35891, 35892, 14023, 35905, 35904, 35897, 14034, 35898, 35906, 35909, 35908, 35910, 35913, 35912, 35752, 14055, 35753, 35754, 14061, 35756, 35755, 35893, 14067, 35895, 35894, 35757, 14073, 35759, 14075, 14077, 35761, 35763, 35764, 35766, 14084, 35767, 35769, 35770, 35772, 35773, 14091, 35774, 14094, 35776, 14096, 35821, 14098, 14099, 14100, 35778, 35780, 35781, 35783, 35784, 14108, 35834, 14112, 35835, 35785, 14118, 35787, 35786, 35826, 35828, 35827, 35788, 14132, 35790, 35789, 35791, 14138, 35793, 35792, 35794, 35796, 14146, 35797, 35799, 35800, 35802, 35803, 14153, 35804, 35806, 14158, 35807, 35809, 35810, 35812, 35813, 14165, 35814, 35816, 35817, 35819, 35820, 14172, 35821, 14175, 35823, 14177, 14178, 14179, 35826, 35828, 35827, 35829, 14190, 14191, 35831, 35830, 35834, 14199, 35835, 35836, 35838, 35839, 35841, 35842, 35844, 35845, 35847, 35848, 14213, 14214, 35849, 35851, 35852, 35854, 35855, 35857, 14222, 14223, 35858, 35860, 14228, 35861, 35863, 35864, 35866, 14234, 14235, 35867, 14238, 35869, 14240, 35871, 14242, 14244, 35873, 14247, 35875, 14249, 35877, 35879, 14253, 35880, 35882, 35883, 35885, 35886, 35888, 35889, 35891, 35892, 14264, 35893, 14267, 35895, 35894, 35897, 14274, 35898, 35900, 14281, 35901, 35905, 35904, 35906, 35909, 35908, 35910, 35913, 35912, 35915, 14309, 35916, 35917, 14315, 35919, 35918, 14347, 36034, 14352, 14354, 14356, 14358, 36040, 14363, 35945, 35947, 14382, 14384, 14413, 14415, 36048, 14422, 35986, 14446, 35988, 36003, 36006, 36008, 14505, 14507, 14509, 36061, 14516, 10, 11, 12, 13, 14, 15, 13788, 13789, 13790, 13791, 13792, 13793, 13794, 13797, 13798, 13799, 13800, 36092, 13804, 13805, 13806, 13807, 13808, 13809, 13810, 13811, 13812, 13813, 13814, 13815, 36105, 13819, 13820, 13821, 13822, 13823, 13824, 13825, 13826, 36114, 13830, 13831, 13832, 13833, 36120, 13837, 13838, 13839, 13840, 13841, 13842, 13843, 13846, 36064, 13848, 13849, 36065, 13854, 13855, 13856, 36075, 36074, 13864, 13865, 13869, 36066, 13872, 13876, 13878, 13879, 13882, 36067, 13885, 36068, 13890, 13891, 13892, 13898, 13900, 13901, 13904, 13906, 36159, 13912, 13913, 36162, 13917, 13918, 36165, 13922, 13923, 13924, 13925, 13926, 13929, 13930, 13931, 13932, 13933, 13936, 36070, 13938, 13939, 13943, 36071, 13946, 13950, 13952, 13953, 13957, 13959, 13960, 13964, 13965, 36194, 13969, 13971, 13973, 13974, 36201, 13978, 13980, 13982, 36208, 13987, 13988, 13989, 13990, 36214, 13994, 13995, 13996, 13997, 13998, 13999, 36222, 14003, 14004, 14005, 14006, 14007, 14008, 14009, 14010, 14011, 14014, 14015, 14016, 14017, 14018, 14019, 14020, 14021, 14022, 36075, 36074, 14027, 14028, 14032, 36072, 14035, 36076, 14040, 14041, 14042, 36077, 14046, 14047, 14048, 14053, 36069, 14056, 14060, 14062, 14063, 14066, 14068, 14069, 14072, 14074, 36269, 14079, 14080, 14081, 14082, 36274, 14086, 14087, 14088, 14089, 14090, 14093, 14095, 14097, 36288, 14103, 14104, 14105, 14106, 14107, 14110, 36071, 14113, 14117, 14119, 14120, 14124, 36070, 14126, 14127, 14131, 14133, 14134, 14137, 14139, 14140, 14143, 14144, 36315, 14148, 14149, 14150, 14151, 14152, 14155, 14156, 36324, 14160, 14161, 14162, 14163, 14164, 14167, 14168, 14169, 14170, 14171, 14174, 14176, 36342, 14182, 36070, 14184, 14185, 14189, 14192, 14193, 14197, 36071, 14200, 14204, 14205, 14206, 14207, 14208, 14209, 14210, 14211, 14212, 14216, 14217, 14218, 14219, 14220, 14221, 36372, 14225, 14226, 36375, 14230, 14231, 14232, 14233, 36381, 14237, 14239, 14241, 36388, 14246, 14248, 14250, 14251, 36395, 14255, 14256, 14257, 14258, 14259, 14260, 14261, 14262, 14263, 14266, 14268, 14269, 14272, 36072, 14275, 14279, 36073, 14282, 36075, 36074, 14288, 14289, 36076, 14294, 14295, 14296, 36077, 14300, 14301, 14302, 14307, 36078, 14310, 14314, 14316, 14317, 14378, 14380, 14444, 14448, 14470, 14472, 14474, 36086, 36128, 13847, 36513, 13853, 36517, 13862, 13863, 36521, 13870, 36524, 36141, 36527, 13883, 36530, 13889, 36534, 36151, 36537, 36171, 36177, 13937, 36560, 13944, 36563, 36185, 36566, 36189, 36569, 36232, 36242, 14025, 14026, 36615, 14033, 36618, 14039, 36622, 14045, 36626, 14054, 36629, 36258, 36632, 36262, 36635, 36280, 36294, 14111, 36660, 36299, 36663, 14125, 36667, 36306, 36670, 36310, 36673, 36321, 36330, 36336, 14183, 36701, 36347, 36704, 14198, 36707, 36363, 36405, 36407, 36752, 14273, 36755, 14280, 36758, 14286, 14287, 36762, 14293, 36766, 14299, 36770, 14308, 36773, 36428, 36776, 36468, 36466, 36464, 36473, 36471, 36475, 36478, 36476, 36486, 36482, 36484, 36480, 36488, 36495, 36493, 36491, 36489, 36497, 36500, 36498, 36502, 36507, 36505, 36503, 36539, 36538, 36540, 36541, 36543, 36544, 36546, 36549, 36547, 36554, 36552, 36570, 36572, 36575, 36574, 36573, 36577, 36580, 36579, 36578, 36581, 36584, 36582, 36586, 36591, 36589, 36587, 36593, 36600, 36598, 36596, 36594, 36609, 36607, 36605, 36603, 36637, 36636, 36638, 36641, 36639, 36643, 36646, 36644, 36651, 36650, 36649, 36652, 36655, 36653, 36674, 36676, 36679, 36677, 36682, 36684, 36687, 36685, 36692, 36690, 36696, 36695, 36697, 36714, 36712, 36710, 36708, 36721, 36719, 36717, 36723, 36724, 36726, 36729, 36727, 36731, 36734, 36733, 36732, 36735, 36738, 36737, 36736, 36740, 36747, 36745, 36743, 36741, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 36786, 36515, 36791, 36793, 36797, 36532, 36805, 36807, 36816, 36818, 36620, 36624, 36824, 36832, 36836, 36845, 36348, 36849, 36364, 36855, 36857, 36860, 36764, 36768, 36866, 14320, 14321, 14322, 36784, 14324, 14325, 14326, 14327, 14328, 14329, 14330, 14331, 14332, 14333, 14334, 14335, 14336, 14337, 14338, 14339, 14340, 14341, 14342, 14343, 14344, 36785, 36795, 36801, 14364, 14365, 14366, 14367, 14368, 14369, 14370, 14371, 14372, 36803, 14374, 14375, 36804, 36809, 36811, 14385, 14386, 14387, 14388, 14389, 14390, 14391, 14392, 14393, 14394, 14395, 14396, 14397, 14398, 14399, 14400, 14401, 14402, 14403, 14404, 14405, 36813, 14407, 14408, 14409, 14410, 36814, 36826, 36828, 14427, 14428, 14429, 14430, 14431, 14432, 14433, 14434, 36830, 14436, 14437, 14438, 14439, 14440, 14441, 36831, 36834, 36838, 36840, 14453, 14454, 14455, 14456, 36842, 14458, 14459, 14460, 14461, 36843, 14463, 14464, 36844, 14466, 14467, 14468, 14475, 14476, 14477, 14478, 14480, 14481, 14482, 14483, 14484, 14485, 14486, 14487, 14488, 14489, 14490, 14491, 14492, 14493, 14494, 14495, 14496, 14497, 14498, 14499, 14500, 36852, 36853, 36868, 37018, 14323, 37022, 37025, 37027, 37029, 37032, 37034, 37037, 37040, 14345, 36992, 36993, 36994, 36995, 14355, 36996, 36997, 14362, 37046, 37053, 14373, 37056, 14376, 36998, 36999, 14381, 14383, 37063, 37067, 37071, 37074, 37078, 37080, 14406, 37083, 37085, 14411, 37000, 37001, 37002, 37003, 37004, 14423, 14425, 37090, 37093, 37096, 14435, 37099, 37103, 14442, 37005, 14445, 37006, 14449, 14451, 37111, 14457, 37116, 14462, 37119, 14465, 37122, 37007, 37008, 37009, 37125, 37127, 37010, 37129, 37135, 37138, 37142, 37146, 37148, 14501, 14502, 37011, 37012, 37013, 37014, 37015, 37016, 14517, 37050, 37048, 37060, 37113, 37108, 37132, 11, 12, 13, 14, 15, 37019, 37156, 37159, 37041, 14346, 14348, 14351, 14353, 14357, 14359, 14377, 14379, 37064, 37068, 37075, 37185, 37188, 14412, 14414, 14416, 14418, 14421, 37100, 14443, 14447, 14469, 14471, 14473, 37220, 14479, 37130, 37139, 37143, 37227, 14504, 14506, 14508, 14510, 14512, 14515, 37160, 37154, 37167, 37170, 37171, 37174, 14535, 37172, 14537, 37179, 37178, 14546, 37182, 37196, 37195, 37199, 37202, 37198, 37197, 37208, 37207, 37205, 37211, 14567, 37215, 14569, 37209, 37213, 14578, 37223, 37236, 37229, 8, 9, 10, 11, 12, 13, 14, 15, 37157, 37250, 14520, 14521, 37248, 37251, 14525, 37255, 37257, 37253, 37252, 37254, 14531, 37256, 14533, 14534, 14536, 14538, 14539, 37259, 37258, 37261, 37262, 37260, 37263, 37264, 14548, 37268, 37266, 14551, 37265, 14553, 37267, 37269, 37270, 14557, 14558, 14559, 14560, 14561, 14562, 14563, 37271, 37272, 14566, 14568, 14570, 14571, 37275, 37274, 37273, 37276, 37278, 37280, 14579, 37281, 37279, 37285, 14583, 37284, 37282, 37286, 14587, 37283, 37287, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 14519, 14522, 14523, 37328, 14526, 14527, 14528, 14529, 14530, 14532, 37343, 37344, 14540, 14541, 37346, 14542, 14543, 14544, 14545, 14547, 14549, 14550, 14552, 14554, 14555, 14556, 37365, 14564, 14565, 37368, 37311, 37313, 37375, 14572, 14573, 14574, 14575, 14576, 14577, 14580, 14581, 14582, 14584, 14585, 14586, 14588, 14589, 15, 14524, 37330, 37409, 37412, 37414, 37416, 37417, 37419, 37421, 37424, 37426, 37427, 37429, 37430, 37431, 37363, 37435, 37439, 37442, 37445, 37316, 37447, 37386, 37451, 37390, 37454, 10, 11, 12, 13, 14, 15, 37456, 37458, 37460, 37462, 37296, 37464, 37466, 37354, 37469, 37432, 37434, 37472, 37440, 37443, 37476, 37448, 37479, 37481, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37488, 37491, 37495, 37497, 37366, 37436, 37503, 37505, 37492, 37500, 10, 11, 12, 13, 14, 15, 37524, 14591, 37522, 37526, 37520, 14595, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 14590, 14592, 14593, 14594, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37537, 37554, 37541, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37569, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 37570, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};
bool h_Op[]= {
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
#define THREADS_PER_BLOCK 16
#define BLOCKS_PER_GRID 1
#define SIZE_OF_IN 14608
#define SIZE_OF_AC 23008
__device__ void
ac(float *A, const int *B, const int *C, const bool *Op, int n_iter) {
int i= blockDim.x * blockIdx.x + threadIdx.x;
__shared__ float R[2351*THREADS_PER_BLOCK];
const int t= THREADS_PER_BLOCK;
__shared__ float final;
final=0;
R[i + 0*t] = A[i + 0*t];
R[i + 1*t] = A[i + 1*t];
R[i + 2*t] = A[i + 2*t];
R[i + 3*t] = A[i + 3*t];
R[i + 4*t] = A[i + 4*t];
R[i + 5*t] = A[i + 5*t];
R[i + 6*t] = A[i + 6*t];
R[i + 7*t] = A[i + 7*t];
R[i + 8*t] = A[i + 8*t];
R[i + 9*t] = A[i + 9*t];
R[i + 10*t] = A[i + 10*t];
R[i + 11*t] = A[i + 11*t];
R[i + 12*t] = A[i + 12*t];
R[i + 13*t] = A[i + 13*t];
R[i + 14*t] = A[i + 14*t];
R[i + 15*t] = A[i + 15*t];
R[i + 16*t] = A[i + 16*t];
R[i + 17*t] = A[i + 17*t];
R[i + 18*t] = A[i + 18*t];
R[i + 19*t] = A[i + 19*t];
R[i + 20*t] = A[i + 20*t];
R[i + 21*t] = A[i + 21*t];
R[i + 22*t] = A[i + 22*t];
R[i + 23*t] = A[i + 23*t];
R[i + 24*t] = A[i + 24*t];
R[i + 25*t] = A[i + 25*t];
R[i + 26*t] = A[i + 26*t];
R[i + 27*t] = A[i + 27*t];
R[i + 28*t] = A[i + 28*t];
R[i + 29*t] = A[i + 29*t];
R[i + 30*t] = A[i + 30*t];
R[i + 31*t] = A[i + 31*t];
R[i + 32*t] = A[i + 32*t];
R[i + 33*t] = A[i + 33*t];
R[i + 34*t] = A[i + 34*t];
R[i + 35*t] = A[i + 35*t];
R[i + 36*t] = A[i + 36*t];
R[i + 37*t] = A[i + 37*t];
R[i + 38*t] = A[i + 38*t];
R[i + 39*t] = A[i + 39*t];
R[i + 40*t] = A[i + 40*t];
R[i + 41*t] = A[i + 41*t];
R[i + 42*t] = A[i + 42*t];
R[i + 43*t] = A[i + 43*t];
R[i + 44*t] = A[i + 44*t];
R[i + 45*t] = A[i + 45*t];
R[i + 46*t] = A[i + 46*t];
R[i + 47*t] = A[i + 47*t];
R[i + 48*t] = A[i + 48*t];
R[i + 49*t] = A[i + 49*t];
R[i + 50*t] = A[i + 50*t];
R[i + 51*t] = A[i + 51*t];
R[i + 52*t] = A[i + 52*t];
R[i + 53*t] = A[i + 53*t];
R[i + 54*t] = A[i + 54*t];
R[i + 55*t] = A[i + 55*t];
R[i + 56*t] = A[i + 56*t];
R[i + 57*t] = A[i + 57*t];
R[i + 58*t] = A[i + 58*t];
R[i + 59*t] = A[i + 59*t];
R[i + 60*t] = A[i + 60*t];
R[i + 61*t] = A[i + 61*t];
R[i + 62*t] = A[i + 62*t];
R[i + 63*t] = A[i + 63*t];
R[i + 64*t] = A[i + 64*t];
R[i + 65*t] = A[i + 65*t];
R[i + 66*t] = A[i + 66*t];
R[i + 67*t] = A[i + 67*t];
R[i + 68*t] = A[i + 68*t];
R[i + 69*t] = A[i + 69*t];
R[i + 70*t] = A[i + 70*t];
R[i + 71*t] = A[i + 71*t];
R[i + 72*t] = A[i + 72*t];
R[i + 73*t] = A[i + 73*t];
R[i + 74*t] = A[i + 74*t];
R[i + 75*t] = A[i + 75*t];
R[i + 76*t] = A[i + 76*t];
R[i + 77*t] = A[i + 77*t];
R[i + 78*t] = A[i + 78*t];
R[i + 79*t] = A[i + 79*t];
R[i + 80*t] = A[i + 80*t];
R[i + 81*t] = A[i + 81*t];
R[i + 82*t] = A[i + 82*t];
R[i + 83*t] = A[i + 83*t];
R[i + 84*t] = A[i + 84*t];
R[i + 85*t] = A[i + 85*t];
R[i + 86*t] = A[i + 86*t];
R[i + 87*t] = A[i + 87*t];
R[i + 88*t] = A[i + 88*t];
R[i + 89*t] = A[i + 89*t];
R[i + 90*t] = A[i + 90*t];
R[i + 91*t] = A[i + 91*t];
R[i + 92*t] = A[i + 92*t];
R[i + 93*t] = A[i + 93*t];
R[i + 94*t] = A[i + 94*t];
R[i + 95*t] = A[i + 95*t];
R[i + 96*t] = A[i + 96*t];
R[i + 97*t] = A[i + 97*t];
R[i + 98*t] = A[i + 98*t];
R[i + 99*t] = A[i + 99*t];
R[i + 100*t] = A[i + 100*t];
R[i + 101*t] = A[i + 101*t];
R[i + 102*t] = A[i + 102*t];
R[i + 103*t] = A[i + 103*t];
R[i + 104*t] = A[i + 104*t];
R[i + 105*t] = A[i + 105*t];
R[i + 106*t] = A[i + 106*t];
R[i + 107*t] = A[i + 107*t];
R[i + 108*t] = A[i + 108*t];
R[i + 109*t] = A[i + 109*t];
R[i + 110*t] = A[i + 110*t];
R[i + 111*t] = A[i + 111*t];
R[i + 112*t] = A[i + 112*t];
R[i + 113*t] = A[i + 113*t];
R[i + 114*t] = A[i + 114*t];
R[i + 115*t] = A[i + 115*t];
R[i + 116*t] = A[i + 116*t];
R[i + 117*t] = A[i + 117*t];
R[i + 118*t] = A[i + 118*t];
R[i + 119*t] = A[i + 119*t];
R[i + 120*t] = A[i + 120*t];
R[i + 121*t] = A[i + 121*t];
R[i + 122*t] = A[i + 122*t];
R[i + 123*t] = A[i + 123*t];
R[i + 124*t] = A[i + 124*t];
R[i + 125*t] = A[i + 125*t];
R[i + 126*t] = A[i + 126*t];
R[i + 127*t] = A[i + 127*t];
R[i + 128*t] = A[i + 128*t];
R[i + 129*t] = A[i + 129*t];
R[i + 130*t] = A[i + 130*t];
R[i + 131*t] = A[i + 131*t];
R[i + 132*t] = A[i + 132*t];
R[i + 133*t] = A[i + 133*t];
R[i + 134*t] = A[i + 134*t];
R[i + 135*t] = A[i + 135*t];
R[i + 136*t] = A[i + 136*t];
R[i + 137*t] = A[i + 137*t];
R[i + 138*t] = A[i + 138*t];
R[i + 139*t] = A[i + 139*t];
R[i + 140*t] = A[i + 140*t];
R[i + 141*t] = A[i + 141*t];
R[i + 142*t] = A[i + 142*t];
R[i + 143*t] = A[i + 143*t];
R[i + 144*t] = A[i + 144*t];
R[i + 145*t] = A[i + 145*t];
R[i + 146*t] = A[i + 146*t];
R[i + 147*t] = A[i + 147*t];
R[i + 148*t] = A[i + 148*t];
R[i + 149*t] = A[i + 149*t];
R[i + 150*t] = A[i + 150*t];
R[i + 151*t] = A[i + 151*t];
R[i + 152*t] = A[i + 152*t];
R[i + 153*t] = A[i + 153*t];
R[i + 154*t] = A[i + 154*t];
R[i + 155*t] = A[i + 155*t];
R[i + 156*t] = A[i + 156*t];
R[i + 157*t] = A[i + 157*t];
R[i + 158*t] = A[i + 158*t];
R[i + 159*t] = A[i + 159*t];
R[i + 160*t] = A[i + 160*t];
R[i + 161*t] = A[i + 161*t];
R[i + 162*t] = A[i + 162*t];
R[i + 163*t] = A[i + 163*t];
R[i + 164*t] = A[i + 164*t];
R[i + 165*t] = A[i + 165*t];
R[i + 166*t] = A[i + 166*t];
R[i + 167*t] = A[i + 167*t];
R[i + 168*t] = A[i + 168*t];
R[i + 169*t] = A[i + 169*t];
R[i + 170*t] = A[i + 170*t];
R[i + 171*t] = A[i + 171*t];
R[i + 172*t] = A[i + 172*t];
R[i + 173*t] = A[i + 173*t];
R[i + 174*t] = A[i + 174*t];
R[i + 175*t] = A[i + 175*t];
R[i + 176*t] = A[i + 176*t];
R[i + 177*t] = A[i + 177*t];
R[i + 178*t] = A[i + 178*t];
R[i + 179*t] = A[i + 179*t];
R[i + 180*t] = A[i + 180*t];
R[i + 181*t] = A[i + 181*t];
R[i + 182*t] = A[i + 182*t];
R[i + 183*t] = A[i + 183*t];
R[i + 184*t] = A[i + 184*t];
R[i + 185*t] = A[i + 185*t];
R[i + 186*t] = A[i + 186*t];
R[i + 187*t] = A[i + 187*t];
R[i + 188*t] = A[i + 188*t];
R[i + 189*t] = A[i + 189*t];
R[i + 190*t] = A[i + 190*t];
R[i + 191*t] = A[i + 191*t];
R[i + 192*t] = A[i + 192*t];
R[i + 193*t] = A[i + 193*t];
R[i + 194*t] = A[i + 194*t];
R[i + 195*t] = A[i + 195*t];
R[i + 196*t] = A[i + 196*t];
R[i + 197*t] = A[i + 197*t];
R[i + 198*t] = A[i + 198*t];
R[i + 199*t] = A[i + 199*t];
R[i + 200*t] = A[i + 200*t];
R[i + 201*t] = A[i + 201*t];
R[i + 202*t] = A[i + 202*t];
R[i + 203*t] = A[i + 203*t];
R[i + 204*t] = A[i + 204*t];
R[i + 205*t] = A[i + 205*t];
R[i + 206*t] = A[i + 206*t];
R[i + 207*t] = A[i + 207*t];
R[i + 208*t] = A[i + 208*t];
R[i + 209*t] = A[i + 209*t];
R[i + 210*t] = A[i + 210*t];
R[i + 211*t] = A[i + 211*t];
R[i + 212*t] = A[i + 212*t];
R[i + 213*t] = A[i + 213*t];
R[i + 214*t] = A[i + 214*t];
R[i + 215*t] = A[i + 215*t];
R[i + 216*t] = A[i + 216*t];
R[i + 217*t] = A[i + 217*t];
R[i + 218*t] = A[i + 218*t];
R[i + 219*t] = A[i + 219*t];
R[i + 220*t] = A[i + 220*t];
R[i + 221*t] = A[i + 221*t];
R[i + 222*t] = A[i + 222*t];
R[i + 223*t] = A[i + 223*t];
R[i + 224*t] = A[i + 224*t];
R[i + 225*t] = A[i + 225*t];
R[i + 226*t] = A[i + 226*t];
R[i + 227*t] = A[i + 227*t];
R[i + 228*t] = A[i + 228*t];
R[i + 229*t] = A[i + 229*t];
R[i + 230*t] = A[i + 230*t];
R[i + 231*t] = A[i + 231*t];
R[i + 232*t] = A[i + 232*t];
R[i + 233*t] = A[i + 233*t];
R[i + 234*t] = A[i + 234*t];
R[i + 235*t] = A[i + 235*t];
R[i + 236*t] = A[i + 236*t];
R[i + 237*t] = A[i + 237*t];
R[i + 238*t] = A[i + 238*t];
R[i + 239*t] = A[i + 239*t];
R[i + 240*t] = A[i + 240*t];
R[i + 241*t] = A[i + 241*t];
R[i + 242*t] = A[i + 242*t];
R[i + 243*t] = A[i + 243*t];
R[i + 244*t] = A[i + 244*t];
R[i + 245*t] = A[i + 245*t];
R[i + 246*t] = A[i + 246*t];
R[i + 247*t] = A[i + 247*t];
R[i + 248*t] = A[i + 248*t];
R[i + 249*t] = A[i + 249*t];
R[i + 250*t] = A[i + 250*t];
R[i + 251*t] = A[i + 251*t];
R[i + 252*t] = A[i + 252*t];
R[i + 253*t] = A[i + 253*t];
R[i + 254*t] = A[i + 254*t];
R[i + 255*t] = A[i + 255*t];
R[i + 256*t] = A[i + 256*t];
R[i + 257*t] = A[i + 257*t];
R[i + 258*t] = A[i + 258*t];
R[i + 259*t] = A[i + 259*t];
R[i + 260*t] = A[i + 260*t];
R[i + 261*t] = A[i + 261*t];
R[i + 262*t] = A[i + 262*t];
R[i + 263*t] = A[i + 263*t];
R[i + 264*t] = A[i + 264*t];
R[i + 265*t] = A[i + 265*t];
R[i + 266*t] = A[i + 266*t];
R[i + 267*t] = A[i + 267*t];
R[i + 268*t] = A[i + 268*t];
R[i + 269*t] = A[i + 269*t];
R[i + 270*t] = A[i + 270*t];
R[i + 271*t] = A[i + 271*t];
R[i + 272*t] = A[i + 272*t];
R[i + 273*t] = A[i + 273*t];
R[i + 274*t] = A[i + 274*t];
R[i + 275*t] = A[i + 275*t];
R[i + 276*t] = A[i + 276*t];
R[i + 277*t] = A[i + 277*t];
R[i + 278*t] = A[i + 278*t];
R[i + 279*t] = A[i + 279*t];
R[i + 280*t] = A[i + 280*t];
R[i + 281*t] = A[i + 281*t];
R[i + 282*t] = A[i + 282*t];
R[i + 283*t] = A[i + 283*t];
R[i + 284*t] = A[i + 284*t];
R[i + 285*t] = A[i + 285*t];
R[i + 286*t] = A[i + 286*t];
R[i + 287*t] = A[i + 287*t];
R[i + 288*t] = A[i + 288*t];
R[i + 289*t] = A[i + 289*t];
R[i + 290*t] = A[i + 290*t];
R[i + 291*t] = A[i + 291*t];
R[i + 292*t] = A[i + 292*t];
R[i + 293*t] = A[i + 293*t];
R[i + 294*t] = A[i + 294*t];
R[i + 295*t] = A[i + 295*t];
R[i + 296*t] = A[i + 296*t];
R[i + 297*t] = A[i + 297*t];
R[i + 298*t] = A[i + 298*t];
R[i + 299*t] = A[i + 299*t];
R[i + 300*t] = A[i + 300*t];
R[i + 301*t] = A[i + 301*t];
R[i + 302*t] = A[i + 302*t];
R[i + 303*t] = A[i + 303*t];
R[i + 304*t] = A[i + 304*t];
R[i + 305*t] = A[i + 305*t];
R[i + 306*t] = A[i + 306*t];
R[i + 307*t] = A[i + 307*t];
R[i + 308*t] = A[i + 308*t];
R[i + 309*t] = A[i + 309*t];
R[i + 310*t] = A[i + 310*t];
R[i + 311*t] = A[i + 311*t];
R[i + 312*t] = A[i + 312*t];
R[i + 313*t] = A[i + 313*t];
R[i + 314*t] = A[i + 314*t];
R[i + 315*t] = A[i + 315*t];
R[i + 316*t] = A[i + 316*t];
R[i + 317*t] = A[i + 317*t];
R[i + 318*t] = A[i + 318*t];
R[i + 319*t] = A[i + 319*t];
R[i + 320*t] = A[i + 320*t];
R[i + 321*t] = A[i + 321*t];
R[i + 322*t] = A[i + 322*t];
R[i + 323*t] = A[i + 323*t];
R[i + 324*t] = A[i + 324*t];
R[i + 325*t] = A[i + 325*t];
R[i + 326*t] = A[i + 326*t];
R[i + 327*t] = A[i + 327*t];
R[i + 328*t] = A[i + 328*t];
R[i + 329*t] = A[i + 329*t];
R[i + 330*t] = A[i + 330*t];
R[i + 331*t] = A[i + 331*t];
R[i + 332*t] = A[i + 332*t];
R[i + 333*t] = A[i + 333*t];
R[i + 334*t] = A[i + 334*t];
R[i + 335*t] = A[i + 335*t];
R[i + 336*t] = A[i + 336*t];
R[i + 337*t] = A[i + 337*t];
R[i + 338*t] = A[i + 338*t];
R[i + 339*t] = A[i + 339*t];
R[i + 340*t] = A[i + 340*t];
R[i + 341*t] = A[i + 341*t];
R[i + 342*t] = A[i + 342*t];
R[i + 343*t] = A[i + 343*t];
R[i + 344*t] = A[i + 344*t];
R[i + 345*t] = A[i + 345*t];
R[i + 346*t] = A[i + 346*t];
R[i + 347*t] = A[i + 347*t];
R[i + 348*t] = A[i + 348*t];
R[i + 349*t] = A[i + 349*t];
R[i + 350*t] = A[i + 350*t];
R[i + 351*t] = A[i + 351*t];
R[i + 352*t] = A[i + 352*t];
R[i + 353*t] = A[i + 353*t];
R[i + 354*t] = A[i + 354*t];
R[i + 355*t] = A[i + 355*t];
R[i + 356*t] = A[i + 356*t];
R[i + 357*t] = A[i + 357*t];
R[i + 358*t] = A[i + 358*t];
R[i + 359*t] = A[i + 359*t];
R[i + 360*t] = A[i + 360*t];
R[i + 361*t] = A[i + 361*t];
R[i + 362*t] = A[i + 362*t];
R[i + 363*t] = A[i + 363*t];
R[i + 364*t] = A[i + 364*t];
R[i + 365*t] = A[i + 365*t];
R[i + 366*t] = A[i + 366*t];
R[i + 367*t] = A[i + 367*t];
R[i + 368*t] = A[i + 368*t];
R[i + 369*t] = A[i + 369*t];
R[i + 370*t] = A[i + 370*t];
R[i + 371*t] = A[i + 371*t];
R[i + 372*t] = A[i + 372*t];
R[i + 373*t] = A[i + 373*t];
R[i + 374*t] = A[i + 374*t];
R[i + 375*t] = A[i + 375*t];
R[i + 376*t] = A[i + 376*t];
R[i + 377*t] = A[i + 377*t];
R[i + 378*t] = A[i + 378*t];
R[i + 379*t] = A[i + 379*t];
R[i + 380*t] = A[i + 380*t];
R[i + 381*t] = A[i + 381*t];
R[i + 382*t] = A[i + 382*t];
R[i + 383*t] = A[i + 383*t];
R[i + 384*t] = A[i + 384*t];
R[i + 385*t] = A[i + 385*t];
R[i + 386*t] = A[i + 386*t];
R[i + 387*t] = A[i + 387*t];
R[i + 388*t] = A[i + 388*t];
R[i + 389*t] = A[i + 389*t];
R[i + 390*t] = A[i + 390*t];
R[i + 391*t] = A[i + 391*t];
R[i + 392*t] = A[i + 392*t];
R[i + 393*t] = A[i + 393*t];
R[i + 394*t] = A[i + 394*t];
R[i + 395*t] = A[i + 395*t];
R[i + 396*t] = A[i + 396*t];
R[i + 397*t] = A[i + 397*t];
R[i + 398*t] = A[i + 398*t];
R[i + 399*t] = A[i + 399*t];
R[i + 400*t] = A[i + 400*t];
R[i + 401*t] = A[i + 401*t];
R[i + 402*t] = A[i + 402*t];
R[i + 403*t] = A[i + 403*t];
R[i + 404*t] = A[i + 404*t];
R[i + 405*t] = A[i + 405*t];
R[i + 406*t] = A[i + 406*t];
R[i + 407*t] = A[i + 407*t];
R[i + 408*t] = A[i + 408*t];
R[i + 409*t] = A[i + 409*t];
R[i + 410*t] = A[i + 410*t];
R[i + 411*t] = A[i + 411*t];
R[i + 412*t] = A[i + 412*t];
R[i + 413*t] = A[i + 413*t];
R[i + 414*t] = A[i + 414*t];
R[i + 415*t] = A[i + 415*t];
R[i + 416*t] = A[i + 416*t];
R[i + 417*t] = A[i + 417*t];
R[i + 418*t] = A[i + 418*t];
R[i + 419*t] = A[i + 419*t];
R[i + 420*t] = A[i + 420*t];
R[i + 421*t] = A[i + 421*t];
R[i + 422*t] = A[i + 422*t];
R[i + 423*t] = A[i + 423*t];
R[i + 424*t] = A[i + 424*t];
R[i + 425*t] = A[i + 425*t];
R[i + 426*t] = A[i + 426*t];
R[i + 427*t] = A[i + 427*t];
R[i + 428*t] = A[i + 428*t];
R[i + 429*t] = A[i + 429*t];
R[i + 430*t] = A[i + 430*t];
R[i + 431*t] = A[i + 431*t];
R[i + 432*t] = A[i + 432*t];
R[i + 433*t] = A[i + 433*t];
R[i + 434*t] = A[i + 434*t];
R[i + 435*t] = A[i + 435*t];
R[i + 436*t] = A[i + 436*t];
R[i + 437*t] = A[i + 437*t];
R[i + 438*t] = A[i + 438*t];
R[i + 439*t] = A[i + 439*t];
R[i + 440*t] = A[i + 440*t];
R[i + 441*t] = A[i + 441*t];
R[i + 442*t] = A[i + 442*t];
R[i + 443*t] = A[i + 443*t];
R[i + 444*t] = A[i + 444*t];
R[i + 445*t] = A[i + 445*t];
R[i + 446*t] = A[i + 446*t];
R[i + 447*t] = A[i + 447*t];
R[i + 448*t] = A[i + 448*t];
R[i + 449*t] = A[i + 449*t];
R[i + 450*t] = A[i + 450*t];
R[i + 451*t] = A[i + 451*t];
R[i + 452*t] = A[i + 452*t];
R[i + 453*t] = A[i + 453*t];
R[i + 454*t] = A[i + 454*t];
R[i + 455*t] = A[i + 455*t];
R[i + 456*t] = A[i + 456*t];
R[i + 457*t] = A[i + 457*t];
R[i + 458*t] = A[i + 458*t];
R[i + 459*t] = A[i + 459*t];
R[i + 460*t] = A[i + 460*t];
R[i + 461*t] = A[i + 461*t];
R[i + 462*t] = A[i + 462*t];
R[i + 463*t] = A[i + 463*t];
R[i + 464*t] = A[i + 464*t];
R[i + 465*t] = A[i + 465*t];
R[i + 466*t] = A[i + 466*t];
R[i + 467*t] = A[i + 467*t];
R[i + 468*t] = A[i + 468*t];
R[i + 469*t] = A[i + 469*t];
R[i + 470*t] = A[i + 470*t];
R[i + 471*t] = A[i + 471*t];
R[i + 472*t] = A[i + 472*t];
R[i + 473*t] = A[i + 473*t];
R[i + 474*t] = A[i + 474*t];
R[i + 475*t] = A[i + 475*t];
R[i + 476*t] = A[i + 476*t];
R[i + 477*t] = A[i + 477*t];
R[i + 478*t] = A[i + 478*t];
R[i + 479*t] = A[i + 479*t];
R[i + 480*t] = A[i + 480*t];
R[i + 481*t] = A[i + 481*t];
R[i + 482*t] = A[i + 482*t];
R[i + 483*t] = A[i + 483*t];
R[i + 484*t] = A[i + 484*t];
R[i + 485*t] = A[i + 485*t];
R[i + 486*t] = A[i + 486*t];
R[i + 487*t] = A[i + 487*t];
R[i + 488*t] = A[i + 488*t];
R[i + 489*t] = A[i + 489*t];
R[i + 490*t] = A[i + 490*t];
R[i + 491*t] = A[i + 491*t];
R[i + 492*t] = A[i + 492*t];
R[i + 493*t] = A[i + 493*t];
R[i + 494*t] = A[i + 494*t];
R[i + 495*t] = A[i + 495*t];
R[i + 496*t] = A[i + 496*t];
R[i + 497*t] = A[i + 497*t];
R[i + 498*t] = A[i + 498*t];
R[i + 499*t] = A[i + 499*t];
R[i + 500*t] = A[i + 500*t];
R[i + 501*t] = A[i + 501*t];
R[i + 502*t] = A[i + 502*t];
R[i + 503*t] = A[i + 503*t];
R[i + 504*t] = A[i + 504*t];
R[i + 505*t] = A[i + 505*t];
R[i + 506*t] = A[i + 506*t];
R[i + 507*t] = A[i + 507*t];
R[i + 508*t] = A[i + 508*t];
R[i + 509*t] = A[i + 509*t];
R[i + 510*t] = A[i + 510*t];
R[i + 511*t] = A[i + 511*t];
R[i + 512*t] = A[i + 512*t];
R[i + 513*t] = A[i + 513*t];
R[i + 514*t] = A[i + 514*t];
R[i + 515*t] = A[i + 515*t];
R[i + 516*t] = A[i + 516*t];
R[i + 517*t] = A[i + 517*t];
R[i + 518*t] = A[i + 518*t];
R[i + 519*t] = A[i + 519*t];
R[i + 520*t] = A[i + 520*t];
R[i + 521*t] = A[i + 521*t];
R[i + 522*t] = A[i + 522*t];
R[i + 523*t] = A[i + 523*t];
R[i + 524*t] = A[i + 524*t];
R[i + 525*t] = A[i + 525*t];
R[i + 526*t] = A[i + 526*t];
R[i + 527*t] = A[i + 527*t];
R[i + 528*t] = A[i + 528*t];
R[i + 529*t] = A[i + 529*t];
R[i + 530*t] = A[i + 530*t];
R[i + 531*t] = A[i + 531*t];
R[i + 532*t] = A[i + 532*t];
R[i + 533*t] = A[i + 533*t];
R[i + 534*t] = A[i + 534*t];
R[i + 535*t] = A[i + 535*t];
R[i + 536*t] = A[i + 536*t];
R[i + 537*t] = A[i + 537*t];
R[i + 538*t] = A[i + 538*t];
R[i + 539*t] = A[i + 539*t];
R[i + 540*t] = A[i + 540*t];
R[i + 541*t] = A[i + 541*t];
R[i + 542*t] = A[i + 542*t];
R[i + 543*t] = A[i + 543*t];
R[i + 544*t] = A[i + 544*t];
R[i + 545*t] = A[i + 545*t];
R[i + 546*t] = A[i + 546*t];
R[i + 547*t] = A[i + 547*t];
R[i + 548*t] = A[i + 548*t];
R[i + 549*t] = A[i + 549*t];
R[i + 550*t] = A[i + 550*t];
R[i + 551*t] = A[i + 551*t];
R[i + 552*t] = A[i + 552*t];
R[i + 553*t] = A[i + 553*t];
R[i + 554*t] = A[i + 554*t];
R[i + 555*t] = A[i + 555*t];
R[i + 556*t] = A[i + 556*t];
R[i + 557*t] = A[i + 557*t];
R[i + 558*t] = A[i + 558*t];
R[i + 559*t] = A[i + 559*t];
R[i + 560*t] = A[i + 560*t];
R[i + 561*t] = A[i + 561*t];
R[i + 562*t] = A[i + 562*t];
R[i + 563*t] = A[i + 563*t];
R[i + 564*t] = A[i + 564*t];
R[i + 565*t] = A[i + 565*t];
R[i + 566*t] = A[i + 566*t];
R[i + 567*t] = A[i + 567*t];
R[i + 568*t] = A[i + 568*t];
R[i + 569*t] = A[i + 569*t];
R[i + 570*t] = A[i + 570*t];
R[i + 571*t] = A[i + 571*t];
R[i + 572*t] = A[i + 572*t];
R[i + 573*t] = A[i + 573*t];
R[i + 574*t] = A[i + 574*t];
R[i + 575*t] = A[i + 575*t];
R[i + 576*t] = A[i + 576*t];
R[i + 577*t] = A[i + 577*t];
R[i + 578*t] = A[i + 578*t];
R[i + 579*t] = A[i + 579*t];
R[i + 580*t] = A[i + 580*t];
R[i + 581*t] = A[i + 581*t];
R[i + 582*t] = A[i + 582*t];
R[i + 583*t] = A[i + 583*t];
R[i + 584*t] = A[i + 584*t];
R[i + 585*t] = A[i + 585*t];
R[i + 586*t] = A[i + 586*t];
R[i + 587*t] = A[i + 587*t];
R[i + 588*t] = A[i + 588*t];
R[i + 589*t] = A[i + 589*t];
R[i + 590*t] = A[i + 590*t];
R[i + 591*t] = A[i + 591*t];
R[i + 592*t] = A[i + 592*t];
R[i + 593*t] = A[i + 593*t];
R[i + 594*t] = A[i + 594*t];
R[i + 595*t] = A[i + 595*t];
R[i + 596*t] = A[i + 596*t];
R[i + 597*t] = A[i + 597*t];
R[i + 598*t] = A[i + 598*t];
R[i + 599*t] = A[i + 599*t];
R[i + 600*t] = A[i + 600*t];
R[i + 601*t] = A[i + 601*t];
R[i + 602*t] = A[i + 602*t];
R[i + 603*t] = A[i + 603*t];
R[i + 604*t] = A[i + 604*t];
R[i + 605*t] = A[i + 605*t];
R[i + 606*t] = A[i + 606*t];
R[i + 607*t] = A[i + 607*t];
R[i + 608*t] = A[i + 608*t];
R[i + 609*t] = A[i + 609*t];
R[i + 610*t] = A[i + 610*t];
R[i + 611*t] = A[i + 611*t];
R[i + 612*t] = A[i + 612*t];
R[i + 613*t] = A[i + 613*t];
R[i + 614*t] = A[i + 614*t];
R[i + 615*t] = A[i + 615*t];
R[i + 616*t] = A[i + 616*t];
R[i + 617*t] = A[i + 617*t];
R[i + 618*t] = A[i + 618*t];
R[i + 619*t] = A[i + 619*t];
R[i + 620*t] = A[i + 620*t];
R[i + 621*t] = A[i + 621*t];
R[i + 622*t] = A[i + 622*t];
R[i + 623*t] = A[i + 623*t];
R[i + 624*t] = A[i + 624*t];
R[i + 625*t] = A[i + 625*t];
R[i + 626*t] = A[i + 626*t];
R[i + 627*t] = A[i + 627*t];
R[i + 628*t] = A[i + 628*t];
R[i + 629*t] = A[i + 629*t];
R[i + 630*t] = A[i + 630*t];
R[i + 631*t] = A[i + 631*t];
R[i + 632*t] = A[i + 632*t];
R[i + 633*t] = A[i + 633*t];
R[i + 634*t] = A[i + 634*t];
R[i + 635*t] = A[i + 635*t];
R[i + 636*t] = A[i + 636*t];
R[i + 637*t] = A[i + 637*t];
R[i + 638*t] = A[i + 638*t];
R[i + 639*t] = A[i + 639*t];
R[i + 640*t] = A[i + 640*t];
R[i + 641*t] = A[i + 641*t];
R[i + 642*t] = A[i + 642*t];
R[i + 643*t] = A[i + 643*t];
R[i + 644*t] = A[i + 644*t];
R[i + 645*t] = A[i + 645*t];
R[i + 646*t] = A[i + 646*t];
R[i + 647*t] = A[i + 647*t];
R[i + 648*t] = A[i + 648*t];
R[i + 649*t] = A[i + 649*t];
R[i + 650*t] = A[i + 650*t];
R[i + 651*t] = A[i + 651*t];
R[i + 652*t] = A[i + 652*t];
R[i + 653*t] = A[i + 653*t];
R[i + 654*t] = A[i + 654*t];
R[i + 655*t] = A[i + 655*t];
R[i + 656*t] = A[i + 656*t];
R[i + 657*t] = A[i + 657*t];
R[i + 658*t] = A[i + 658*t];
R[i + 659*t] = A[i + 659*t];
R[i + 660*t] = A[i + 660*t];
R[i + 661*t] = A[i + 661*t];
R[i + 662*t] = A[i + 662*t];
R[i + 663*t] = A[i + 663*t];
R[i + 664*t] = A[i + 664*t];
R[i + 665*t] = A[i + 665*t];
R[i + 666*t] = A[i + 666*t];
R[i + 667*t] = A[i + 667*t];
R[i + 668*t] = A[i + 668*t];
R[i + 669*t] = A[i + 669*t];
R[i + 670*t] = A[i + 670*t];
R[i + 671*t] = A[i + 671*t];
R[i + 672*t] = A[i + 672*t];
R[i + 673*t] = A[i + 673*t];
R[i + 674*t] = A[i + 674*t];
R[i + 675*t] = A[i + 675*t];
R[i + 676*t] = A[i + 676*t];
R[i + 677*t] = A[i + 677*t];
R[i + 678*t] = A[i + 678*t];
R[i + 679*t] = A[i + 679*t];
R[i + 680*t] = A[i + 680*t];
R[i + 681*t] = A[i + 681*t];
R[i + 682*t] = A[i + 682*t];
R[i + 683*t] = A[i + 683*t];
R[i + 684*t] = A[i + 684*t];
R[i + 685*t] = A[i + 685*t];
R[i + 686*t] = A[i + 686*t];
R[i + 687*t] = A[i + 687*t];
R[i + 688*t] = A[i + 688*t];
R[i + 689*t] = A[i + 689*t];
R[i + 690*t] = A[i + 690*t];
R[i + 691*t] = A[i + 691*t];
R[i + 692*t] = A[i + 692*t];
R[i + 693*t] = A[i + 693*t];
R[i + 694*t] = A[i + 694*t];
R[i + 695*t] = A[i + 695*t];
R[i + 696*t] = A[i + 696*t];
R[i + 697*t] = A[i + 697*t];
R[i + 698*t] = A[i + 698*t];
R[i + 699*t] = A[i + 699*t];
R[i + 700*t] = A[i + 700*t];
R[i + 701*t] = A[i + 701*t];
R[i + 702*t] = A[i + 702*t];
R[i + 703*t] = A[i + 703*t];
R[i + 704*t] = A[i + 704*t];
R[i + 705*t] = A[i + 705*t];
R[i + 706*t] = A[i + 706*t];
R[i + 707*t] = A[i + 707*t];
R[i + 708*t] = A[i + 708*t];
R[i + 709*t] = A[i + 709*t];
R[i + 710*t] = A[i + 710*t];
R[i + 711*t] = A[i + 711*t];
R[i + 712*t] = A[i + 712*t];
R[i + 713*t] = A[i + 713*t];
R[i + 714*t] = A[i + 714*t];
R[i + 715*t] = A[i + 715*t];
R[i + 716*t] = A[i + 716*t];
R[i + 717*t] = A[i + 717*t];
R[i + 718*t] = A[i + 718*t];
R[i + 719*t] = A[i + 719*t];
R[i + 720*t] = A[i + 720*t];
R[i + 721*t] = A[i + 721*t];
R[i + 722*t] = A[i + 722*t];
R[i + 723*t] = A[i + 723*t];
R[i + 724*t] = A[i + 724*t];
R[i + 725*t] = A[i + 725*t];
R[i + 726*t] = A[i + 726*t];
R[i + 727*t] = A[i + 727*t];
R[i + 728*t] = A[i + 728*t];
R[i + 729*t] = A[i + 729*t];
R[i + 730*t] = A[i + 730*t];
R[i + 731*t] = A[i + 731*t];
R[i + 732*t] = A[i + 732*t];
R[i + 733*t] = A[i + 733*t];
R[i + 734*t] = A[i + 734*t];
R[i + 735*t] = A[i + 735*t];
R[i + 736*t] = A[i + 736*t];
R[i + 737*t] = A[i + 737*t];
R[i + 738*t] = A[i + 738*t];
R[i + 739*t] = A[i + 739*t];
R[i + 740*t] = A[i + 740*t];
R[i + 741*t] = A[i + 741*t];
R[i + 742*t] = A[i + 742*t];
R[i + 743*t] = A[i + 743*t];
R[i + 744*t] = A[i + 744*t];
R[i + 745*t] = A[i + 745*t];
R[i + 746*t] = A[i + 746*t];
R[i + 747*t] = A[i + 747*t];
R[i + 748*t] = A[i + 748*t];
R[i + 749*t] = A[i + 749*t];
R[i + 750*t] = A[i + 750*t];
R[i + 751*t] = A[i + 751*t];
R[i + 752*t] = A[i + 752*t];
R[i + 753*t] = A[i + 753*t];
R[i + 754*t] = A[i + 754*t];
R[i + 755*t] = A[i + 755*t];
R[i + 756*t] = A[i + 756*t];
R[i + 757*t] = A[i + 757*t];
R[i + 758*t] = A[i + 758*t];
R[i + 759*t] = A[i + 759*t];
R[i + 760*t] = A[i + 760*t];
R[i + 761*t] = A[i + 761*t];
R[i + 762*t] = A[i + 762*t];
R[i + 763*t] = A[i + 763*t];
R[i + 764*t] = A[i + 764*t];
R[i + 765*t] = A[i + 765*t];
R[i + 766*t] = A[i + 766*t];
R[i + 767*t] = A[i + 767*t];
R[i + 768*t] = A[i + 768*t];
R[i + 769*t] = A[i + 769*t];
R[i + 770*t] = A[i + 770*t];
R[i + 771*t] = A[i + 771*t];
R[i + 772*t] = A[i + 772*t];
R[i + 773*t] = A[i + 773*t];
R[i + 774*t] = A[i + 774*t];
R[i + 775*t] = A[i + 775*t];
R[i + 776*t] = A[i + 776*t];
R[i + 777*t] = A[i + 777*t];
R[i + 778*t] = A[i + 778*t];
R[i + 779*t] = A[i + 779*t];
R[i + 780*t] = A[i + 780*t];
R[i + 781*t] = A[i + 781*t];
R[i + 782*t] = A[i + 782*t];
R[i + 783*t] = A[i + 783*t];
R[i + 784*t] = A[i + 784*t];
R[i + 785*t] = A[i + 785*t];
R[i + 786*t] = A[i + 786*t];
R[i + 787*t] = A[i + 787*t];
R[i + 788*t] = A[i + 788*t];
R[i + 789*t] = A[i + 789*t];
R[i + 790*t] = A[i + 790*t];
R[i + 791*t] = A[i + 791*t];
R[i + 792*t] = A[i + 792*t];
R[i + 793*t] = A[i + 793*t];
R[i + 794*t] = A[i + 794*t];
R[i + 795*t] = A[i + 795*t];
R[i + 796*t] = A[i + 796*t];
R[i + 797*t] = A[i + 797*t];
R[i + 798*t] = A[i + 798*t];
R[i + 799*t] = A[i + 799*t];
R[i + 800*t] = A[i + 800*t];
R[i + 801*t] = A[i + 801*t];
R[i + 802*t] = A[i + 802*t];
R[i + 803*t] = A[i + 803*t];
R[i + 804*t] = A[i + 804*t];
R[i + 805*t] = A[i + 805*t];
R[i + 806*t] = A[i + 806*t];
R[i + 807*t] = A[i + 807*t];
R[i + 808*t] = A[i + 808*t];
R[i + 809*t] = A[i + 809*t];
R[i + 810*t] = A[i + 810*t];
R[i + 811*t] = A[i + 811*t];
R[i + 812*t] = A[i + 812*t];
R[i + 813*t] = A[i + 813*t];
R[i + 814*t] = A[i + 814*t];
R[i + 815*t] = A[i + 815*t];
R[i + 816*t] = A[i + 816*t];
R[i + 817*t] = A[i + 817*t];
R[i + 818*t] = A[i + 818*t];
R[i + 819*t] = A[i + 819*t];
R[i + 820*t] = A[i + 820*t];
R[i + 821*t] = A[i + 821*t];
R[i + 822*t] = A[i + 822*t];
R[i + 823*t] = A[i + 823*t];
R[i + 824*t] = A[i + 824*t];
R[i + 825*t] = A[i + 825*t];
R[i + 826*t] = A[i + 826*t];
R[i + 827*t] = A[i + 827*t];
R[i + 828*t] = A[i + 828*t];
R[i + 829*t] = A[i + 829*t];
R[i + 830*t] = A[i + 830*t];
R[i + 831*t] = A[i + 831*t];
R[i + 832*t] = A[i + 832*t];
R[i + 833*t] = A[i + 833*t];
R[i + 834*t] = A[i + 834*t];
R[i + 835*t] = A[i + 835*t];
R[i + 836*t] = A[i + 836*t];
R[i + 837*t] = A[i + 837*t];
R[i + 838*t] = A[i + 838*t];
R[i + 839*t] = A[i + 839*t];
R[i + 840*t] = A[i + 840*t];
R[i + 841*t] = A[i + 841*t];
R[i + 842*t] = A[i + 842*t];
R[i + 843*t] = A[i + 843*t];
R[i + 844*t] = A[i + 844*t];
R[i + 845*t] = A[i + 845*t];
R[i + 846*t] = A[i + 846*t];
R[i + 847*t] = A[i + 847*t];
R[i + 848*t] = A[i + 848*t];
R[i + 849*t] = A[i + 849*t];
R[i + 850*t] = A[i + 850*t];
R[i + 851*t] = A[i + 851*t];
R[i + 852*t] = A[i + 852*t];
R[i + 853*t] = A[i + 853*t];
R[i + 854*t] = A[i + 854*t];
R[i + 855*t] = A[i + 855*t];
R[i + 856*t] = A[i + 856*t];
R[i + 857*t] = A[i + 857*t];
R[i + 858*t] = A[i + 858*t];
R[i + 859*t] = A[i + 859*t];
R[i + 860*t] = A[i + 860*t];
R[i + 861*t] = A[i + 861*t];
R[i + 862*t] = A[i + 862*t];
R[i + 863*t] = A[i + 863*t];
R[i + 864*t] = A[i + 864*t];
R[i + 865*t] = A[i + 865*t];
R[i + 866*t] = A[i + 866*t];
R[i + 867*t] = A[i + 867*t];
R[i + 868*t] = A[i + 868*t];
R[i + 869*t] = A[i + 869*t];
R[i + 870*t] = A[i + 870*t];
R[i + 871*t] = A[i + 871*t];
R[i + 872*t] = A[i + 872*t];
R[i + 873*t] = A[i + 873*t];
R[i + 874*t] = A[i + 874*t];
R[i + 875*t] = A[i + 875*t];
R[i + 876*t] = A[i + 876*t];
R[i + 877*t] = A[i + 877*t];
R[i + 878*t] = A[i + 878*t];
R[i + 879*t] = A[i + 879*t];
R[i + 880*t] = A[i + 880*t];
R[i + 881*t] = A[i + 881*t];
R[i + 882*t] = A[i + 882*t];
R[i + 883*t] = A[i + 883*t];
R[i + 884*t] = A[i + 884*t];
R[i + 885*t] = A[i + 885*t];
R[i + 886*t] = A[i + 886*t];
R[i + 887*t] = A[i + 887*t];
R[i + 888*t] = A[i + 888*t];
R[i + 889*t] = A[i + 889*t];
R[i + 890*t] = A[i + 890*t];
R[i + 891*t] = A[i + 891*t];
R[i + 892*t] = A[i + 892*t];
R[i + 893*t] = A[i + 893*t];
R[i + 894*t] = A[i + 894*t];
R[i + 895*t] = A[i + 895*t];
R[i + 896*t] = A[i + 896*t];
R[i + 897*t] = A[i + 897*t];
R[i + 898*t] = A[i + 898*t];
R[i + 899*t] = A[i + 899*t];
R[i + 900*t] = A[i + 900*t];
R[i + 901*t] = A[i + 901*t];
R[i + 902*t] = A[i + 902*t];
R[i + 903*t] = A[i + 903*t];
R[i + 904*t] = A[i + 904*t];
R[i + 905*t] = A[i + 905*t];
R[i + 906*t] = A[i + 906*t];
R[i + 907*t] = A[i + 907*t];
R[i + 908*t] = A[i + 908*t];
R[i + 909*t] = A[i + 909*t];
R[i + 910*t] = A[i + 910*t];
R[i + 911*t] = A[i + 911*t];
R[i + 912*t] = A[i + 912*t];
__syncthreads();
for (int iter=0; iter< n_iter; iter++) {
R[i + 913*t] = Op[i + 0*t] ? R[B[i + 0*t]] * R[C[i + 0*t]] : R[B[i + 0*t]] + R[C[i + 0*t]];
R[i + 914*t] = Op[i + 1*t] ? R[B[i + 1*t]] * R[C[i + 1*t]] : R[B[i + 1*t]] + R[C[i + 1*t]];
R[i + 915*t] = Op[i + 2*t] ? R[B[i + 2*t]] * R[C[i + 2*t]] : R[B[i + 2*t]] + R[C[i + 2*t]];
R[i + 916*t] = Op[i + 3*t] ? R[B[i + 3*t]] * R[C[i + 3*t]] : R[B[i + 3*t]] + R[C[i + 3*t]];
R[i + 917*t] = Op[i + 4*t] ? R[B[i + 4*t]] * R[C[i + 4*t]] : R[B[i + 4*t]] + R[C[i + 4*t]];
R[i + 918*t] = Op[i + 5*t] ? R[B[i + 5*t]] * R[C[i + 5*t]] : R[B[i + 5*t]] + R[C[i + 5*t]];
R[i + 919*t] = Op[i + 6*t] ? R[B[i + 6*t]] * R[C[i + 6*t]] : R[B[i + 6*t]] + R[C[i + 6*t]];
R[i + 920*t] = Op[i + 7*t] ? R[B[i + 7*t]] * R[C[i + 7*t]] : R[B[i + 7*t]] + R[C[i + 7*t]];
R[i + 921*t] = Op[i + 8*t] ? R[B[i + 8*t]] * R[C[i + 8*t]] : R[B[i + 8*t]] + R[C[i + 8*t]];
R[i + 922*t] = Op[i + 9*t] ? R[B[i + 9*t]] * R[C[i + 9*t]] : R[B[i + 9*t]] + R[C[i + 9*t]];
R[i + 923*t] = Op[i + 10*t] ? R[B[i + 10*t]] * R[C[i + 10*t]] : R[B[i + 10*t]] + R[C[i + 10*t]];
R[i + 924*t] = Op[i + 11*t] ? R[B[i + 11*t]] * R[C[i + 11*t]] : R[B[i + 11*t]] + R[C[i + 11*t]];
R[i + 925*t] = Op[i + 12*t] ? R[B[i + 12*t]] * R[C[i + 12*t]] : R[B[i + 12*t]] + R[C[i + 12*t]];
R[i + 926*t] = Op[i + 13*t] ? R[B[i + 13*t]] * R[C[i + 13*t]] : R[B[i + 13*t]] + R[C[i + 13*t]];
R[i + 927*t] = Op[i + 14*t] ? R[B[i + 14*t]] * R[C[i + 14*t]] : R[B[i + 14*t]] + R[C[i + 14*t]];
R[i + 928*t] = Op[i + 15*t] ? R[B[i + 15*t]] * R[C[i + 15*t]] : R[B[i + 15*t]] + R[C[i + 15*t]];
R[i + 929*t] = Op[i + 16*t] ? R[B[i + 16*t]] * R[C[i + 16*t]] : R[B[i + 16*t]] + R[C[i + 16*t]];
R[i + 930*t] = Op[i + 17*t] ? R[B[i + 17*t]] * R[C[i + 17*t]] : R[B[i + 17*t]] + R[C[i + 17*t]];
R[i + 931*t] = Op[i + 18*t] ? R[B[i + 18*t]] * R[C[i + 18*t]] : R[B[i + 18*t]] + R[C[i + 18*t]];
R[i + 932*t] = Op[i + 19*t] ? R[B[i + 19*t]] * R[C[i + 19*t]] : R[B[i + 19*t]] + R[C[i + 19*t]];
R[i + 933*t] = Op[i + 20*t] ? R[B[i + 20*t]] * R[C[i + 20*t]] : R[B[i + 20*t]] + R[C[i + 20*t]];
R[i + 934*t] = Op[i + 21*t] ? R[B[i + 21*t]] * R[C[i + 21*t]] : R[B[i + 21*t]] + R[C[i + 21*t]];
R[i + 935*t] = Op[i + 22*t] ? R[B[i + 22*t]] * R[C[i + 22*t]] : R[B[i + 22*t]] + R[C[i + 22*t]];
R[i + 936*t] = Op[i + 23*t] ? R[B[i + 23*t]] * R[C[i + 23*t]] : R[B[i + 23*t]] + R[C[i + 23*t]];
R[i + 937*t] = Op[i + 24*t] ? R[B[i + 24*t]] * R[C[i + 24*t]] : R[B[i + 24*t]] + R[C[i + 24*t]];
R[i + 938*t] = Op[i + 25*t] ? R[B[i + 25*t]] * R[C[i + 25*t]] : R[B[i + 25*t]] + R[C[i + 25*t]];
R[i + 939*t] = Op[i + 26*t] ? R[B[i + 26*t]] * R[C[i + 26*t]] : R[B[i + 26*t]] + R[C[i + 26*t]];
R[i + 940*t] = Op[i + 27*t] ? R[B[i + 27*t]] * R[C[i + 27*t]] : R[B[i + 27*t]] + R[C[i + 27*t]];
R[i + 941*t] = Op[i + 28*t] ? R[B[i + 28*t]] * R[C[i + 28*t]] : R[B[i + 28*t]] + R[C[i + 28*t]];
R[i + 942*t] = Op[i + 29*t] ? R[B[i + 29*t]] * R[C[i + 29*t]] : R[B[i + 29*t]] + R[C[i + 29*t]];
R[i + 943*t] = Op[i + 30*t] ? R[B[i + 30*t]] * R[C[i + 30*t]] : R[B[i + 30*t]] + R[C[i + 30*t]];
R[i + 944*t] = Op[i + 31*t] ? R[B[i + 31*t]] * R[C[i + 31*t]] : R[B[i + 31*t]] + R[C[i + 31*t]];
R[i + 945*t] = Op[i + 32*t] ? R[B[i + 32*t]] * R[C[i + 32*t]] : R[B[i + 32*t]] + R[C[i + 32*t]];
R[i + 946*t] = Op[i + 33*t] ? R[B[i + 33*t]] * R[C[i + 33*t]] : R[B[i + 33*t]] + R[C[i + 33*t]];
R[i + 947*t] = Op[i + 34*t] ? R[B[i + 34*t]] * R[C[i + 34*t]] : R[B[i + 34*t]] + R[C[i + 34*t]];
R[i + 948*t] = Op[i + 35*t] ? R[B[i + 35*t]] * R[C[i + 35*t]] : R[B[i + 35*t]] + R[C[i + 35*t]];
R[i + 949*t] = Op[i + 36*t] ? R[B[i + 36*t]] * R[C[i + 36*t]] : R[B[i + 36*t]] + R[C[i + 36*t]];
R[i + 950*t] = Op[i + 37*t] ? R[B[i + 37*t]] * R[C[i + 37*t]] : R[B[i + 37*t]] + R[C[i + 37*t]];
R[i + 951*t] = Op[i + 38*t] ? R[B[i + 38*t]] * R[C[i + 38*t]] : R[B[i + 38*t]] + R[C[i + 38*t]];
R[i + 952*t] = Op[i + 39*t] ? R[B[i + 39*t]] * R[C[i + 39*t]] : R[B[i + 39*t]] + R[C[i + 39*t]];
R[i + 953*t] = Op[i + 40*t] ? R[B[i + 40*t]] * R[C[i + 40*t]] : R[B[i + 40*t]] + R[C[i + 40*t]];
R[i + 954*t] = Op[i + 41*t] ? R[B[i + 41*t]] * R[C[i + 41*t]] : R[B[i + 41*t]] + R[C[i + 41*t]];
R[i + 955*t] = Op[i + 42*t] ? R[B[i + 42*t]] * R[C[i + 42*t]] : R[B[i + 42*t]] + R[C[i + 42*t]];
R[i + 956*t] = Op[i + 43*t] ? R[B[i + 43*t]] * R[C[i + 43*t]] : R[B[i + 43*t]] + R[C[i + 43*t]];
R[i + 957*t] = Op[i + 44*t] ? R[B[i + 44*t]] * R[C[i + 44*t]] : R[B[i + 44*t]] + R[C[i + 44*t]];
R[i + 958*t] = Op[i + 45*t] ? R[B[i + 45*t]] * R[C[i + 45*t]] : R[B[i + 45*t]] + R[C[i + 45*t]];
R[i + 959*t] = Op[i + 46*t] ? R[B[i + 46*t]] * R[C[i + 46*t]] : R[B[i + 46*t]] + R[C[i + 46*t]];
R[i + 960*t] = Op[i + 47*t] ? R[B[i + 47*t]] * R[C[i + 47*t]] : R[B[i + 47*t]] + R[C[i + 47*t]];
R[i + 961*t] = Op[i + 48*t] ? R[B[i + 48*t]] * R[C[i + 48*t]] : R[B[i + 48*t]] + R[C[i + 48*t]];
R[i + 962*t] = Op[i + 49*t] ? R[B[i + 49*t]] * R[C[i + 49*t]] : R[B[i + 49*t]] + R[C[i + 49*t]];
R[i + 963*t] = Op[i + 50*t] ? R[B[i + 50*t]] * R[C[i + 50*t]] : R[B[i + 50*t]] + R[C[i + 50*t]];
R[i + 964*t] = Op[i + 51*t] ? R[B[i + 51*t]] * R[C[i + 51*t]] : R[B[i + 51*t]] + R[C[i + 51*t]];
R[i + 965*t] = Op[i + 52*t] ? R[B[i + 52*t]] * R[C[i + 52*t]] : R[B[i + 52*t]] + R[C[i + 52*t]];
R[i + 966*t] = Op[i + 53*t] ? R[B[i + 53*t]] * R[C[i + 53*t]] : R[B[i + 53*t]] + R[C[i + 53*t]];
R[i + 967*t] = Op[i + 54*t] ? R[B[i + 54*t]] * R[C[i + 54*t]] : R[B[i + 54*t]] + R[C[i + 54*t]];
R[i + 968*t] = Op[i + 55*t] ? R[B[i + 55*t]] * R[C[i + 55*t]] : R[B[i + 55*t]] + R[C[i + 55*t]];
R[i + 969*t] = Op[i + 56*t] ? R[B[i + 56*t]] * R[C[i + 56*t]] : R[B[i + 56*t]] + R[C[i + 56*t]];
R[i + 970*t] = Op[i + 57*t] ? R[B[i + 57*t]] * R[C[i + 57*t]] : R[B[i + 57*t]] + R[C[i + 57*t]];
R[i + 971*t] = Op[i + 58*t] ? R[B[i + 58*t]] * R[C[i + 58*t]] : R[B[i + 58*t]] + R[C[i + 58*t]];
R[i + 972*t] = Op[i + 59*t] ? R[B[i + 59*t]] * R[C[i + 59*t]] : R[B[i + 59*t]] + R[C[i + 59*t]];
R[i + 973*t] = Op[i + 60*t] ? R[B[i + 60*t]] * R[C[i + 60*t]] : R[B[i + 60*t]] + R[C[i + 60*t]];
R[i + 974*t] = Op[i + 61*t] ? R[B[i + 61*t]] * R[C[i + 61*t]] : R[B[i + 61*t]] + R[C[i + 61*t]];
R[i + 975*t] = Op[i + 62*t] ? R[B[i + 62*t]] * R[C[i + 62*t]] : R[B[i + 62*t]] + R[C[i + 62*t]];
R[i + 976*t] = Op[i + 63*t] ? R[B[i + 63*t]] * R[C[i + 63*t]] : R[B[i + 63*t]] + R[C[i + 63*t]];
R[i + 977*t] = Op[i + 64*t] ? R[B[i + 64*t]] * R[C[i + 64*t]] : R[B[i + 64*t]] + R[C[i + 64*t]];
R[i + 978*t] = Op[i + 65*t] ? R[B[i + 65*t]] * R[C[i + 65*t]] : R[B[i + 65*t]] + R[C[i + 65*t]];
R[i + 979*t] = Op[i + 66*t] ? R[B[i + 66*t]] * R[C[i + 66*t]] : R[B[i + 66*t]] + R[C[i + 66*t]];
R[i + 980*t] = Op[i + 67*t] ? R[B[i + 67*t]] * R[C[i + 67*t]] : R[B[i + 67*t]] + R[C[i + 67*t]];
R[i + 981*t] = Op[i + 68*t] ? R[B[i + 68*t]] * R[C[i + 68*t]] : R[B[i + 68*t]] + R[C[i + 68*t]];
R[i + 982*t] = Op[i + 69*t] ? R[B[i + 69*t]] * R[C[i + 69*t]] : R[B[i + 69*t]] + R[C[i + 69*t]];
R[i + 983*t] = Op[i + 70*t] ? R[B[i + 70*t]] * R[C[i + 70*t]] : R[B[i + 70*t]] + R[C[i + 70*t]];
R[i + 984*t] = Op[i + 71*t] ? R[B[i + 71*t]] * R[C[i + 71*t]] : R[B[i + 71*t]] + R[C[i + 71*t]];
R[i + 985*t] = Op[i + 72*t] ? R[B[i + 72*t]] * R[C[i + 72*t]] : R[B[i + 72*t]] + R[C[i + 72*t]];
R[i + 986*t] = Op[i + 73*t] ? R[B[i + 73*t]] * R[C[i + 73*t]] : R[B[i + 73*t]] + R[C[i + 73*t]];
R[i + 987*t] = Op[i + 74*t] ? R[B[i + 74*t]] * R[C[i + 74*t]] : R[B[i + 74*t]] + R[C[i + 74*t]];
R[i + 988*t] = Op[i + 75*t] ? R[B[i + 75*t]] * R[C[i + 75*t]] : R[B[i + 75*t]] + R[C[i + 75*t]];
R[i + 989*t] = Op[i + 76*t] ? R[B[i + 76*t]] * R[C[i + 76*t]] : R[B[i + 76*t]] + R[C[i + 76*t]];
R[i + 990*t] = Op[i + 77*t] ? R[B[i + 77*t]] * R[C[i + 77*t]] : R[B[i + 77*t]] + R[C[i + 77*t]];
R[i + 991*t] = Op[i + 78*t] ? R[B[i + 78*t]] * R[C[i + 78*t]] : R[B[i + 78*t]] + R[C[i + 78*t]];
R[i + 992*t] = Op[i + 79*t] ? R[B[i + 79*t]] * R[C[i + 79*t]] : R[B[i + 79*t]] + R[C[i + 79*t]];
R[i + 993*t] = Op[i + 80*t] ? R[B[i + 80*t]] * R[C[i + 80*t]] : R[B[i + 80*t]] + R[C[i + 80*t]];
R[i + 994*t] = Op[i + 81*t] ? R[B[i + 81*t]] * R[C[i + 81*t]] : R[B[i + 81*t]] + R[C[i + 81*t]];
R[i + 995*t] = Op[i + 82*t] ? R[B[i + 82*t]] * R[C[i + 82*t]] : R[B[i + 82*t]] + R[C[i + 82*t]];
R[i + 996*t] = Op[i + 83*t] ? R[B[i + 83*t]] * R[C[i + 83*t]] : R[B[i + 83*t]] + R[C[i + 83*t]];
R[i + 997*t] = Op[i + 84*t] ? R[B[i + 84*t]] * R[C[i + 84*t]] : R[B[i + 84*t]] + R[C[i + 84*t]];
R[i + 998*t] = Op[i + 85*t] ? R[B[i + 85*t]] * R[C[i + 85*t]] : R[B[i + 85*t]] + R[C[i + 85*t]];
R[i + 999*t] = Op[i + 86*t] ? R[B[i + 86*t]] * R[C[i + 86*t]] : R[B[i + 86*t]] + R[C[i + 86*t]];
R[i + 1000*t] = Op[i + 87*t] ? R[B[i + 87*t]] * R[C[i + 87*t]] : R[B[i + 87*t]] + R[C[i + 87*t]];
R[i + 1001*t] = Op[i + 88*t] ? R[B[i + 88*t]] * R[C[i + 88*t]] : R[B[i + 88*t]] + R[C[i + 88*t]];
R[i + 1002*t] = Op[i + 89*t] ? R[B[i + 89*t]] * R[C[i + 89*t]] : R[B[i + 89*t]] + R[C[i + 89*t]];
R[i + 1003*t] = Op[i + 90*t] ? R[B[i + 90*t]] * R[C[i + 90*t]] : R[B[i + 90*t]] + R[C[i + 90*t]];
R[i + 1004*t] = Op[i + 91*t] ? R[B[i + 91*t]] * R[C[i + 91*t]] : R[B[i + 91*t]] + R[C[i + 91*t]];
R[i + 1005*t] = Op[i + 92*t] ? R[B[i + 92*t]] * R[C[i + 92*t]] : R[B[i + 92*t]] + R[C[i + 92*t]];
R[i + 1006*t] = Op[i + 93*t] ? R[B[i + 93*t]] * R[C[i + 93*t]] : R[B[i + 93*t]] + R[C[i + 93*t]];
R[i + 1007*t] = Op[i + 94*t] ? R[B[i + 94*t]] * R[C[i + 94*t]] : R[B[i + 94*t]] + R[C[i + 94*t]];
R[i + 1008*t] = Op[i + 95*t] ? R[B[i + 95*t]] * R[C[i + 95*t]] : R[B[i + 95*t]] + R[C[i + 95*t]];
R[i + 1009*t] = Op[i + 96*t] ? R[B[i + 96*t]] * R[C[i + 96*t]] : R[B[i + 96*t]] + R[C[i + 96*t]];
R[i + 1010*t] = Op[i + 97*t] ? R[B[i + 97*t]] * R[C[i + 97*t]] : R[B[i + 97*t]] + R[C[i + 97*t]];
R[i + 1011*t] = Op[i + 98*t] ? R[B[i + 98*t]] * R[C[i + 98*t]] : R[B[i + 98*t]] + R[C[i + 98*t]];
R[i + 1012*t] = Op[i + 99*t] ? R[B[i + 99*t]] * R[C[i + 99*t]] : R[B[i + 99*t]] + R[C[i + 99*t]];
R[i + 1013*t] = Op[i + 100*t] ? R[B[i + 100*t]] * R[C[i + 100*t]] : R[B[i + 100*t]] + R[C[i + 100*t]];
R[i + 1014*t] = Op[i + 101*t] ? R[B[i + 101*t]] * R[C[i + 101*t]] : R[B[i + 101*t]] + R[C[i + 101*t]];
R[i + 1015*t] = Op[i + 102*t] ? R[B[i + 102*t]] * R[C[i + 102*t]] : R[B[i + 102*t]] + R[C[i + 102*t]];
R[i + 1016*t] = Op[i + 103*t] ? R[B[i + 103*t]] * R[C[i + 103*t]] : R[B[i + 103*t]] + R[C[i + 103*t]];
R[i + 1017*t] = Op[i + 104*t] ? R[B[i + 104*t]] * R[C[i + 104*t]] : R[B[i + 104*t]] + R[C[i + 104*t]];
R[i + 1018*t] = Op[i + 105*t] ? R[B[i + 105*t]] * R[C[i + 105*t]] : R[B[i + 105*t]] + R[C[i + 105*t]];
R[i + 1019*t] = Op[i + 106*t] ? R[B[i + 106*t]] * R[C[i + 106*t]] : R[B[i + 106*t]] + R[C[i + 106*t]];
R[i + 1020*t] = Op[i + 107*t] ? R[B[i + 107*t]] * R[C[i + 107*t]] : R[B[i + 107*t]] + R[C[i + 107*t]];
R[i + 1021*t] = Op[i + 108*t] ? R[B[i + 108*t]] * R[C[i + 108*t]] : R[B[i + 108*t]] + R[C[i + 108*t]];
R[i + 1022*t] = Op[i + 109*t] ? R[B[i + 109*t]] * R[C[i + 109*t]] : R[B[i + 109*t]] + R[C[i + 109*t]];
R[i + 1023*t] = Op[i + 110*t] ? R[B[i + 110*t]] * R[C[i + 110*t]] : R[B[i + 110*t]] + R[C[i + 110*t]];
R[i + 1024*t] = Op[i + 111*t] ? R[B[i + 111*t]] * R[C[i + 111*t]] : R[B[i + 111*t]] + R[C[i + 111*t]];
R[i + 1025*t] = Op[i + 112*t] ? R[B[i + 112*t]] * R[C[i + 112*t]] : R[B[i + 112*t]] + R[C[i + 112*t]];
R[i + 1026*t] = Op[i + 113*t] ? R[B[i + 113*t]] * R[C[i + 113*t]] : R[B[i + 113*t]] + R[C[i + 113*t]];
R[i + 1027*t] = Op[i + 114*t] ? R[B[i + 114*t]] * R[C[i + 114*t]] : R[B[i + 114*t]] + R[C[i + 114*t]];
R[i + 1028*t] = Op[i + 115*t] ? R[B[i + 115*t]] * R[C[i + 115*t]] : R[B[i + 115*t]] + R[C[i + 115*t]];
R[i + 1029*t] = Op[i + 116*t] ? R[B[i + 116*t]] * R[C[i + 116*t]] : R[B[i + 116*t]] + R[C[i + 116*t]];
R[i + 1030*t] = Op[i + 117*t] ? R[B[i + 117*t]] * R[C[i + 117*t]] : R[B[i + 117*t]] + R[C[i + 117*t]];
R[i + 1031*t] = Op[i + 118*t] ? R[B[i + 118*t]] * R[C[i + 118*t]] : R[B[i + 118*t]] + R[C[i + 118*t]];
R[i + 1032*t] = Op[i + 119*t] ? R[B[i + 119*t]] * R[C[i + 119*t]] : R[B[i + 119*t]] + R[C[i + 119*t]];
R[i + 1033*t] = Op[i + 120*t] ? R[B[i + 120*t]] * R[C[i + 120*t]] : R[B[i + 120*t]] + R[C[i + 120*t]];
R[i + 1034*t] = Op[i + 121*t] ? R[B[i + 121*t]] * R[C[i + 121*t]] : R[B[i + 121*t]] + R[C[i + 121*t]];
R[i + 1035*t] = Op[i + 122*t] ? R[B[i + 122*t]] * R[C[i + 122*t]] : R[B[i + 122*t]] + R[C[i + 122*t]];
R[i + 1036*t] = Op[i + 123*t] ? R[B[i + 123*t]] * R[C[i + 123*t]] : R[B[i + 123*t]] + R[C[i + 123*t]];
R[i + 1037*t] = Op[i + 124*t] ? R[B[i + 124*t]] * R[C[i + 124*t]] : R[B[i + 124*t]] + R[C[i + 124*t]];
R[i + 1038*t] = Op[i + 125*t] ? R[B[i + 125*t]] * R[C[i + 125*t]] : R[B[i + 125*t]] + R[C[i + 125*t]];
R[i + 1039*t] = Op[i + 126*t] ? R[B[i + 126*t]] * R[C[i + 126*t]] : R[B[i + 126*t]] + R[C[i + 126*t]];
R[i + 1040*t] = Op[i + 127*t] ? R[B[i + 127*t]] * R[C[i + 127*t]] : R[B[i + 127*t]] + R[C[i + 127*t]];
R[i + 1041*t] = Op[i + 128*t] ? R[B[i + 128*t]] * R[C[i + 128*t]] : R[B[i + 128*t]] + R[C[i + 128*t]];
R[i + 1042*t] = Op[i + 129*t] ? R[B[i + 129*t]] * R[C[i + 129*t]] : R[B[i + 129*t]] + R[C[i + 129*t]];
R[i + 1043*t] = Op[i + 130*t] ? R[B[i + 130*t]] * R[C[i + 130*t]] : R[B[i + 130*t]] + R[C[i + 130*t]];
R[i + 1044*t] = Op[i + 131*t] ? R[B[i + 131*t]] * R[C[i + 131*t]] : R[B[i + 131*t]] + R[C[i + 131*t]];
R[i + 1045*t] = Op[i + 132*t] ? R[B[i + 132*t]] * R[C[i + 132*t]] : R[B[i + 132*t]] + R[C[i + 132*t]];
R[i + 1046*t] = Op[i + 133*t] ? R[B[i + 133*t]] * R[C[i + 133*t]] : R[B[i + 133*t]] + R[C[i + 133*t]];
R[i + 1047*t] = Op[i + 134*t] ? R[B[i + 134*t]] * R[C[i + 134*t]] : R[B[i + 134*t]] + R[C[i + 134*t]];
R[i + 1048*t] = Op[i + 135*t] ? R[B[i + 135*t]] * R[C[i + 135*t]] : R[B[i + 135*t]] + R[C[i + 135*t]];
R[i + 1049*t] = Op[i + 136*t] ? R[B[i + 136*t]] * R[C[i + 136*t]] : R[B[i + 136*t]] + R[C[i + 136*t]];
R[i + 1050*t] = Op[i + 137*t] ? R[B[i + 137*t]] * R[C[i + 137*t]] : R[B[i + 137*t]] + R[C[i + 137*t]];
R[i + 1051*t] = Op[i + 138*t] ? R[B[i + 138*t]] * R[C[i + 138*t]] : R[B[i + 138*t]] + R[C[i + 138*t]];
R[i + 1052*t] = Op[i + 139*t] ? R[B[i + 139*t]] * R[C[i + 139*t]] : R[B[i + 139*t]] + R[C[i + 139*t]];
R[i + 1053*t] = Op[i + 140*t] ? R[B[i + 140*t]] * R[C[i + 140*t]] : R[B[i + 140*t]] + R[C[i + 140*t]];
R[i + 1054*t] = Op[i + 141*t] ? R[B[i + 141*t]] * R[C[i + 141*t]] : R[B[i + 141*t]] + R[C[i + 141*t]];
R[i + 1055*t] = Op[i + 142*t] ? R[B[i + 142*t]] * R[C[i + 142*t]] : R[B[i + 142*t]] + R[C[i + 142*t]];
R[i + 1056*t] = Op[i + 143*t] ? R[B[i + 143*t]] * R[C[i + 143*t]] : R[B[i + 143*t]] + R[C[i + 143*t]];
R[i + 1057*t] = Op[i + 144*t] ? R[B[i + 144*t]] * R[C[i + 144*t]] : R[B[i + 144*t]] + R[C[i + 144*t]];
R[i + 1058*t] = Op[i + 145*t] ? R[B[i + 145*t]] * R[C[i + 145*t]] : R[B[i + 145*t]] + R[C[i + 145*t]];
R[i + 1059*t] = Op[i + 146*t] ? R[B[i + 146*t]] * R[C[i + 146*t]] : R[B[i + 146*t]] + R[C[i + 146*t]];
R[i + 1060*t] = Op[i + 147*t] ? R[B[i + 147*t]] * R[C[i + 147*t]] : R[B[i + 147*t]] + R[C[i + 147*t]];
R[i + 1061*t] = Op[i + 148*t] ? R[B[i + 148*t]] * R[C[i + 148*t]] : R[B[i + 148*t]] + R[C[i + 148*t]];
R[i + 1062*t] = Op[i + 149*t] ? R[B[i + 149*t]] * R[C[i + 149*t]] : R[B[i + 149*t]] + R[C[i + 149*t]];
R[i + 1063*t] = Op[i + 150*t] ? R[B[i + 150*t]] * R[C[i + 150*t]] : R[B[i + 150*t]] + R[C[i + 150*t]];
R[i + 1064*t] = Op[i + 151*t] ? R[B[i + 151*t]] * R[C[i + 151*t]] : R[B[i + 151*t]] + R[C[i + 151*t]];
R[i + 1065*t] = Op[i + 152*t] ? R[B[i + 152*t]] * R[C[i + 152*t]] : R[B[i + 152*t]] + R[C[i + 152*t]];
R[i + 1066*t] = Op[i + 153*t] ? R[B[i + 153*t]] * R[C[i + 153*t]] : R[B[i + 153*t]] + R[C[i + 153*t]];
R[i + 1067*t] = Op[i + 154*t] ? R[B[i + 154*t]] * R[C[i + 154*t]] : R[B[i + 154*t]] + R[C[i + 154*t]];
R[i + 1068*t] = Op[i + 155*t] ? R[B[i + 155*t]] * R[C[i + 155*t]] : R[B[i + 155*t]] + R[C[i + 155*t]];
R[i + 1069*t] = Op[i + 156*t] ? R[B[i + 156*t]] * R[C[i + 156*t]] : R[B[i + 156*t]] + R[C[i + 156*t]];
R[i + 1070*t] = Op[i + 157*t] ? R[B[i + 157*t]] * R[C[i + 157*t]] : R[B[i + 157*t]] + R[C[i + 157*t]];
R[i + 1071*t] = Op[i + 158*t] ? R[B[i + 158*t]] * R[C[i + 158*t]] : R[B[i + 158*t]] + R[C[i + 158*t]];
R[i + 1072*t] = Op[i + 159*t] ? R[B[i + 159*t]] * R[C[i + 159*t]] : R[B[i + 159*t]] + R[C[i + 159*t]];
R[i + 1073*t] = Op[i + 160*t] ? R[B[i + 160*t]] * R[C[i + 160*t]] : R[B[i + 160*t]] + R[C[i + 160*t]];
R[i + 1074*t] = Op[i + 161*t] ? R[B[i + 161*t]] * R[C[i + 161*t]] : R[B[i + 161*t]] + R[C[i + 161*t]];
R[i + 1075*t] = Op[i + 162*t] ? R[B[i + 162*t]] * R[C[i + 162*t]] : R[B[i + 162*t]] + R[C[i + 162*t]];
R[i + 1076*t] = Op[i + 163*t] ? R[B[i + 163*t]] * R[C[i + 163*t]] : R[B[i + 163*t]] + R[C[i + 163*t]];
R[i + 1077*t] = Op[i + 164*t] ? R[B[i + 164*t]] * R[C[i + 164*t]] : R[B[i + 164*t]] + R[C[i + 164*t]];
R[i + 1078*t] = Op[i + 165*t] ? R[B[i + 165*t]] * R[C[i + 165*t]] : R[B[i + 165*t]] + R[C[i + 165*t]];
R[i + 1079*t] = Op[i + 166*t] ? R[B[i + 166*t]] * R[C[i + 166*t]] : R[B[i + 166*t]] + R[C[i + 166*t]];
R[i + 1080*t] = Op[i + 167*t] ? R[B[i + 167*t]] * R[C[i + 167*t]] : R[B[i + 167*t]] + R[C[i + 167*t]];
R[i + 1081*t] = Op[i + 168*t] ? R[B[i + 168*t]] * R[C[i + 168*t]] : R[B[i + 168*t]] + R[C[i + 168*t]];
R[i + 1082*t] = Op[i + 169*t] ? R[B[i + 169*t]] * R[C[i + 169*t]] : R[B[i + 169*t]] + R[C[i + 169*t]];
R[i + 1083*t] = Op[i + 170*t] ? R[B[i + 170*t]] * R[C[i + 170*t]] : R[B[i + 170*t]] + R[C[i + 170*t]];
R[i + 1084*t] = Op[i + 171*t] ? R[B[i + 171*t]] * R[C[i + 171*t]] : R[B[i + 171*t]] + R[C[i + 171*t]];
R[i + 1085*t] = Op[i + 172*t] ? R[B[i + 172*t]] * R[C[i + 172*t]] : R[B[i + 172*t]] + R[C[i + 172*t]];
R[i + 1086*t] = Op[i + 173*t] ? R[B[i + 173*t]] * R[C[i + 173*t]] : R[B[i + 173*t]] + R[C[i + 173*t]];
R[i + 1087*t] = Op[i + 174*t] ? R[B[i + 174*t]] * R[C[i + 174*t]] : R[B[i + 174*t]] + R[C[i + 174*t]];
R[i + 1088*t] = Op[i + 175*t] ? R[B[i + 175*t]] * R[C[i + 175*t]] : R[B[i + 175*t]] + R[C[i + 175*t]];
R[i + 1089*t] = Op[i + 176*t] ? R[B[i + 176*t]] * R[C[i + 176*t]] : R[B[i + 176*t]] + R[C[i + 176*t]];
R[i + 1090*t] = Op[i + 177*t] ? R[B[i + 177*t]] * R[C[i + 177*t]] : R[B[i + 177*t]] + R[C[i + 177*t]];
R[i + 1091*t] = Op[i + 178*t] ? R[B[i + 178*t]] * R[C[i + 178*t]] : R[B[i + 178*t]] + R[C[i + 178*t]];
R[i + 1092*t] = Op[i + 179*t] ? R[B[i + 179*t]] * R[C[i + 179*t]] : R[B[i + 179*t]] + R[C[i + 179*t]];
R[i + 1093*t] = Op[i + 180*t] ? R[B[i + 180*t]] * R[C[i + 180*t]] : R[B[i + 180*t]] + R[C[i + 180*t]];
R[i + 1094*t] = Op[i + 181*t] ? R[B[i + 181*t]] * R[C[i + 181*t]] : R[B[i + 181*t]] + R[C[i + 181*t]];
R[i + 1095*t] = Op[i + 182*t] ? R[B[i + 182*t]] * R[C[i + 182*t]] : R[B[i + 182*t]] + R[C[i + 182*t]];
R[i + 1096*t] = Op[i + 183*t] ? R[B[i + 183*t]] * R[C[i + 183*t]] : R[B[i + 183*t]] + R[C[i + 183*t]];
R[i + 1097*t] = Op[i + 184*t] ? R[B[i + 184*t]] * R[C[i + 184*t]] : R[B[i + 184*t]] + R[C[i + 184*t]];
R[i + 1098*t] = Op[i + 185*t] ? R[B[i + 185*t]] * R[C[i + 185*t]] : R[B[i + 185*t]] + R[C[i + 185*t]];
R[i + 1099*t] = Op[i + 186*t] ? R[B[i + 186*t]] * R[C[i + 186*t]] : R[B[i + 186*t]] + R[C[i + 186*t]];
R[i + 1100*t] = Op[i + 187*t] ? R[B[i + 187*t]] * R[C[i + 187*t]] : R[B[i + 187*t]] + R[C[i + 187*t]];
R[i + 1101*t] = Op[i + 188*t] ? R[B[i + 188*t]] * R[C[i + 188*t]] : R[B[i + 188*t]] + R[C[i + 188*t]];
R[i + 1102*t] = Op[i + 189*t] ? R[B[i + 189*t]] * R[C[i + 189*t]] : R[B[i + 189*t]] + R[C[i + 189*t]];
R[i + 1103*t] = Op[i + 190*t] ? R[B[i + 190*t]] * R[C[i + 190*t]] : R[B[i + 190*t]] + R[C[i + 190*t]];
R[i + 1104*t] = Op[i + 191*t] ? R[B[i + 191*t]] * R[C[i + 191*t]] : R[B[i + 191*t]] + R[C[i + 191*t]];
R[i + 1105*t] = Op[i + 192*t] ? R[B[i + 192*t]] * R[C[i + 192*t]] : R[B[i + 192*t]] + R[C[i + 192*t]];
R[i + 1106*t] = Op[i + 193*t] ? R[B[i + 193*t]] * R[C[i + 193*t]] : R[B[i + 193*t]] + R[C[i + 193*t]];
R[i + 1107*t] = Op[i + 194*t] ? R[B[i + 194*t]] * R[C[i + 194*t]] : R[B[i + 194*t]] + R[C[i + 194*t]];
R[i + 1108*t] = Op[i + 195*t] ? R[B[i + 195*t]] * R[C[i + 195*t]] : R[B[i + 195*t]] + R[C[i + 195*t]];
R[i + 1109*t] = Op[i + 196*t] ? R[B[i + 196*t]] * R[C[i + 196*t]] : R[B[i + 196*t]] + R[C[i + 196*t]];
R[i + 1110*t] = Op[i + 197*t] ? R[B[i + 197*t]] * R[C[i + 197*t]] : R[B[i + 197*t]] + R[C[i + 197*t]];
R[i + 1111*t] = Op[i + 198*t] ? R[B[i + 198*t]] * R[C[i + 198*t]] : R[B[i + 198*t]] + R[C[i + 198*t]];
R[i + 1112*t] = Op[i + 199*t] ? R[B[i + 199*t]] * R[C[i + 199*t]] : R[B[i + 199*t]] + R[C[i + 199*t]];
R[i + 1113*t] = Op[i + 200*t] ? R[B[i + 200*t]] * R[C[i + 200*t]] : R[B[i + 200*t]] + R[C[i + 200*t]];
R[i + 1114*t] = Op[i + 201*t] ? R[B[i + 201*t]] * R[C[i + 201*t]] : R[B[i + 201*t]] + R[C[i + 201*t]];
R[i + 1115*t] = Op[i + 202*t] ? R[B[i + 202*t]] * R[C[i + 202*t]] : R[B[i + 202*t]] + R[C[i + 202*t]];
R[i + 1116*t] = Op[i + 203*t] ? R[B[i + 203*t]] * R[C[i + 203*t]] : R[B[i + 203*t]] + R[C[i + 203*t]];
R[i + 1117*t] = Op[i + 204*t] ? R[B[i + 204*t]] * R[C[i + 204*t]] : R[B[i + 204*t]] + R[C[i + 204*t]];
R[i + 1118*t] = Op[i + 205*t] ? R[B[i + 205*t]] * R[C[i + 205*t]] : R[B[i + 205*t]] + R[C[i + 205*t]];
R[i + 1119*t] = Op[i + 206*t] ? R[B[i + 206*t]] * R[C[i + 206*t]] : R[B[i + 206*t]] + R[C[i + 206*t]];
R[i + 1120*t] = Op[i + 207*t] ? R[B[i + 207*t]] * R[C[i + 207*t]] : R[B[i + 207*t]] + R[C[i + 207*t]];
R[i + 1121*t] = Op[i + 208*t] ? R[B[i + 208*t]] * R[C[i + 208*t]] : R[B[i + 208*t]] + R[C[i + 208*t]];
R[i + 1122*t] = Op[i + 209*t] ? R[B[i + 209*t]] * R[C[i + 209*t]] : R[B[i + 209*t]] + R[C[i + 209*t]];
R[i + 1123*t] = Op[i + 210*t] ? R[B[i + 210*t]] * R[C[i + 210*t]] : R[B[i + 210*t]] + R[C[i + 210*t]];
R[i + 1124*t] = Op[i + 211*t] ? R[B[i + 211*t]] * R[C[i + 211*t]] : R[B[i + 211*t]] + R[C[i + 211*t]];
R[i + 1125*t] = Op[i + 212*t] ? R[B[i + 212*t]] * R[C[i + 212*t]] : R[B[i + 212*t]] + R[C[i + 212*t]];
R[i + 1126*t] = Op[i + 213*t] ? R[B[i + 213*t]] * R[C[i + 213*t]] : R[B[i + 213*t]] + R[C[i + 213*t]];
R[i + 1127*t] = Op[i + 214*t] ? R[B[i + 214*t]] * R[C[i + 214*t]] : R[B[i + 214*t]] + R[C[i + 214*t]];
R[i + 1128*t] = Op[i + 215*t] ? R[B[i + 215*t]] * R[C[i + 215*t]] : R[B[i + 215*t]] + R[C[i + 215*t]];
R[i + 1129*t] = Op[i + 216*t] ? R[B[i + 216*t]] * R[C[i + 216*t]] : R[B[i + 216*t]] + R[C[i + 216*t]];
R[i + 1130*t] = Op[i + 217*t] ? R[B[i + 217*t]] * R[C[i + 217*t]] : R[B[i + 217*t]] + R[C[i + 217*t]];
R[i + 1131*t] = Op[i + 218*t] ? R[B[i + 218*t]] * R[C[i + 218*t]] : R[B[i + 218*t]] + R[C[i + 218*t]];
R[i + 1132*t] = Op[i + 219*t] ? R[B[i + 219*t]] * R[C[i + 219*t]] : R[B[i + 219*t]] + R[C[i + 219*t]];
R[i + 1133*t] = Op[i + 220*t] ? R[B[i + 220*t]] * R[C[i + 220*t]] : R[B[i + 220*t]] + R[C[i + 220*t]];
R[i + 1134*t] = Op[i + 221*t] ? R[B[i + 221*t]] * R[C[i + 221*t]] : R[B[i + 221*t]] + R[C[i + 221*t]];
R[i + 1135*t] = Op[i + 222*t] ? R[B[i + 222*t]] * R[C[i + 222*t]] : R[B[i + 222*t]] + R[C[i + 222*t]];
R[i + 1136*t] = Op[i + 223*t] ? R[B[i + 223*t]] * R[C[i + 223*t]] : R[B[i + 223*t]] + R[C[i + 223*t]];
R[i + 1137*t] = Op[i + 224*t] ? R[B[i + 224*t]] * R[C[i + 224*t]] : R[B[i + 224*t]] + R[C[i + 224*t]];
R[i + 1138*t] = Op[i + 225*t] ? R[B[i + 225*t]] * R[C[i + 225*t]] : R[B[i + 225*t]] + R[C[i + 225*t]];
R[i + 1139*t] = Op[i + 226*t] ? R[B[i + 226*t]] * R[C[i + 226*t]] : R[B[i + 226*t]] + R[C[i + 226*t]];
R[i + 1140*t] = Op[i + 227*t] ? R[B[i + 227*t]] * R[C[i + 227*t]] : R[B[i + 227*t]] + R[C[i + 227*t]];
R[i + 1141*t] = Op[i + 228*t] ? R[B[i + 228*t]] * R[C[i + 228*t]] : R[B[i + 228*t]] + R[C[i + 228*t]];
R[i + 1142*t] = Op[i + 229*t] ? R[B[i + 229*t]] * R[C[i + 229*t]] : R[B[i + 229*t]] + R[C[i + 229*t]];
R[i + 1143*t] = Op[i + 230*t] ? R[B[i + 230*t]] * R[C[i + 230*t]] : R[B[i + 230*t]] + R[C[i + 230*t]];
R[i + 1144*t] = Op[i + 231*t] ? R[B[i + 231*t]] * R[C[i + 231*t]] : R[B[i + 231*t]] + R[C[i + 231*t]];
R[i + 1145*t] = Op[i + 232*t] ? R[B[i + 232*t]] * R[C[i + 232*t]] : R[B[i + 232*t]] + R[C[i + 232*t]];
R[i + 1146*t] = Op[i + 233*t] ? R[B[i + 233*t]] * R[C[i + 233*t]] : R[B[i + 233*t]] + R[C[i + 233*t]];
R[i + 1147*t] = Op[i + 234*t] ? R[B[i + 234*t]] * R[C[i + 234*t]] : R[B[i + 234*t]] + R[C[i + 234*t]];
R[i + 1148*t] = Op[i + 235*t] ? R[B[i + 235*t]] * R[C[i + 235*t]] : R[B[i + 235*t]] + R[C[i + 235*t]];
R[i + 1149*t] = Op[i + 236*t] ? R[B[i + 236*t]] * R[C[i + 236*t]] : R[B[i + 236*t]] + R[C[i + 236*t]];
R[i + 1150*t] = Op[i + 237*t] ? R[B[i + 237*t]] * R[C[i + 237*t]] : R[B[i + 237*t]] + R[C[i + 237*t]];
R[i + 1151*t] = Op[i + 238*t] ? R[B[i + 238*t]] * R[C[i + 238*t]] : R[B[i + 238*t]] + R[C[i + 238*t]];
R[i + 1152*t] = Op[i + 239*t] ? R[B[i + 239*t]] * R[C[i + 239*t]] : R[B[i + 239*t]] + R[C[i + 239*t]];
R[i + 1153*t] = Op[i + 240*t] ? R[B[i + 240*t]] * R[C[i + 240*t]] : R[B[i + 240*t]] + R[C[i + 240*t]];
R[i + 1154*t] = Op[i + 241*t] ? R[B[i + 241*t]] * R[C[i + 241*t]] : R[B[i + 241*t]] + R[C[i + 241*t]];
R[i + 1155*t] = Op[i + 242*t] ? R[B[i + 242*t]] * R[C[i + 242*t]] : R[B[i + 242*t]] + R[C[i + 242*t]];
R[i + 1156*t] = Op[i + 243*t] ? R[B[i + 243*t]] * R[C[i + 243*t]] : R[B[i + 243*t]] + R[C[i + 243*t]];
R[i + 1157*t] = Op[i + 244*t] ? R[B[i + 244*t]] * R[C[i + 244*t]] : R[B[i + 244*t]] + R[C[i + 244*t]];
R[i + 1158*t] = Op[i + 245*t] ? R[B[i + 245*t]] * R[C[i + 245*t]] : R[B[i + 245*t]] + R[C[i + 245*t]];
R[i + 1159*t] = Op[i + 246*t] ? R[B[i + 246*t]] * R[C[i + 246*t]] : R[B[i + 246*t]] + R[C[i + 246*t]];
R[i + 1160*t] = Op[i + 247*t] ? R[B[i + 247*t]] * R[C[i + 247*t]] : R[B[i + 247*t]] + R[C[i + 247*t]];
R[i + 1161*t] = Op[i + 248*t] ? R[B[i + 248*t]] * R[C[i + 248*t]] : R[B[i + 248*t]] + R[C[i + 248*t]];
R[i + 1162*t] = Op[i + 249*t] ? R[B[i + 249*t]] * R[C[i + 249*t]] : R[B[i + 249*t]] + R[C[i + 249*t]];
R[i + 1163*t] = Op[i + 250*t] ? R[B[i + 250*t]] * R[C[i + 250*t]] : R[B[i + 250*t]] + R[C[i + 250*t]];
R[i + 1164*t] = Op[i + 251*t] ? R[B[i + 251*t]] * R[C[i + 251*t]] : R[B[i + 251*t]] + R[C[i + 251*t]];
R[i + 1165*t] = Op[i + 252*t] ? R[B[i + 252*t]] * R[C[i + 252*t]] : R[B[i + 252*t]] + R[C[i + 252*t]];
R[i + 1166*t] = Op[i + 253*t] ? R[B[i + 253*t]] * R[C[i + 253*t]] : R[B[i + 253*t]] + R[C[i + 253*t]];
R[i + 1167*t] = Op[i + 254*t] ? R[B[i + 254*t]] * R[C[i + 254*t]] : R[B[i + 254*t]] + R[C[i + 254*t]];
R[i + 1168*t] = Op[i + 255*t] ? R[B[i + 255*t]] * R[C[i + 255*t]] : R[B[i + 255*t]] + R[C[i + 255*t]];
R[i + 1169*t] = Op[i + 256*t] ? R[B[i + 256*t]] * R[C[i + 256*t]] : R[B[i + 256*t]] + R[C[i + 256*t]];
R[i + 1170*t] = Op[i + 257*t] ? R[B[i + 257*t]] * R[C[i + 257*t]] : R[B[i + 257*t]] + R[C[i + 257*t]];
R[i + 1171*t] = Op[i + 258*t] ? R[B[i + 258*t]] * R[C[i + 258*t]] : R[B[i + 258*t]] + R[C[i + 258*t]];
R[i + 1172*t] = Op[i + 259*t] ? R[B[i + 259*t]] * R[C[i + 259*t]] : R[B[i + 259*t]] + R[C[i + 259*t]];
R[i + 1173*t] = Op[i + 260*t] ? R[B[i + 260*t]] * R[C[i + 260*t]] : R[B[i + 260*t]] + R[C[i + 260*t]];
R[i + 1174*t] = Op[i + 261*t] ? R[B[i + 261*t]] * R[C[i + 261*t]] : R[B[i + 261*t]] + R[C[i + 261*t]];
R[i + 1175*t] = Op[i + 262*t] ? R[B[i + 262*t]] * R[C[i + 262*t]] : R[B[i + 262*t]] + R[C[i + 262*t]];
R[i + 1176*t] = Op[i + 263*t] ? R[B[i + 263*t]] * R[C[i + 263*t]] : R[B[i + 263*t]] + R[C[i + 263*t]];
R[i + 1177*t] = Op[i + 264*t] ? R[B[i + 264*t]] * R[C[i + 264*t]] : R[B[i + 264*t]] + R[C[i + 264*t]];
R[i + 1178*t] = Op[i + 265*t] ? R[B[i + 265*t]] * R[C[i + 265*t]] : R[B[i + 265*t]] + R[C[i + 265*t]];
R[i + 1179*t] = Op[i + 266*t] ? R[B[i + 266*t]] * R[C[i + 266*t]] : R[B[i + 266*t]] + R[C[i + 266*t]];
R[i + 1180*t] = Op[i + 267*t] ? R[B[i + 267*t]] * R[C[i + 267*t]] : R[B[i + 267*t]] + R[C[i + 267*t]];
R[i + 1181*t] = Op[i + 268*t] ? R[B[i + 268*t]] * R[C[i + 268*t]] : R[B[i + 268*t]] + R[C[i + 268*t]];
R[i + 1182*t] = Op[i + 269*t] ? R[B[i + 269*t]] * R[C[i + 269*t]] : R[B[i + 269*t]] + R[C[i + 269*t]];
R[i + 1183*t] = Op[i + 270*t] ? R[B[i + 270*t]] * R[C[i + 270*t]] : R[B[i + 270*t]] + R[C[i + 270*t]];
R[i + 1184*t] = Op[i + 271*t] ? R[B[i + 271*t]] * R[C[i + 271*t]] : R[B[i + 271*t]] + R[C[i + 271*t]];
R[i + 1185*t] = Op[i + 272*t] ? R[B[i + 272*t]] * R[C[i + 272*t]] : R[B[i + 272*t]] + R[C[i + 272*t]];
R[i + 1186*t] = Op[i + 273*t] ? R[B[i + 273*t]] * R[C[i + 273*t]] : R[B[i + 273*t]] + R[C[i + 273*t]];
R[i + 1187*t] = Op[i + 274*t] ? R[B[i + 274*t]] * R[C[i + 274*t]] : R[B[i + 274*t]] + R[C[i + 274*t]];
R[i + 1188*t] = Op[i + 275*t] ? R[B[i + 275*t]] * R[C[i + 275*t]] : R[B[i + 275*t]] + R[C[i + 275*t]];
R[i + 1189*t] = Op[i + 276*t] ? R[B[i + 276*t]] * R[C[i + 276*t]] : R[B[i + 276*t]] + R[C[i + 276*t]];
R[i + 1190*t] = Op[i + 277*t] ? R[B[i + 277*t]] * R[C[i + 277*t]] : R[B[i + 277*t]] + R[C[i + 277*t]];
R[i + 1191*t] = Op[i + 278*t] ? R[B[i + 278*t]] * R[C[i + 278*t]] : R[B[i + 278*t]] + R[C[i + 278*t]];
R[i + 1192*t] = Op[i + 279*t] ? R[B[i + 279*t]] * R[C[i + 279*t]] : R[B[i + 279*t]] + R[C[i + 279*t]];
R[i + 1193*t] = Op[i + 280*t] ? R[B[i + 280*t]] * R[C[i + 280*t]] : R[B[i + 280*t]] + R[C[i + 280*t]];
__syncthreads();
R[i + 1194*t] = Op[i + 281*t] ? R[B[i + 281*t]] * R[C[i + 281*t]] : R[B[i + 281*t]] + R[C[i + 281*t]];
R[i + 1195*t] = Op[i + 282*t] ? R[B[i + 282*t]] * R[C[i + 282*t]] : R[B[i + 282*t]] + R[C[i + 282*t]];
R[i + 1196*t] = Op[i + 283*t] ? R[B[i + 283*t]] * R[C[i + 283*t]] : R[B[i + 283*t]] + R[C[i + 283*t]];
R[i + 1197*t] = Op[i + 284*t] ? R[B[i + 284*t]] * R[C[i + 284*t]] : R[B[i + 284*t]] + R[C[i + 284*t]];
R[i + 1198*t] = Op[i + 285*t] ? R[B[i + 285*t]] * R[C[i + 285*t]] : R[B[i + 285*t]] + R[C[i + 285*t]];
R[i + 1199*t] = Op[i + 286*t] ? R[B[i + 286*t]] * R[C[i + 286*t]] : R[B[i + 286*t]] + R[C[i + 286*t]];
R[i + 1200*t] = Op[i + 287*t] ? R[B[i + 287*t]] * R[C[i + 287*t]] : R[B[i + 287*t]] + R[C[i + 287*t]];
R[i + 1201*t] = Op[i + 288*t] ? R[B[i + 288*t]] * R[C[i + 288*t]] : R[B[i + 288*t]] + R[C[i + 288*t]];
R[i + 1202*t] = Op[i + 289*t] ? R[B[i + 289*t]] * R[C[i + 289*t]] : R[B[i + 289*t]] + R[C[i + 289*t]];
R[i + 1203*t] = Op[i + 290*t] ? R[B[i + 290*t]] * R[C[i + 290*t]] : R[B[i + 290*t]] + R[C[i + 290*t]];
R[i + 1204*t] = Op[i + 291*t] ? R[B[i + 291*t]] * R[C[i + 291*t]] : R[B[i + 291*t]] + R[C[i + 291*t]];
R[i + 1205*t] = Op[i + 292*t] ? R[B[i + 292*t]] * R[C[i + 292*t]] : R[B[i + 292*t]] + R[C[i + 292*t]];
R[i + 1206*t] = Op[i + 293*t] ? R[B[i + 293*t]] * R[C[i + 293*t]] : R[B[i + 293*t]] + R[C[i + 293*t]];
R[i + 1207*t] = Op[i + 294*t] ? R[B[i + 294*t]] * R[C[i + 294*t]] : R[B[i + 294*t]] + R[C[i + 294*t]];
R[i + 1208*t] = Op[i + 295*t] ? R[B[i + 295*t]] * R[C[i + 295*t]] : R[B[i + 295*t]] + R[C[i + 295*t]];
R[i + 1209*t] = Op[i + 296*t] ? R[B[i + 296*t]] * R[C[i + 296*t]] : R[B[i + 296*t]] + R[C[i + 296*t]];
R[i + 1210*t] = Op[i + 297*t] ? R[B[i + 297*t]] * R[C[i + 297*t]] : R[B[i + 297*t]] + R[C[i + 297*t]];
R[i + 1211*t] = Op[i + 298*t] ? R[B[i + 298*t]] * R[C[i + 298*t]] : R[B[i + 298*t]] + R[C[i + 298*t]];
R[i + 1212*t] = Op[i + 299*t] ? R[B[i + 299*t]] * R[C[i + 299*t]] : R[B[i + 299*t]] + R[C[i + 299*t]];
R[i + 1213*t] = Op[i + 300*t] ? R[B[i + 300*t]] * R[C[i + 300*t]] : R[B[i + 300*t]] + R[C[i + 300*t]];
R[i + 1214*t] = Op[i + 301*t] ? R[B[i + 301*t]] * R[C[i + 301*t]] : R[B[i + 301*t]] + R[C[i + 301*t]];
R[i + 1215*t] = Op[i + 302*t] ? R[B[i + 302*t]] * R[C[i + 302*t]] : R[B[i + 302*t]] + R[C[i + 302*t]];
R[i + 1216*t] = Op[i + 303*t] ? R[B[i + 303*t]] * R[C[i + 303*t]] : R[B[i + 303*t]] + R[C[i + 303*t]];
R[i + 1217*t] = Op[i + 304*t] ? R[B[i + 304*t]] * R[C[i + 304*t]] : R[B[i + 304*t]] + R[C[i + 304*t]];
R[i + 1218*t] = Op[i + 305*t] ? R[B[i + 305*t]] * R[C[i + 305*t]] : R[B[i + 305*t]] + R[C[i + 305*t]];
R[i + 1219*t] = Op[i + 306*t] ? R[B[i + 306*t]] * R[C[i + 306*t]] : R[B[i + 306*t]] + R[C[i + 306*t]];
R[i + 1220*t] = Op[i + 307*t] ? R[B[i + 307*t]] * R[C[i + 307*t]] : R[B[i + 307*t]] + R[C[i + 307*t]];
R[i + 1221*t] = Op[i + 308*t] ? R[B[i + 308*t]] * R[C[i + 308*t]] : R[B[i + 308*t]] + R[C[i + 308*t]];
R[i + 1222*t] = Op[i + 309*t] ? R[B[i + 309*t]] * R[C[i + 309*t]] : R[B[i + 309*t]] + R[C[i + 309*t]];
R[i + 1223*t] = Op[i + 310*t] ? R[B[i + 310*t]] * R[C[i + 310*t]] : R[B[i + 310*t]] + R[C[i + 310*t]];
R[i + 1224*t] = Op[i + 311*t] ? R[B[i + 311*t]] * R[C[i + 311*t]] : R[B[i + 311*t]] + R[C[i + 311*t]];
R[i + 1225*t] = Op[i + 312*t] ? R[B[i + 312*t]] * R[C[i + 312*t]] : R[B[i + 312*t]] + R[C[i + 312*t]];
R[i + 1226*t] = Op[i + 313*t] ? R[B[i + 313*t]] * R[C[i + 313*t]] : R[B[i + 313*t]] + R[C[i + 313*t]];
R[i + 1227*t] = Op[i + 314*t] ? R[B[i + 314*t]] * R[C[i + 314*t]] : R[B[i + 314*t]] + R[C[i + 314*t]];
R[i + 1228*t] = Op[i + 315*t] ? R[B[i + 315*t]] * R[C[i + 315*t]] : R[B[i + 315*t]] + R[C[i + 315*t]];
R[i + 1229*t] = Op[i + 316*t] ? R[B[i + 316*t]] * R[C[i + 316*t]] : R[B[i + 316*t]] + R[C[i + 316*t]];
R[i + 1230*t] = Op[i + 317*t] ? R[B[i + 317*t]] * R[C[i + 317*t]] : R[B[i + 317*t]] + R[C[i + 317*t]];
R[i + 1231*t] = Op[i + 318*t] ? R[B[i + 318*t]] * R[C[i + 318*t]] : R[B[i + 318*t]] + R[C[i + 318*t]];
R[i + 1232*t] = Op[i + 319*t] ? R[B[i + 319*t]] * R[C[i + 319*t]] : R[B[i + 319*t]] + R[C[i + 319*t]];
R[i + 1233*t] = Op[i + 320*t] ? R[B[i + 320*t]] * R[C[i + 320*t]] : R[B[i + 320*t]] + R[C[i + 320*t]];
R[i + 1234*t] = Op[i + 321*t] ? R[B[i + 321*t]] * R[C[i + 321*t]] : R[B[i + 321*t]] + R[C[i + 321*t]];
R[i + 1235*t] = Op[i + 322*t] ? R[B[i + 322*t]] * R[C[i + 322*t]] : R[B[i + 322*t]] + R[C[i + 322*t]];
R[i + 1236*t] = Op[i + 323*t] ? R[B[i + 323*t]] * R[C[i + 323*t]] : R[B[i + 323*t]] + R[C[i + 323*t]];
R[i + 1237*t] = Op[i + 324*t] ? R[B[i + 324*t]] * R[C[i + 324*t]] : R[B[i + 324*t]] + R[C[i + 324*t]];
R[i + 1238*t] = Op[i + 325*t] ? R[B[i + 325*t]] * R[C[i + 325*t]] : R[B[i + 325*t]] + R[C[i + 325*t]];
R[i + 1239*t] = Op[i + 326*t] ? R[B[i + 326*t]] * R[C[i + 326*t]] : R[B[i + 326*t]] + R[C[i + 326*t]];
R[i + 1240*t] = Op[i + 327*t] ? R[B[i + 327*t]] * R[C[i + 327*t]] : R[B[i + 327*t]] + R[C[i + 327*t]];
R[i + 1241*t] = Op[i + 328*t] ? R[B[i + 328*t]] * R[C[i + 328*t]] : R[B[i + 328*t]] + R[C[i + 328*t]];
R[i + 1242*t] = Op[i + 329*t] ? R[B[i + 329*t]] * R[C[i + 329*t]] : R[B[i + 329*t]] + R[C[i + 329*t]];
R[i + 1243*t] = Op[i + 330*t] ? R[B[i + 330*t]] * R[C[i + 330*t]] : R[B[i + 330*t]] + R[C[i + 330*t]];
R[i + 1244*t] = Op[i + 331*t] ? R[B[i + 331*t]] * R[C[i + 331*t]] : R[B[i + 331*t]] + R[C[i + 331*t]];
R[i + 1245*t] = Op[i + 332*t] ? R[B[i + 332*t]] * R[C[i + 332*t]] : R[B[i + 332*t]] + R[C[i + 332*t]];
R[i + 1246*t] = Op[i + 333*t] ? R[B[i + 333*t]] * R[C[i + 333*t]] : R[B[i + 333*t]] + R[C[i + 333*t]];
R[i + 1247*t] = Op[i + 334*t] ? R[B[i + 334*t]] * R[C[i + 334*t]] : R[B[i + 334*t]] + R[C[i + 334*t]];
R[i + 1248*t] = Op[i + 335*t] ? R[B[i + 335*t]] * R[C[i + 335*t]] : R[B[i + 335*t]] + R[C[i + 335*t]];
R[i + 1249*t] = Op[i + 336*t] ? R[B[i + 336*t]] * R[C[i + 336*t]] : R[B[i + 336*t]] + R[C[i + 336*t]];
R[i + 1250*t] = Op[i + 337*t] ? R[B[i + 337*t]] * R[C[i + 337*t]] : R[B[i + 337*t]] + R[C[i + 337*t]];
R[i + 1251*t] = Op[i + 338*t] ? R[B[i + 338*t]] * R[C[i + 338*t]] : R[B[i + 338*t]] + R[C[i + 338*t]];
R[i + 1252*t] = Op[i + 339*t] ? R[B[i + 339*t]] * R[C[i + 339*t]] : R[B[i + 339*t]] + R[C[i + 339*t]];
R[i + 1253*t] = Op[i + 340*t] ? R[B[i + 340*t]] * R[C[i + 340*t]] : R[B[i + 340*t]] + R[C[i + 340*t]];
R[i + 1254*t] = Op[i + 341*t] ? R[B[i + 341*t]] * R[C[i + 341*t]] : R[B[i + 341*t]] + R[C[i + 341*t]];
R[i + 1255*t] = Op[i + 342*t] ? R[B[i + 342*t]] * R[C[i + 342*t]] : R[B[i + 342*t]] + R[C[i + 342*t]];
R[i + 1256*t] = Op[i + 343*t] ? R[B[i + 343*t]] * R[C[i + 343*t]] : R[B[i + 343*t]] + R[C[i + 343*t]];
R[i + 1257*t] = Op[i + 344*t] ? R[B[i + 344*t]] * R[C[i + 344*t]] : R[B[i + 344*t]] + R[C[i + 344*t]];
R[i + 1258*t] = Op[i + 345*t] ? R[B[i + 345*t]] * R[C[i + 345*t]] : R[B[i + 345*t]] + R[C[i + 345*t]];
R[i + 1259*t] = Op[i + 346*t] ? R[B[i + 346*t]] * R[C[i + 346*t]] : R[B[i + 346*t]] + R[C[i + 346*t]];
R[i + 1260*t] = Op[i + 347*t] ? R[B[i + 347*t]] * R[C[i + 347*t]] : R[B[i + 347*t]] + R[C[i + 347*t]];
R[i + 1261*t] = Op[i + 348*t] ? R[B[i + 348*t]] * R[C[i + 348*t]] : R[B[i + 348*t]] + R[C[i + 348*t]];
R[i + 1262*t] = Op[i + 349*t] ? R[B[i + 349*t]] * R[C[i + 349*t]] : R[B[i + 349*t]] + R[C[i + 349*t]];
R[i + 1263*t] = Op[i + 350*t] ? R[B[i + 350*t]] * R[C[i + 350*t]] : R[B[i + 350*t]] + R[C[i + 350*t]];
R[i + 1264*t] = Op[i + 351*t] ? R[B[i + 351*t]] * R[C[i + 351*t]] : R[B[i + 351*t]] + R[C[i + 351*t]];
R[i + 1265*t] = Op[i + 352*t] ? R[B[i + 352*t]] * R[C[i + 352*t]] : R[B[i + 352*t]] + R[C[i + 352*t]];
R[i + 1266*t] = Op[i + 353*t] ? R[B[i + 353*t]] * R[C[i + 353*t]] : R[B[i + 353*t]] + R[C[i + 353*t]];
R[i + 1267*t] = Op[i + 354*t] ? R[B[i + 354*t]] * R[C[i + 354*t]] : R[B[i + 354*t]] + R[C[i + 354*t]];
R[i + 1268*t] = Op[i + 355*t] ? R[B[i + 355*t]] * R[C[i + 355*t]] : R[B[i + 355*t]] + R[C[i + 355*t]];
R[i + 1269*t] = Op[i + 356*t] ? R[B[i + 356*t]] * R[C[i + 356*t]] : R[B[i + 356*t]] + R[C[i + 356*t]];
R[i + 1270*t] = Op[i + 357*t] ? R[B[i + 357*t]] * R[C[i + 357*t]] : R[B[i + 357*t]] + R[C[i + 357*t]];
R[i + 1271*t] = Op[i + 358*t] ? R[B[i + 358*t]] * R[C[i + 358*t]] : R[B[i + 358*t]] + R[C[i + 358*t]];
R[i + 1272*t] = Op[i + 359*t] ? R[B[i + 359*t]] * R[C[i + 359*t]] : R[B[i + 359*t]] + R[C[i + 359*t]];
R[i + 1273*t] = Op[i + 360*t] ? R[B[i + 360*t]] * R[C[i + 360*t]] : R[B[i + 360*t]] + R[C[i + 360*t]];
R[i + 1274*t] = Op[i + 361*t] ? R[B[i + 361*t]] * R[C[i + 361*t]] : R[B[i + 361*t]] + R[C[i + 361*t]];
R[i + 1275*t] = Op[i + 362*t] ? R[B[i + 362*t]] * R[C[i + 362*t]] : R[B[i + 362*t]] + R[C[i + 362*t]];
R[i + 1276*t] = Op[i + 363*t] ? R[B[i + 363*t]] * R[C[i + 363*t]] : R[B[i + 363*t]] + R[C[i + 363*t]];
R[i + 1277*t] = Op[i + 364*t] ? R[B[i + 364*t]] * R[C[i + 364*t]] : R[B[i + 364*t]] + R[C[i + 364*t]];
R[i + 1278*t] = Op[i + 365*t] ? R[B[i + 365*t]] * R[C[i + 365*t]] : R[B[i + 365*t]] + R[C[i + 365*t]];
R[i + 1279*t] = Op[i + 366*t] ? R[B[i + 366*t]] * R[C[i + 366*t]] : R[B[i + 366*t]] + R[C[i + 366*t]];
R[i + 1280*t] = Op[i + 367*t] ? R[B[i + 367*t]] * R[C[i + 367*t]] : R[B[i + 367*t]] + R[C[i + 367*t]];
R[i + 1281*t] = Op[i + 368*t] ? R[B[i + 368*t]] * R[C[i + 368*t]] : R[B[i + 368*t]] + R[C[i + 368*t]];
R[i + 1282*t] = Op[i + 369*t] ? R[B[i + 369*t]] * R[C[i + 369*t]] : R[B[i + 369*t]] + R[C[i + 369*t]];
R[i + 1283*t] = Op[i + 370*t] ? R[B[i + 370*t]] * R[C[i + 370*t]] : R[B[i + 370*t]] + R[C[i + 370*t]];
R[i + 1284*t] = Op[i + 371*t] ? R[B[i + 371*t]] * R[C[i + 371*t]] : R[B[i + 371*t]] + R[C[i + 371*t]];
R[i + 1285*t] = Op[i + 372*t] ? R[B[i + 372*t]] * R[C[i + 372*t]] : R[B[i + 372*t]] + R[C[i + 372*t]];
R[i + 1286*t] = Op[i + 373*t] ? R[B[i + 373*t]] * R[C[i + 373*t]] : R[B[i + 373*t]] + R[C[i + 373*t]];
R[i + 1287*t] = Op[i + 374*t] ? R[B[i + 374*t]] * R[C[i + 374*t]] : R[B[i + 374*t]] + R[C[i + 374*t]];
R[i + 1288*t] = Op[i + 375*t] ? R[B[i + 375*t]] * R[C[i + 375*t]] : R[B[i + 375*t]] + R[C[i + 375*t]];
R[i + 1289*t] = Op[i + 376*t] ? R[B[i + 376*t]] * R[C[i + 376*t]] : R[B[i + 376*t]] + R[C[i + 376*t]];
R[i + 1290*t] = Op[i + 377*t] ? R[B[i + 377*t]] * R[C[i + 377*t]] : R[B[i + 377*t]] + R[C[i + 377*t]];
R[i + 1291*t] = Op[i + 378*t] ? R[B[i + 378*t]] * R[C[i + 378*t]] : R[B[i + 378*t]] + R[C[i + 378*t]];
R[i + 1292*t] = Op[i + 379*t] ? R[B[i + 379*t]] * R[C[i + 379*t]] : R[B[i + 379*t]] + R[C[i + 379*t]];
R[i + 1293*t] = Op[i + 380*t] ? R[B[i + 380*t]] * R[C[i + 380*t]] : R[B[i + 380*t]] + R[C[i + 380*t]];
R[i + 1294*t] = Op[i + 381*t] ? R[B[i + 381*t]] * R[C[i + 381*t]] : R[B[i + 381*t]] + R[C[i + 381*t]];
R[i + 1295*t] = Op[i + 382*t] ? R[B[i + 382*t]] * R[C[i + 382*t]] : R[B[i + 382*t]] + R[C[i + 382*t]];
R[i + 1296*t] = Op[i + 383*t] ? R[B[i + 383*t]] * R[C[i + 383*t]] : R[B[i + 383*t]] + R[C[i + 383*t]];
R[i + 1297*t] = Op[i + 384*t] ? R[B[i + 384*t]] * R[C[i + 384*t]] : R[B[i + 384*t]] + R[C[i + 384*t]];
R[i + 1298*t] = Op[i + 385*t] ? R[B[i + 385*t]] * R[C[i + 385*t]] : R[B[i + 385*t]] + R[C[i + 385*t]];
R[i + 1299*t] = Op[i + 386*t] ? R[B[i + 386*t]] * R[C[i + 386*t]] : R[B[i + 386*t]] + R[C[i + 386*t]];
R[i + 1300*t] = Op[i + 387*t] ? R[B[i + 387*t]] * R[C[i + 387*t]] : R[B[i + 387*t]] + R[C[i + 387*t]];
R[i + 1301*t] = Op[i + 388*t] ? R[B[i + 388*t]] * R[C[i + 388*t]] : R[B[i + 388*t]] + R[C[i + 388*t]];
R[i + 1302*t] = Op[i + 389*t] ? R[B[i + 389*t]] * R[C[i + 389*t]] : R[B[i + 389*t]] + R[C[i + 389*t]];
R[i + 1303*t] = Op[i + 390*t] ? R[B[i + 390*t]] * R[C[i + 390*t]] : R[B[i + 390*t]] + R[C[i + 390*t]];
R[i + 1304*t] = Op[i + 391*t] ? R[B[i + 391*t]] * R[C[i + 391*t]] : R[B[i + 391*t]] + R[C[i + 391*t]];
R[i + 1305*t] = Op[i + 392*t] ? R[B[i + 392*t]] * R[C[i + 392*t]] : R[B[i + 392*t]] + R[C[i + 392*t]];
R[i + 1306*t] = Op[i + 393*t] ? R[B[i + 393*t]] * R[C[i + 393*t]] : R[B[i + 393*t]] + R[C[i + 393*t]];
R[i + 1307*t] = Op[i + 394*t] ? R[B[i + 394*t]] * R[C[i + 394*t]] : R[B[i + 394*t]] + R[C[i + 394*t]];
R[i + 1308*t] = Op[i + 395*t] ? R[B[i + 395*t]] * R[C[i + 395*t]] : R[B[i + 395*t]] + R[C[i + 395*t]];
R[i + 1309*t] = Op[i + 396*t] ? R[B[i + 396*t]] * R[C[i + 396*t]] : R[B[i + 396*t]] + R[C[i + 396*t]];
R[i + 1310*t] = Op[i + 397*t] ? R[B[i + 397*t]] * R[C[i + 397*t]] : R[B[i + 397*t]] + R[C[i + 397*t]];
R[i + 1311*t] = Op[i + 398*t] ? R[B[i + 398*t]] * R[C[i + 398*t]] : R[B[i + 398*t]] + R[C[i + 398*t]];
R[i + 1312*t] = Op[i + 399*t] ? R[B[i + 399*t]] * R[C[i + 399*t]] : R[B[i + 399*t]] + R[C[i + 399*t]];
R[i + 1313*t] = Op[i + 400*t] ? R[B[i + 400*t]] * R[C[i + 400*t]] : R[B[i + 400*t]] + R[C[i + 400*t]];
R[i + 1314*t] = Op[i + 401*t] ? R[B[i + 401*t]] * R[C[i + 401*t]] : R[B[i + 401*t]] + R[C[i + 401*t]];
R[i + 1315*t] = Op[i + 402*t] ? R[B[i + 402*t]] * R[C[i + 402*t]] : R[B[i + 402*t]] + R[C[i + 402*t]];
R[i + 1316*t] = Op[i + 403*t] ? R[B[i + 403*t]] * R[C[i + 403*t]] : R[B[i + 403*t]] + R[C[i + 403*t]];
R[i + 1317*t] = Op[i + 404*t] ? R[B[i + 404*t]] * R[C[i + 404*t]] : R[B[i + 404*t]] + R[C[i + 404*t]];
R[i + 1318*t] = Op[i + 405*t] ? R[B[i + 405*t]] * R[C[i + 405*t]] : R[B[i + 405*t]] + R[C[i + 405*t]];
R[i + 1319*t] = Op[i + 406*t] ? R[B[i + 406*t]] * R[C[i + 406*t]] : R[B[i + 406*t]] + R[C[i + 406*t]];
R[i + 1320*t] = Op[i + 407*t] ? R[B[i + 407*t]] * R[C[i + 407*t]] : R[B[i + 407*t]] + R[C[i + 407*t]];
R[i + 1321*t] = Op[i + 408*t] ? R[B[i + 408*t]] * R[C[i + 408*t]] : R[B[i + 408*t]] + R[C[i + 408*t]];
R[i + 1322*t] = Op[i + 409*t] ? R[B[i + 409*t]] * R[C[i + 409*t]] : R[B[i + 409*t]] + R[C[i + 409*t]];
R[i + 1323*t] = Op[i + 410*t] ? R[B[i + 410*t]] * R[C[i + 410*t]] : R[B[i + 410*t]] + R[C[i + 410*t]];
R[i + 1324*t] = Op[i + 411*t] ? R[B[i + 411*t]] * R[C[i + 411*t]] : R[B[i + 411*t]] + R[C[i + 411*t]];
R[i + 1325*t] = Op[i + 412*t] ? R[B[i + 412*t]] * R[C[i + 412*t]] : R[B[i + 412*t]] + R[C[i + 412*t]];
R[i + 1326*t] = Op[i + 413*t] ? R[B[i + 413*t]] * R[C[i + 413*t]] : R[B[i + 413*t]] + R[C[i + 413*t]];
R[i + 1327*t] = Op[i + 414*t] ? R[B[i + 414*t]] * R[C[i + 414*t]] : R[B[i + 414*t]] + R[C[i + 414*t]];
R[i + 1328*t] = Op[i + 415*t] ? R[B[i + 415*t]] * R[C[i + 415*t]] : R[B[i + 415*t]] + R[C[i + 415*t]];
R[i + 1329*t] = Op[i + 416*t] ? R[B[i + 416*t]] * R[C[i + 416*t]] : R[B[i + 416*t]] + R[C[i + 416*t]];
R[i + 1330*t] = Op[i + 417*t] ? R[B[i + 417*t]] * R[C[i + 417*t]] : R[B[i + 417*t]] + R[C[i + 417*t]];
R[i + 1331*t] = Op[i + 418*t] ? R[B[i + 418*t]] * R[C[i + 418*t]] : R[B[i + 418*t]] + R[C[i + 418*t]];
R[i + 1332*t] = Op[i + 419*t] ? R[B[i + 419*t]] * R[C[i + 419*t]] : R[B[i + 419*t]] + R[C[i + 419*t]];
R[i + 1333*t] = Op[i + 420*t] ? R[B[i + 420*t]] * R[C[i + 420*t]] : R[B[i + 420*t]] + R[C[i + 420*t]];
R[i + 1334*t] = Op[i + 421*t] ? R[B[i + 421*t]] * R[C[i + 421*t]] : R[B[i + 421*t]] + R[C[i + 421*t]];
R[i + 1335*t] = Op[i + 422*t] ? R[B[i + 422*t]] * R[C[i + 422*t]] : R[B[i + 422*t]] + R[C[i + 422*t]];
R[i + 1336*t] = Op[i + 423*t] ? R[B[i + 423*t]] * R[C[i + 423*t]] : R[B[i + 423*t]] + R[C[i + 423*t]];
R[i + 1337*t] = Op[i + 424*t] ? R[B[i + 424*t]] * R[C[i + 424*t]] : R[B[i + 424*t]] + R[C[i + 424*t]];
R[i + 1338*t] = Op[i + 425*t] ? R[B[i + 425*t]] * R[C[i + 425*t]] : R[B[i + 425*t]] + R[C[i + 425*t]];
R[i + 1339*t] = Op[i + 426*t] ? R[B[i + 426*t]] * R[C[i + 426*t]] : R[B[i + 426*t]] + R[C[i + 426*t]];
R[i + 1340*t] = Op[i + 427*t] ? R[B[i + 427*t]] * R[C[i + 427*t]] : R[B[i + 427*t]] + R[C[i + 427*t]];
R[i + 1341*t] = Op[i + 428*t] ? R[B[i + 428*t]] * R[C[i + 428*t]] : R[B[i + 428*t]] + R[C[i + 428*t]];
R[i + 1342*t] = Op[i + 429*t] ? R[B[i + 429*t]] * R[C[i + 429*t]] : R[B[i + 429*t]] + R[C[i + 429*t]];
R[i + 1343*t] = Op[i + 430*t] ? R[B[i + 430*t]] * R[C[i + 430*t]] : R[B[i + 430*t]] + R[C[i + 430*t]];
R[i + 1344*t] = Op[i + 431*t] ? R[B[i + 431*t]] * R[C[i + 431*t]] : R[B[i + 431*t]] + R[C[i + 431*t]];
R[i + 1345*t] = Op[i + 432*t] ? R[B[i + 432*t]] * R[C[i + 432*t]] : R[B[i + 432*t]] + R[C[i + 432*t]];
R[i + 1346*t] = Op[i + 433*t] ? R[B[i + 433*t]] * R[C[i + 433*t]] : R[B[i + 433*t]] + R[C[i + 433*t]];
R[i + 1347*t] = Op[i + 434*t] ? R[B[i + 434*t]] * R[C[i + 434*t]] : R[B[i + 434*t]] + R[C[i + 434*t]];
R[i + 1348*t] = Op[i + 435*t] ? R[B[i + 435*t]] * R[C[i + 435*t]] : R[B[i + 435*t]] + R[C[i + 435*t]];
R[i + 1349*t] = Op[i + 436*t] ? R[B[i + 436*t]] * R[C[i + 436*t]] : R[B[i + 436*t]] + R[C[i + 436*t]];
R[i + 1350*t] = Op[i + 437*t] ? R[B[i + 437*t]] * R[C[i + 437*t]] : R[B[i + 437*t]] + R[C[i + 437*t]];
R[i + 1351*t] = Op[i + 438*t] ? R[B[i + 438*t]] * R[C[i + 438*t]] : R[B[i + 438*t]] + R[C[i + 438*t]];
R[i + 1352*t] = Op[i + 439*t] ? R[B[i + 439*t]] * R[C[i + 439*t]] : R[B[i + 439*t]] + R[C[i + 439*t]];
R[i + 1353*t] = Op[i + 440*t] ? R[B[i + 440*t]] * R[C[i + 440*t]] : R[B[i + 440*t]] + R[C[i + 440*t]];
R[i + 1354*t] = Op[i + 441*t] ? R[B[i + 441*t]] * R[C[i + 441*t]] : R[B[i + 441*t]] + R[C[i + 441*t]];
R[i + 1355*t] = Op[i + 442*t] ? R[B[i + 442*t]] * R[C[i + 442*t]] : R[B[i + 442*t]] + R[C[i + 442*t]];
R[i + 1356*t] = Op[i + 443*t] ? R[B[i + 443*t]] * R[C[i + 443*t]] : R[B[i + 443*t]] + R[C[i + 443*t]];
R[i + 1357*t] = Op[i + 444*t] ? R[B[i + 444*t]] * R[C[i + 444*t]] : R[B[i + 444*t]] + R[C[i + 444*t]];
__syncthreads();
R[i + 1358*t] = Op[i + 445*t] ? R[B[i + 445*t]] * R[C[i + 445*t]] : R[B[i + 445*t]] + R[C[i + 445*t]];
R[i + 1359*t] = Op[i + 446*t] ? R[B[i + 446*t]] * R[C[i + 446*t]] : R[B[i + 446*t]] + R[C[i + 446*t]];
R[i + 1360*t] = Op[i + 447*t] ? R[B[i + 447*t]] * R[C[i + 447*t]] : R[B[i + 447*t]] + R[C[i + 447*t]];
R[i + 1361*t] = Op[i + 448*t] ? R[B[i + 448*t]] * R[C[i + 448*t]] : R[B[i + 448*t]] + R[C[i + 448*t]];
R[i + 1362*t] = Op[i + 449*t] ? R[B[i + 449*t]] * R[C[i + 449*t]] : R[B[i + 449*t]] + R[C[i + 449*t]];
R[i + 1363*t] = Op[i + 450*t] ? R[B[i + 450*t]] * R[C[i + 450*t]] : R[B[i + 450*t]] + R[C[i + 450*t]];
R[i + 1364*t] = Op[i + 451*t] ? R[B[i + 451*t]] * R[C[i + 451*t]] : R[B[i + 451*t]] + R[C[i + 451*t]];
R[i + 1365*t] = Op[i + 452*t] ? R[B[i + 452*t]] * R[C[i + 452*t]] : R[B[i + 452*t]] + R[C[i + 452*t]];
R[i + 1366*t] = Op[i + 453*t] ? R[B[i + 453*t]] * R[C[i + 453*t]] : R[B[i + 453*t]] + R[C[i + 453*t]];
R[i + 1367*t] = Op[i + 454*t] ? R[B[i + 454*t]] * R[C[i + 454*t]] : R[B[i + 454*t]] + R[C[i + 454*t]];
R[i + 1368*t] = Op[i + 455*t] ? R[B[i + 455*t]] * R[C[i + 455*t]] : R[B[i + 455*t]] + R[C[i + 455*t]];
R[i + 1369*t] = Op[i + 456*t] ? R[B[i + 456*t]] * R[C[i + 456*t]] : R[B[i + 456*t]] + R[C[i + 456*t]];
R[i + 1370*t] = Op[i + 457*t] ? R[B[i + 457*t]] * R[C[i + 457*t]] : R[B[i + 457*t]] + R[C[i + 457*t]];
R[i + 1371*t] = Op[i + 458*t] ? R[B[i + 458*t]] * R[C[i + 458*t]] : R[B[i + 458*t]] + R[C[i + 458*t]];
R[i + 1372*t] = Op[i + 459*t] ? R[B[i + 459*t]] * R[C[i + 459*t]] : R[B[i + 459*t]] + R[C[i + 459*t]];
R[i + 1373*t] = Op[i + 460*t] ? R[B[i + 460*t]] * R[C[i + 460*t]] : R[B[i + 460*t]] + R[C[i + 460*t]];
R[i + 1374*t] = Op[i + 461*t] ? R[B[i + 461*t]] * R[C[i + 461*t]] : R[B[i + 461*t]] + R[C[i + 461*t]];
R[i + 1375*t] = Op[i + 462*t] ? R[B[i + 462*t]] * R[C[i + 462*t]] : R[B[i + 462*t]] + R[C[i + 462*t]];
R[i + 1376*t] = Op[i + 463*t] ? R[B[i + 463*t]] * R[C[i + 463*t]] : R[B[i + 463*t]] + R[C[i + 463*t]];
R[i + 1377*t] = Op[i + 464*t] ? R[B[i + 464*t]] * R[C[i + 464*t]] : R[B[i + 464*t]] + R[C[i + 464*t]];
R[i + 1378*t] = Op[i + 465*t] ? R[B[i + 465*t]] * R[C[i + 465*t]] : R[B[i + 465*t]] + R[C[i + 465*t]];
R[i + 1379*t] = Op[i + 466*t] ? R[B[i + 466*t]] * R[C[i + 466*t]] : R[B[i + 466*t]] + R[C[i + 466*t]];
R[i + 1380*t] = Op[i + 467*t] ? R[B[i + 467*t]] * R[C[i + 467*t]] : R[B[i + 467*t]] + R[C[i + 467*t]];
R[i + 1381*t] = Op[i + 468*t] ? R[B[i + 468*t]] * R[C[i + 468*t]] : R[B[i + 468*t]] + R[C[i + 468*t]];
R[i + 1382*t] = Op[i + 469*t] ? R[B[i + 469*t]] * R[C[i + 469*t]] : R[B[i + 469*t]] + R[C[i + 469*t]];
R[i + 1383*t] = Op[i + 470*t] ? R[B[i + 470*t]] * R[C[i + 470*t]] : R[B[i + 470*t]] + R[C[i + 470*t]];
R[i + 1384*t] = Op[i + 471*t] ? R[B[i + 471*t]] * R[C[i + 471*t]] : R[B[i + 471*t]] + R[C[i + 471*t]];
R[i + 1385*t] = Op[i + 472*t] ? R[B[i + 472*t]] * R[C[i + 472*t]] : R[B[i + 472*t]] + R[C[i + 472*t]];
R[i + 1386*t] = Op[i + 473*t] ? R[B[i + 473*t]] * R[C[i + 473*t]] : R[B[i + 473*t]] + R[C[i + 473*t]];
R[i + 1387*t] = Op[i + 474*t] ? R[B[i + 474*t]] * R[C[i + 474*t]] : R[B[i + 474*t]] + R[C[i + 474*t]];
R[i + 1388*t] = Op[i + 475*t] ? R[B[i + 475*t]] * R[C[i + 475*t]] : R[B[i + 475*t]] + R[C[i + 475*t]];
R[i + 1389*t] = Op[i + 476*t] ? R[B[i + 476*t]] * R[C[i + 476*t]] : R[B[i + 476*t]] + R[C[i + 476*t]];
R[i + 1390*t] = Op[i + 477*t] ? R[B[i + 477*t]] * R[C[i + 477*t]] : R[B[i + 477*t]] + R[C[i + 477*t]];
R[i + 1391*t] = Op[i + 478*t] ? R[B[i + 478*t]] * R[C[i + 478*t]] : R[B[i + 478*t]] + R[C[i + 478*t]];
R[i + 1392*t] = Op[i + 479*t] ? R[B[i + 479*t]] * R[C[i + 479*t]] : R[B[i + 479*t]] + R[C[i + 479*t]];
R[i + 1393*t] = Op[i + 480*t] ? R[B[i + 480*t]] * R[C[i + 480*t]] : R[B[i + 480*t]] + R[C[i + 480*t]];
R[i + 1394*t] = Op[i + 481*t] ? R[B[i + 481*t]] * R[C[i + 481*t]] : R[B[i + 481*t]] + R[C[i + 481*t]];
R[i + 1395*t] = Op[i + 482*t] ? R[B[i + 482*t]] * R[C[i + 482*t]] : R[B[i + 482*t]] + R[C[i + 482*t]];
R[i + 1396*t] = Op[i + 483*t] ? R[B[i + 483*t]] * R[C[i + 483*t]] : R[B[i + 483*t]] + R[C[i + 483*t]];
R[i + 1397*t] = Op[i + 484*t] ? R[B[i + 484*t]] * R[C[i + 484*t]] : R[B[i + 484*t]] + R[C[i + 484*t]];
R[i + 1398*t] = Op[i + 485*t] ? R[B[i + 485*t]] * R[C[i + 485*t]] : R[B[i + 485*t]] + R[C[i + 485*t]];
R[i + 1399*t] = Op[i + 486*t] ? R[B[i + 486*t]] * R[C[i + 486*t]] : R[B[i + 486*t]] + R[C[i + 486*t]];
R[i + 1400*t] = Op[i + 487*t] ? R[B[i + 487*t]] * R[C[i + 487*t]] : R[B[i + 487*t]] + R[C[i + 487*t]];
R[i + 1401*t] = Op[i + 488*t] ? R[B[i + 488*t]] * R[C[i + 488*t]] : R[B[i + 488*t]] + R[C[i + 488*t]];
R[i + 1402*t] = Op[i + 489*t] ? R[B[i + 489*t]] * R[C[i + 489*t]] : R[B[i + 489*t]] + R[C[i + 489*t]];
R[i + 1403*t] = Op[i + 490*t] ? R[B[i + 490*t]] * R[C[i + 490*t]] : R[B[i + 490*t]] + R[C[i + 490*t]];
R[i + 1404*t] = Op[i + 491*t] ? R[B[i + 491*t]] * R[C[i + 491*t]] : R[B[i + 491*t]] + R[C[i + 491*t]];
R[i + 1405*t] = Op[i + 492*t] ? R[B[i + 492*t]] * R[C[i + 492*t]] : R[B[i + 492*t]] + R[C[i + 492*t]];
R[i + 1406*t] = Op[i + 493*t] ? R[B[i + 493*t]] * R[C[i + 493*t]] : R[B[i + 493*t]] + R[C[i + 493*t]];
R[i + 1407*t] = Op[i + 494*t] ? R[B[i + 494*t]] * R[C[i + 494*t]] : R[B[i + 494*t]] + R[C[i + 494*t]];
R[i + 1408*t] = Op[i + 495*t] ? R[B[i + 495*t]] * R[C[i + 495*t]] : R[B[i + 495*t]] + R[C[i + 495*t]];
R[i + 1409*t] = Op[i + 496*t] ? R[B[i + 496*t]] * R[C[i + 496*t]] : R[B[i + 496*t]] + R[C[i + 496*t]];
R[i + 1410*t] = Op[i + 497*t] ? R[B[i + 497*t]] * R[C[i + 497*t]] : R[B[i + 497*t]] + R[C[i + 497*t]];
R[i + 1411*t] = Op[i + 498*t] ? R[B[i + 498*t]] * R[C[i + 498*t]] : R[B[i + 498*t]] + R[C[i + 498*t]];
R[i + 1412*t] = Op[i + 499*t] ? R[B[i + 499*t]] * R[C[i + 499*t]] : R[B[i + 499*t]] + R[C[i + 499*t]];
R[i + 1413*t] = Op[i + 500*t] ? R[B[i + 500*t]] * R[C[i + 500*t]] : R[B[i + 500*t]] + R[C[i + 500*t]];
R[i + 1414*t] = Op[i + 501*t] ? R[B[i + 501*t]] * R[C[i + 501*t]] : R[B[i + 501*t]] + R[C[i + 501*t]];
R[i + 1415*t] = Op[i + 502*t] ? R[B[i + 502*t]] * R[C[i + 502*t]] : R[B[i + 502*t]] + R[C[i + 502*t]];
R[i + 1416*t] = Op[i + 503*t] ? R[B[i + 503*t]] * R[C[i + 503*t]] : R[B[i + 503*t]] + R[C[i + 503*t]];
R[i + 1417*t] = Op[i + 504*t] ? R[B[i + 504*t]] * R[C[i + 504*t]] : R[B[i + 504*t]] + R[C[i + 504*t]];
R[i + 1418*t] = Op[i + 505*t] ? R[B[i + 505*t]] * R[C[i + 505*t]] : R[B[i + 505*t]] + R[C[i + 505*t]];
R[i + 1419*t] = Op[i + 506*t] ? R[B[i + 506*t]] * R[C[i + 506*t]] : R[B[i + 506*t]] + R[C[i + 506*t]];
R[i + 1420*t] = Op[i + 507*t] ? R[B[i + 507*t]] * R[C[i + 507*t]] : R[B[i + 507*t]] + R[C[i + 507*t]];
R[i + 1421*t] = Op[i + 508*t] ? R[B[i + 508*t]] * R[C[i + 508*t]] : R[B[i + 508*t]] + R[C[i + 508*t]];
R[i + 1422*t] = Op[i + 509*t] ? R[B[i + 509*t]] * R[C[i + 509*t]] : R[B[i + 509*t]] + R[C[i + 509*t]];
R[i + 1423*t] = Op[i + 510*t] ? R[B[i + 510*t]] * R[C[i + 510*t]] : R[B[i + 510*t]] + R[C[i + 510*t]];
R[i + 1424*t] = Op[i + 511*t] ? R[B[i + 511*t]] * R[C[i + 511*t]] : R[B[i + 511*t]] + R[C[i + 511*t]];
R[i + 1425*t] = Op[i + 512*t] ? R[B[i + 512*t]] * R[C[i + 512*t]] : R[B[i + 512*t]] + R[C[i + 512*t]];
R[i + 1426*t] = Op[i + 513*t] ? R[B[i + 513*t]] * R[C[i + 513*t]] : R[B[i + 513*t]] + R[C[i + 513*t]];
R[i + 1427*t] = Op[i + 514*t] ? R[B[i + 514*t]] * R[C[i + 514*t]] : R[B[i + 514*t]] + R[C[i + 514*t]];
R[i + 1428*t] = Op[i + 515*t] ? R[B[i + 515*t]] * R[C[i + 515*t]] : R[B[i + 515*t]] + R[C[i + 515*t]];
R[i + 1429*t] = Op[i + 516*t] ? R[B[i + 516*t]] * R[C[i + 516*t]] : R[B[i + 516*t]] + R[C[i + 516*t]];
R[i + 1430*t] = Op[i + 517*t] ? R[B[i + 517*t]] * R[C[i + 517*t]] : R[B[i + 517*t]] + R[C[i + 517*t]];
R[i + 1431*t] = Op[i + 518*t] ? R[B[i + 518*t]] * R[C[i + 518*t]] : R[B[i + 518*t]] + R[C[i + 518*t]];
R[i + 1432*t] = Op[i + 519*t] ? R[B[i + 519*t]] * R[C[i + 519*t]] : R[B[i + 519*t]] + R[C[i + 519*t]];
R[i + 1433*t] = Op[i + 520*t] ? R[B[i + 520*t]] * R[C[i + 520*t]] : R[B[i + 520*t]] + R[C[i + 520*t]];
R[i + 1434*t] = Op[i + 521*t] ? R[B[i + 521*t]] * R[C[i + 521*t]] : R[B[i + 521*t]] + R[C[i + 521*t]];
R[i + 1435*t] = Op[i + 522*t] ? R[B[i + 522*t]] * R[C[i + 522*t]] : R[B[i + 522*t]] + R[C[i + 522*t]];
R[i + 1436*t] = Op[i + 523*t] ? R[B[i + 523*t]] * R[C[i + 523*t]] : R[B[i + 523*t]] + R[C[i + 523*t]];
R[i + 1437*t] = Op[i + 524*t] ? R[B[i + 524*t]] * R[C[i + 524*t]] : R[B[i + 524*t]] + R[C[i + 524*t]];
R[i + 1438*t] = Op[i + 525*t] ? R[B[i + 525*t]] * R[C[i + 525*t]] : R[B[i + 525*t]] + R[C[i + 525*t]];
R[i + 1439*t] = Op[i + 526*t] ? R[B[i + 526*t]] * R[C[i + 526*t]] : R[B[i + 526*t]] + R[C[i + 526*t]];
R[i + 1440*t] = Op[i + 527*t] ? R[B[i + 527*t]] * R[C[i + 527*t]] : R[B[i + 527*t]] + R[C[i + 527*t]];
R[i + 1441*t] = Op[i + 528*t] ? R[B[i + 528*t]] * R[C[i + 528*t]] : R[B[i + 528*t]] + R[C[i + 528*t]];
R[i + 1442*t] = Op[i + 529*t] ? R[B[i + 529*t]] * R[C[i + 529*t]] : R[B[i + 529*t]] + R[C[i + 529*t]];
R[i + 1443*t] = Op[i + 530*t] ? R[B[i + 530*t]] * R[C[i + 530*t]] : R[B[i + 530*t]] + R[C[i + 530*t]];
R[i + 1444*t] = Op[i + 531*t] ? R[B[i + 531*t]] * R[C[i + 531*t]] : R[B[i + 531*t]] + R[C[i + 531*t]];
R[i + 1445*t] = Op[i + 532*t] ? R[B[i + 532*t]] * R[C[i + 532*t]] : R[B[i + 532*t]] + R[C[i + 532*t]];
R[i + 1446*t] = Op[i + 533*t] ? R[B[i + 533*t]] * R[C[i + 533*t]] : R[B[i + 533*t]] + R[C[i + 533*t]];
R[i + 1447*t] = Op[i + 534*t] ? R[B[i + 534*t]] * R[C[i + 534*t]] : R[B[i + 534*t]] + R[C[i + 534*t]];
R[i + 1448*t] = Op[i + 535*t] ? R[B[i + 535*t]] * R[C[i + 535*t]] : R[B[i + 535*t]] + R[C[i + 535*t]];
R[i + 1449*t] = Op[i + 536*t] ? R[B[i + 536*t]] * R[C[i + 536*t]] : R[B[i + 536*t]] + R[C[i + 536*t]];
R[i + 1450*t] = Op[i + 537*t] ? R[B[i + 537*t]] * R[C[i + 537*t]] : R[B[i + 537*t]] + R[C[i + 537*t]];
R[i + 1451*t] = Op[i + 538*t] ? R[B[i + 538*t]] * R[C[i + 538*t]] : R[B[i + 538*t]] + R[C[i + 538*t]];
R[i + 1452*t] = Op[i + 539*t] ? R[B[i + 539*t]] * R[C[i + 539*t]] : R[B[i + 539*t]] + R[C[i + 539*t]];
R[i + 1453*t] = Op[i + 540*t] ? R[B[i + 540*t]] * R[C[i + 540*t]] : R[B[i + 540*t]] + R[C[i + 540*t]];
R[i + 1454*t] = Op[i + 541*t] ? R[B[i + 541*t]] * R[C[i + 541*t]] : R[B[i + 541*t]] + R[C[i + 541*t]];
R[i + 1455*t] = Op[i + 542*t] ? R[B[i + 542*t]] * R[C[i + 542*t]] : R[B[i + 542*t]] + R[C[i + 542*t]];
R[i + 1456*t] = Op[i + 543*t] ? R[B[i + 543*t]] * R[C[i + 543*t]] : R[B[i + 543*t]] + R[C[i + 543*t]];
R[i + 1457*t] = Op[i + 544*t] ? R[B[i + 544*t]] * R[C[i + 544*t]] : R[B[i + 544*t]] + R[C[i + 544*t]];
R[i + 1458*t] = Op[i + 545*t] ? R[B[i + 545*t]] * R[C[i + 545*t]] : R[B[i + 545*t]] + R[C[i + 545*t]];
R[i + 1459*t] = Op[i + 546*t] ? R[B[i + 546*t]] * R[C[i + 546*t]] : R[B[i + 546*t]] + R[C[i + 546*t]];
R[i + 1460*t] = Op[i + 547*t] ? R[B[i + 547*t]] * R[C[i + 547*t]] : R[B[i + 547*t]] + R[C[i + 547*t]];
R[i + 1461*t] = Op[i + 548*t] ? R[B[i + 548*t]] * R[C[i + 548*t]] : R[B[i + 548*t]] + R[C[i + 548*t]];
R[i + 1462*t] = Op[i + 549*t] ? R[B[i + 549*t]] * R[C[i + 549*t]] : R[B[i + 549*t]] + R[C[i + 549*t]];
R[i + 1463*t] = Op[i + 550*t] ? R[B[i + 550*t]] * R[C[i + 550*t]] : R[B[i + 550*t]] + R[C[i + 550*t]];
R[i + 1464*t] = Op[i + 551*t] ? R[B[i + 551*t]] * R[C[i + 551*t]] : R[B[i + 551*t]] + R[C[i + 551*t]];
R[i + 1465*t] = Op[i + 552*t] ? R[B[i + 552*t]] * R[C[i + 552*t]] : R[B[i + 552*t]] + R[C[i + 552*t]];
R[i + 1466*t] = Op[i + 553*t] ? R[B[i + 553*t]] * R[C[i + 553*t]] : R[B[i + 553*t]] + R[C[i + 553*t]];
R[i + 1467*t] = Op[i + 554*t] ? R[B[i + 554*t]] * R[C[i + 554*t]] : R[B[i + 554*t]] + R[C[i + 554*t]];
R[i + 1468*t] = Op[i + 555*t] ? R[B[i + 555*t]] * R[C[i + 555*t]] : R[B[i + 555*t]] + R[C[i + 555*t]];
R[i + 1469*t] = Op[i + 556*t] ? R[B[i + 556*t]] * R[C[i + 556*t]] : R[B[i + 556*t]] + R[C[i + 556*t]];
R[i + 1470*t] = Op[i + 557*t] ? R[B[i + 557*t]] * R[C[i + 557*t]] : R[B[i + 557*t]] + R[C[i + 557*t]];
R[i + 1471*t] = Op[i + 558*t] ? R[B[i + 558*t]] * R[C[i + 558*t]] : R[B[i + 558*t]] + R[C[i + 558*t]];
R[i + 1472*t] = Op[i + 559*t] ? R[B[i + 559*t]] * R[C[i + 559*t]] : R[B[i + 559*t]] + R[C[i + 559*t]];
R[i + 1473*t] = Op[i + 560*t] ? R[B[i + 560*t]] * R[C[i + 560*t]] : R[B[i + 560*t]] + R[C[i + 560*t]];
R[i + 1474*t] = Op[i + 561*t] ? R[B[i + 561*t]] * R[C[i + 561*t]] : R[B[i + 561*t]] + R[C[i + 561*t]];
R[i + 1475*t] = Op[i + 562*t] ? R[B[i + 562*t]] * R[C[i + 562*t]] : R[B[i + 562*t]] + R[C[i + 562*t]];
R[i + 1476*t] = Op[i + 563*t] ? R[B[i + 563*t]] * R[C[i + 563*t]] : R[B[i + 563*t]] + R[C[i + 563*t]];
R[i + 1477*t] = Op[i + 564*t] ? R[B[i + 564*t]] * R[C[i + 564*t]] : R[B[i + 564*t]] + R[C[i + 564*t]];
R[i + 1478*t] = Op[i + 565*t] ? R[B[i + 565*t]] * R[C[i + 565*t]] : R[B[i + 565*t]] + R[C[i + 565*t]];
R[i + 1479*t] = Op[i + 566*t] ? R[B[i + 566*t]] * R[C[i + 566*t]] : R[B[i + 566*t]] + R[C[i + 566*t]];
R[i + 1480*t] = Op[i + 567*t] ? R[B[i + 567*t]] * R[C[i + 567*t]] : R[B[i + 567*t]] + R[C[i + 567*t]];
R[i + 1481*t] = Op[i + 568*t] ? R[B[i + 568*t]] * R[C[i + 568*t]] : R[B[i + 568*t]] + R[C[i + 568*t]];
R[i + 1482*t] = Op[i + 569*t] ? R[B[i + 569*t]] * R[C[i + 569*t]] : R[B[i + 569*t]] + R[C[i + 569*t]];
R[i + 1483*t] = Op[i + 570*t] ? R[B[i + 570*t]] * R[C[i + 570*t]] : R[B[i + 570*t]] + R[C[i + 570*t]];
R[i + 1484*t] = Op[i + 571*t] ? R[B[i + 571*t]] * R[C[i + 571*t]] : R[B[i + 571*t]] + R[C[i + 571*t]];
R[i + 1485*t] = Op[i + 572*t] ? R[B[i + 572*t]] * R[C[i + 572*t]] : R[B[i + 572*t]] + R[C[i + 572*t]];
R[i + 1486*t] = Op[i + 573*t] ? R[B[i + 573*t]] * R[C[i + 573*t]] : R[B[i + 573*t]] + R[C[i + 573*t]];
R[i + 1487*t] = Op[i + 574*t] ? R[B[i + 574*t]] * R[C[i + 574*t]] : R[B[i + 574*t]] + R[C[i + 574*t]];
R[i + 1488*t] = Op[i + 575*t] ? R[B[i + 575*t]] * R[C[i + 575*t]] : R[B[i + 575*t]] + R[C[i + 575*t]];
R[i + 1489*t] = Op[i + 576*t] ? R[B[i + 576*t]] * R[C[i + 576*t]] : R[B[i + 576*t]] + R[C[i + 576*t]];
R[i + 1490*t] = Op[i + 577*t] ? R[B[i + 577*t]] * R[C[i + 577*t]] : R[B[i + 577*t]] + R[C[i + 577*t]];
R[i + 1491*t] = Op[i + 578*t] ? R[B[i + 578*t]] * R[C[i + 578*t]] : R[B[i + 578*t]] + R[C[i + 578*t]];
R[i + 1492*t] = Op[i + 579*t] ? R[B[i + 579*t]] * R[C[i + 579*t]] : R[B[i + 579*t]] + R[C[i + 579*t]];
R[i + 1493*t] = Op[i + 580*t] ? R[B[i + 580*t]] * R[C[i + 580*t]] : R[B[i + 580*t]] + R[C[i + 580*t]];
R[i + 1494*t] = Op[i + 581*t] ? R[B[i + 581*t]] * R[C[i + 581*t]] : R[B[i + 581*t]] + R[C[i + 581*t]];
R[i + 1495*t] = Op[i + 582*t] ? R[B[i + 582*t]] * R[C[i + 582*t]] : R[B[i + 582*t]] + R[C[i + 582*t]];
R[i + 1496*t] = Op[i + 583*t] ? R[B[i + 583*t]] * R[C[i + 583*t]] : R[B[i + 583*t]] + R[C[i + 583*t]];
R[i + 1497*t] = Op[i + 584*t] ? R[B[i + 584*t]] * R[C[i + 584*t]] : R[B[i + 584*t]] + R[C[i + 584*t]];
R[i + 1498*t] = Op[i + 585*t] ? R[B[i + 585*t]] * R[C[i + 585*t]] : R[B[i + 585*t]] + R[C[i + 585*t]];
R[i + 1499*t] = Op[i + 586*t] ? R[B[i + 586*t]] * R[C[i + 586*t]] : R[B[i + 586*t]] + R[C[i + 586*t]];
R[i + 1500*t] = Op[i + 587*t] ? R[B[i + 587*t]] * R[C[i + 587*t]] : R[B[i + 587*t]] + R[C[i + 587*t]];
R[i + 1501*t] = Op[i + 588*t] ? R[B[i + 588*t]] * R[C[i + 588*t]] : R[B[i + 588*t]] + R[C[i + 588*t]];
__syncthreads();
R[i + 1502*t] = Op[i + 589*t] ? R[B[i + 589*t]] * R[C[i + 589*t]] : R[B[i + 589*t]] + R[C[i + 589*t]];
R[i + 1503*t] = Op[i + 590*t] ? R[B[i + 590*t]] * R[C[i + 590*t]] : R[B[i + 590*t]] + R[C[i + 590*t]];
R[i + 1504*t] = Op[i + 591*t] ? R[B[i + 591*t]] * R[C[i + 591*t]] : R[B[i + 591*t]] + R[C[i + 591*t]];
R[i + 1505*t] = Op[i + 592*t] ? R[B[i + 592*t]] * R[C[i + 592*t]] : R[B[i + 592*t]] + R[C[i + 592*t]];
R[i + 1506*t] = Op[i + 593*t] ? R[B[i + 593*t]] * R[C[i + 593*t]] : R[B[i + 593*t]] + R[C[i + 593*t]];
R[i + 1507*t] = Op[i + 594*t] ? R[B[i + 594*t]] * R[C[i + 594*t]] : R[B[i + 594*t]] + R[C[i + 594*t]];
R[i + 1508*t] = Op[i + 595*t] ? R[B[i + 595*t]] * R[C[i + 595*t]] : R[B[i + 595*t]] + R[C[i + 595*t]];
R[i + 1509*t] = Op[i + 596*t] ? R[B[i + 596*t]] * R[C[i + 596*t]] : R[B[i + 596*t]] + R[C[i + 596*t]];
R[i + 1510*t] = Op[i + 597*t] ? R[B[i + 597*t]] * R[C[i + 597*t]] : R[B[i + 597*t]] + R[C[i + 597*t]];
R[i + 1511*t] = Op[i + 598*t] ? R[B[i + 598*t]] * R[C[i + 598*t]] : R[B[i + 598*t]] + R[C[i + 598*t]];
R[i + 1512*t] = Op[i + 599*t] ? R[B[i + 599*t]] * R[C[i + 599*t]] : R[B[i + 599*t]] + R[C[i + 599*t]];
R[i + 1513*t] = Op[i + 600*t] ? R[B[i + 600*t]] * R[C[i + 600*t]] : R[B[i + 600*t]] + R[C[i + 600*t]];
R[i + 1514*t] = Op[i + 601*t] ? R[B[i + 601*t]] * R[C[i + 601*t]] : R[B[i + 601*t]] + R[C[i + 601*t]];
R[i + 1515*t] = Op[i + 602*t] ? R[B[i + 602*t]] * R[C[i + 602*t]] : R[B[i + 602*t]] + R[C[i + 602*t]];
R[i + 1516*t] = Op[i + 603*t] ? R[B[i + 603*t]] * R[C[i + 603*t]] : R[B[i + 603*t]] + R[C[i + 603*t]];
R[i + 1517*t] = Op[i + 604*t] ? R[B[i + 604*t]] * R[C[i + 604*t]] : R[B[i + 604*t]] + R[C[i + 604*t]];
R[i + 1518*t] = Op[i + 605*t] ? R[B[i + 605*t]] * R[C[i + 605*t]] : R[B[i + 605*t]] + R[C[i + 605*t]];
R[i + 1519*t] = Op[i + 606*t] ? R[B[i + 606*t]] * R[C[i + 606*t]] : R[B[i + 606*t]] + R[C[i + 606*t]];
R[i + 1520*t] = Op[i + 607*t] ? R[B[i + 607*t]] * R[C[i + 607*t]] : R[B[i + 607*t]] + R[C[i + 607*t]];
R[i + 1521*t] = Op[i + 608*t] ? R[B[i + 608*t]] * R[C[i + 608*t]] : R[B[i + 608*t]] + R[C[i + 608*t]];
R[i + 1522*t] = Op[i + 609*t] ? R[B[i + 609*t]] * R[C[i + 609*t]] : R[B[i + 609*t]] + R[C[i + 609*t]];
R[i + 1523*t] = Op[i + 610*t] ? R[B[i + 610*t]] * R[C[i + 610*t]] : R[B[i + 610*t]] + R[C[i + 610*t]];
R[i + 1524*t] = Op[i + 611*t] ? R[B[i + 611*t]] * R[C[i + 611*t]] : R[B[i + 611*t]] + R[C[i + 611*t]];
R[i + 1525*t] = Op[i + 612*t] ? R[B[i + 612*t]] * R[C[i + 612*t]] : R[B[i + 612*t]] + R[C[i + 612*t]];
R[i + 1526*t] = Op[i + 613*t] ? R[B[i + 613*t]] * R[C[i + 613*t]] : R[B[i + 613*t]] + R[C[i + 613*t]];
R[i + 1527*t] = Op[i + 614*t] ? R[B[i + 614*t]] * R[C[i + 614*t]] : R[B[i + 614*t]] + R[C[i + 614*t]];
R[i + 1528*t] = Op[i + 615*t] ? R[B[i + 615*t]] * R[C[i + 615*t]] : R[B[i + 615*t]] + R[C[i + 615*t]];
R[i + 1529*t] = Op[i + 616*t] ? R[B[i + 616*t]] * R[C[i + 616*t]] : R[B[i + 616*t]] + R[C[i + 616*t]];
R[i + 1530*t] = Op[i + 617*t] ? R[B[i + 617*t]] * R[C[i + 617*t]] : R[B[i + 617*t]] + R[C[i + 617*t]];
R[i + 1531*t] = Op[i + 618*t] ? R[B[i + 618*t]] * R[C[i + 618*t]] : R[B[i + 618*t]] + R[C[i + 618*t]];
R[i + 1532*t] = Op[i + 619*t] ? R[B[i + 619*t]] * R[C[i + 619*t]] : R[B[i + 619*t]] + R[C[i + 619*t]];
R[i + 1533*t] = Op[i + 620*t] ? R[B[i + 620*t]] * R[C[i + 620*t]] : R[B[i + 620*t]] + R[C[i + 620*t]];
R[i + 1534*t] = Op[i + 621*t] ? R[B[i + 621*t]] * R[C[i + 621*t]] : R[B[i + 621*t]] + R[C[i + 621*t]];
R[i + 1535*t] = Op[i + 622*t] ? R[B[i + 622*t]] * R[C[i + 622*t]] : R[B[i + 622*t]] + R[C[i + 622*t]];
R[i + 1536*t] = Op[i + 623*t] ? R[B[i + 623*t]] * R[C[i + 623*t]] : R[B[i + 623*t]] + R[C[i + 623*t]];
R[i + 1537*t] = Op[i + 624*t] ? R[B[i + 624*t]] * R[C[i + 624*t]] : R[B[i + 624*t]] + R[C[i + 624*t]];
R[i + 1538*t] = Op[i + 625*t] ? R[B[i + 625*t]] * R[C[i + 625*t]] : R[B[i + 625*t]] + R[C[i + 625*t]];
R[i + 1539*t] = Op[i + 626*t] ? R[B[i + 626*t]] * R[C[i + 626*t]] : R[B[i + 626*t]] + R[C[i + 626*t]];
R[i + 1540*t] = Op[i + 627*t] ? R[B[i + 627*t]] * R[C[i + 627*t]] : R[B[i + 627*t]] + R[C[i + 627*t]];
R[i + 1541*t] = Op[i + 628*t] ? R[B[i + 628*t]] * R[C[i + 628*t]] : R[B[i + 628*t]] + R[C[i + 628*t]];
R[i + 1542*t] = Op[i + 629*t] ? R[B[i + 629*t]] * R[C[i + 629*t]] : R[B[i + 629*t]] + R[C[i + 629*t]];
R[i + 1543*t] = Op[i + 630*t] ? R[B[i + 630*t]] * R[C[i + 630*t]] : R[B[i + 630*t]] + R[C[i + 630*t]];
R[i + 1544*t] = Op[i + 631*t] ? R[B[i + 631*t]] * R[C[i + 631*t]] : R[B[i + 631*t]] + R[C[i + 631*t]];
R[i + 1545*t] = Op[i + 632*t] ? R[B[i + 632*t]] * R[C[i + 632*t]] : R[B[i + 632*t]] + R[C[i + 632*t]];
R[i + 1546*t] = Op[i + 633*t] ? R[B[i + 633*t]] * R[C[i + 633*t]] : R[B[i + 633*t]] + R[C[i + 633*t]];
R[i + 1547*t] = Op[i + 634*t] ? R[B[i + 634*t]] * R[C[i + 634*t]] : R[B[i + 634*t]] + R[C[i + 634*t]];
R[i + 1548*t] = Op[i + 635*t] ? R[B[i + 635*t]] * R[C[i + 635*t]] : R[B[i + 635*t]] + R[C[i + 635*t]];
R[i + 1549*t] = Op[i + 636*t] ? R[B[i + 636*t]] * R[C[i + 636*t]] : R[B[i + 636*t]] + R[C[i + 636*t]];
R[i + 1550*t] = Op[i + 637*t] ? R[B[i + 637*t]] * R[C[i + 637*t]] : R[B[i + 637*t]] + R[C[i + 637*t]];
R[i + 1551*t] = Op[i + 638*t] ? R[B[i + 638*t]] * R[C[i + 638*t]] : R[B[i + 638*t]] + R[C[i + 638*t]];
R[i + 1552*t] = Op[i + 639*t] ? R[B[i + 639*t]] * R[C[i + 639*t]] : R[B[i + 639*t]] + R[C[i + 639*t]];
R[i + 1553*t] = Op[i + 640*t] ? R[B[i + 640*t]] * R[C[i + 640*t]] : R[B[i + 640*t]] + R[C[i + 640*t]];
R[i + 1554*t] = Op[i + 641*t] ? R[B[i + 641*t]] * R[C[i + 641*t]] : R[B[i + 641*t]] + R[C[i + 641*t]];
R[i + 1555*t] = Op[i + 642*t] ? R[B[i + 642*t]] * R[C[i + 642*t]] : R[B[i + 642*t]] + R[C[i + 642*t]];
R[i + 1556*t] = Op[i + 643*t] ? R[B[i + 643*t]] * R[C[i + 643*t]] : R[B[i + 643*t]] + R[C[i + 643*t]];
R[i + 1557*t] = Op[i + 644*t] ? R[B[i + 644*t]] * R[C[i + 644*t]] : R[B[i + 644*t]] + R[C[i + 644*t]];
R[i + 1558*t] = Op[i + 645*t] ? R[B[i + 645*t]] * R[C[i + 645*t]] : R[B[i + 645*t]] + R[C[i + 645*t]];
R[i + 1559*t] = Op[i + 646*t] ? R[B[i + 646*t]] * R[C[i + 646*t]] : R[B[i + 646*t]] + R[C[i + 646*t]];
R[i + 1560*t] = Op[i + 647*t] ? R[B[i + 647*t]] * R[C[i + 647*t]] : R[B[i + 647*t]] + R[C[i + 647*t]];
R[i + 1561*t] = Op[i + 648*t] ? R[B[i + 648*t]] * R[C[i + 648*t]] : R[B[i + 648*t]] + R[C[i + 648*t]];
R[i + 1562*t] = Op[i + 649*t] ? R[B[i + 649*t]] * R[C[i + 649*t]] : R[B[i + 649*t]] + R[C[i + 649*t]];
R[i + 1563*t] = Op[i + 650*t] ? R[B[i + 650*t]] * R[C[i + 650*t]] : R[B[i + 650*t]] + R[C[i + 650*t]];
R[i + 1564*t] = Op[i + 651*t] ? R[B[i + 651*t]] * R[C[i + 651*t]] : R[B[i + 651*t]] + R[C[i + 651*t]];
R[i + 1565*t] = Op[i + 652*t] ? R[B[i + 652*t]] * R[C[i + 652*t]] : R[B[i + 652*t]] + R[C[i + 652*t]];
R[i + 1566*t] = Op[i + 653*t] ? R[B[i + 653*t]] * R[C[i + 653*t]] : R[B[i + 653*t]] + R[C[i + 653*t]];
R[i + 1567*t] = Op[i + 654*t] ? R[B[i + 654*t]] * R[C[i + 654*t]] : R[B[i + 654*t]] + R[C[i + 654*t]];
R[i + 1568*t] = Op[i + 655*t] ? R[B[i + 655*t]] * R[C[i + 655*t]] : R[B[i + 655*t]] + R[C[i + 655*t]];
R[i + 1569*t] = Op[i + 656*t] ? R[B[i + 656*t]] * R[C[i + 656*t]] : R[B[i + 656*t]] + R[C[i + 656*t]];
R[i + 1570*t] = Op[i + 657*t] ? R[B[i + 657*t]] * R[C[i + 657*t]] : R[B[i + 657*t]] + R[C[i + 657*t]];
R[i + 1571*t] = Op[i + 658*t] ? R[B[i + 658*t]] * R[C[i + 658*t]] : R[B[i + 658*t]] + R[C[i + 658*t]];
R[i + 1572*t] = Op[i + 659*t] ? R[B[i + 659*t]] * R[C[i + 659*t]] : R[B[i + 659*t]] + R[C[i + 659*t]];
R[i + 1573*t] = Op[i + 660*t] ? R[B[i + 660*t]] * R[C[i + 660*t]] : R[B[i + 660*t]] + R[C[i + 660*t]];
R[i + 1574*t] = Op[i + 661*t] ? R[B[i + 661*t]] * R[C[i + 661*t]] : R[B[i + 661*t]] + R[C[i + 661*t]];
R[i + 1575*t] = Op[i + 662*t] ? R[B[i + 662*t]] * R[C[i + 662*t]] : R[B[i + 662*t]] + R[C[i + 662*t]];
R[i + 1576*t] = Op[i + 663*t] ? R[B[i + 663*t]] * R[C[i + 663*t]] : R[B[i + 663*t]] + R[C[i + 663*t]];
R[i + 1577*t] = Op[i + 664*t] ? R[B[i + 664*t]] * R[C[i + 664*t]] : R[B[i + 664*t]] + R[C[i + 664*t]];
R[i + 1578*t] = Op[i + 665*t] ? R[B[i + 665*t]] * R[C[i + 665*t]] : R[B[i + 665*t]] + R[C[i + 665*t]];
R[i + 1579*t] = Op[i + 666*t] ? R[B[i + 666*t]] * R[C[i + 666*t]] : R[B[i + 666*t]] + R[C[i + 666*t]];
R[i + 1580*t] = Op[i + 667*t] ? R[B[i + 667*t]] * R[C[i + 667*t]] : R[B[i + 667*t]] + R[C[i + 667*t]];
R[i + 1581*t] = Op[i + 668*t] ? R[B[i + 668*t]] * R[C[i + 668*t]] : R[B[i + 668*t]] + R[C[i + 668*t]];
R[i + 1582*t] = Op[i + 669*t] ? R[B[i + 669*t]] * R[C[i + 669*t]] : R[B[i + 669*t]] + R[C[i + 669*t]];
R[i + 1583*t] = Op[i + 670*t] ? R[B[i + 670*t]] * R[C[i + 670*t]] : R[B[i + 670*t]] + R[C[i + 670*t]];
R[i + 1584*t] = Op[i + 671*t] ? R[B[i + 671*t]] * R[C[i + 671*t]] : R[B[i + 671*t]] + R[C[i + 671*t]];
R[i + 1585*t] = Op[i + 672*t] ? R[B[i + 672*t]] * R[C[i + 672*t]] : R[B[i + 672*t]] + R[C[i + 672*t]];
R[i + 1586*t] = Op[i + 673*t] ? R[B[i + 673*t]] * R[C[i + 673*t]] : R[B[i + 673*t]] + R[C[i + 673*t]];
R[i + 1587*t] = Op[i + 674*t] ? R[B[i + 674*t]] * R[C[i + 674*t]] : R[B[i + 674*t]] + R[C[i + 674*t]];
R[i + 1588*t] = Op[i + 675*t] ? R[B[i + 675*t]] * R[C[i + 675*t]] : R[B[i + 675*t]] + R[C[i + 675*t]];
R[i + 1589*t] = Op[i + 676*t] ? R[B[i + 676*t]] * R[C[i + 676*t]] : R[B[i + 676*t]] + R[C[i + 676*t]];
R[i + 1590*t] = Op[i + 677*t] ? R[B[i + 677*t]] * R[C[i + 677*t]] : R[B[i + 677*t]] + R[C[i + 677*t]];
R[i + 1591*t] = Op[i + 678*t] ? R[B[i + 678*t]] * R[C[i + 678*t]] : R[B[i + 678*t]] + R[C[i + 678*t]];
R[i + 1592*t] = Op[i + 679*t] ? R[B[i + 679*t]] * R[C[i + 679*t]] : R[B[i + 679*t]] + R[C[i + 679*t]];
R[i + 1593*t] = Op[i + 680*t] ? R[B[i + 680*t]] * R[C[i + 680*t]] : R[B[i + 680*t]] + R[C[i + 680*t]];
R[i + 1594*t] = Op[i + 681*t] ? R[B[i + 681*t]] * R[C[i + 681*t]] : R[B[i + 681*t]] + R[C[i + 681*t]];
R[i + 1595*t] = Op[i + 682*t] ? R[B[i + 682*t]] * R[C[i + 682*t]] : R[B[i + 682*t]] + R[C[i + 682*t]];
R[i + 1596*t] = Op[i + 683*t] ? R[B[i + 683*t]] * R[C[i + 683*t]] : R[B[i + 683*t]] + R[C[i + 683*t]];
R[i + 1597*t] = Op[i + 684*t] ? R[B[i + 684*t]] * R[C[i + 684*t]] : R[B[i + 684*t]] + R[C[i + 684*t]];
R[i + 1598*t] = Op[i + 685*t] ? R[B[i + 685*t]] * R[C[i + 685*t]] : R[B[i + 685*t]] + R[C[i + 685*t]];
R[i + 1599*t] = Op[i + 686*t] ? R[B[i + 686*t]] * R[C[i + 686*t]] : R[B[i + 686*t]] + R[C[i + 686*t]];
R[i + 1600*t] = Op[i + 687*t] ? R[B[i + 687*t]] * R[C[i + 687*t]] : R[B[i + 687*t]] + R[C[i + 687*t]];
R[i + 1601*t] = Op[i + 688*t] ? R[B[i + 688*t]] * R[C[i + 688*t]] : R[B[i + 688*t]] + R[C[i + 688*t]];
R[i + 1602*t] = Op[i + 689*t] ? R[B[i + 689*t]] * R[C[i + 689*t]] : R[B[i + 689*t]] + R[C[i + 689*t]];
R[i + 1603*t] = Op[i + 690*t] ? R[B[i + 690*t]] * R[C[i + 690*t]] : R[B[i + 690*t]] + R[C[i + 690*t]];
R[i + 1604*t] = Op[i + 691*t] ? R[B[i + 691*t]] * R[C[i + 691*t]] : R[B[i + 691*t]] + R[C[i + 691*t]];
R[i + 1605*t] = Op[i + 692*t] ? R[B[i + 692*t]] * R[C[i + 692*t]] : R[B[i + 692*t]] + R[C[i + 692*t]];
R[i + 1606*t] = Op[i + 693*t] ? R[B[i + 693*t]] * R[C[i + 693*t]] : R[B[i + 693*t]] + R[C[i + 693*t]];
R[i + 1607*t] = Op[i + 694*t] ? R[B[i + 694*t]] * R[C[i + 694*t]] : R[B[i + 694*t]] + R[C[i + 694*t]];
R[i + 1608*t] = Op[i + 695*t] ? R[B[i + 695*t]] * R[C[i + 695*t]] : R[B[i + 695*t]] + R[C[i + 695*t]];
R[i + 1609*t] = Op[i + 696*t] ? R[B[i + 696*t]] * R[C[i + 696*t]] : R[B[i + 696*t]] + R[C[i + 696*t]];
R[i + 1610*t] = Op[i + 697*t] ? R[B[i + 697*t]] * R[C[i + 697*t]] : R[B[i + 697*t]] + R[C[i + 697*t]];
R[i + 1611*t] = Op[i + 698*t] ? R[B[i + 698*t]] * R[C[i + 698*t]] : R[B[i + 698*t]] + R[C[i + 698*t]];
R[i + 1612*t] = Op[i + 699*t] ? R[B[i + 699*t]] * R[C[i + 699*t]] : R[B[i + 699*t]] + R[C[i + 699*t]];
R[i + 1613*t] = Op[i + 700*t] ? R[B[i + 700*t]] * R[C[i + 700*t]] : R[B[i + 700*t]] + R[C[i + 700*t]];
R[i + 1614*t] = Op[i + 701*t] ? R[B[i + 701*t]] * R[C[i + 701*t]] : R[B[i + 701*t]] + R[C[i + 701*t]];
R[i + 1615*t] = Op[i + 702*t] ? R[B[i + 702*t]] * R[C[i + 702*t]] : R[B[i + 702*t]] + R[C[i + 702*t]];
R[i + 1616*t] = Op[i + 703*t] ? R[B[i + 703*t]] * R[C[i + 703*t]] : R[B[i + 703*t]] + R[C[i + 703*t]];
R[i + 1617*t] = Op[i + 704*t] ? R[B[i + 704*t]] * R[C[i + 704*t]] : R[B[i + 704*t]] + R[C[i + 704*t]];
R[i + 1618*t] = Op[i + 705*t] ? R[B[i + 705*t]] * R[C[i + 705*t]] : R[B[i + 705*t]] + R[C[i + 705*t]];
R[i + 1619*t] = Op[i + 706*t] ? R[B[i + 706*t]] * R[C[i + 706*t]] : R[B[i + 706*t]] + R[C[i + 706*t]];
R[i + 1620*t] = Op[i + 707*t] ? R[B[i + 707*t]] * R[C[i + 707*t]] : R[B[i + 707*t]] + R[C[i + 707*t]];
R[i + 1621*t] = Op[i + 708*t] ? R[B[i + 708*t]] * R[C[i + 708*t]] : R[B[i + 708*t]] + R[C[i + 708*t]];
R[i + 1622*t] = Op[i + 709*t] ? R[B[i + 709*t]] * R[C[i + 709*t]] : R[B[i + 709*t]] + R[C[i + 709*t]];
R[i + 1623*t] = Op[i + 710*t] ? R[B[i + 710*t]] * R[C[i + 710*t]] : R[B[i + 710*t]] + R[C[i + 710*t]];
R[i + 1624*t] = Op[i + 711*t] ? R[B[i + 711*t]] * R[C[i + 711*t]] : R[B[i + 711*t]] + R[C[i + 711*t]];
R[i + 1625*t] = Op[i + 712*t] ? R[B[i + 712*t]] * R[C[i + 712*t]] : R[B[i + 712*t]] + R[C[i + 712*t]];
R[i + 1626*t] = Op[i + 713*t] ? R[B[i + 713*t]] * R[C[i + 713*t]] : R[B[i + 713*t]] + R[C[i + 713*t]];
R[i + 1627*t] = Op[i + 714*t] ? R[B[i + 714*t]] * R[C[i + 714*t]] : R[B[i + 714*t]] + R[C[i + 714*t]];
R[i + 1628*t] = Op[i + 715*t] ? R[B[i + 715*t]] * R[C[i + 715*t]] : R[B[i + 715*t]] + R[C[i + 715*t]];
R[i + 1629*t] = Op[i + 716*t] ? R[B[i + 716*t]] * R[C[i + 716*t]] : R[B[i + 716*t]] + R[C[i + 716*t]];
R[i + 1630*t] = Op[i + 717*t] ? R[B[i + 717*t]] * R[C[i + 717*t]] : R[B[i + 717*t]] + R[C[i + 717*t]];
R[i + 1631*t] = Op[i + 718*t] ? R[B[i + 718*t]] * R[C[i + 718*t]] : R[B[i + 718*t]] + R[C[i + 718*t]];
R[i + 1632*t] = Op[i + 719*t] ? R[B[i + 719*t]] * R[C[i + 719*t]] : R[B[i + 719*t]] + R[C[i + 719*t]];
R[i + 1633*t] = Op[i + 720*t] ? R[B[i + 720*t]] * R[C[i + 720*t]] : R[B[i + 720*t]] + R[C[i + 720*t]];
R[i + 1634*t] = Op[i + 721*t] ? R[B[i + 721*t]] * R[C[i + 721*t]] : R[B[i + 721*t]] + R[C[i + 721*t]];
R[i + 1635*t] = Op[i + 722*t] ? R[B[i + 722*t]] * R[C[i + 722*t]] : R[B[i + 722*t]] + R[C[i + 722*t]];
R[i + 1636*t] = Op[i + 723*t] ? R[B[i + 723*t]] * R[C[i + 723*t]] : R[B[i + 723*t]] + R[C[i + 723*t]];
R[i + 1637*t] = Op[i + 724*t] ? R[B[i + 724*t]] * R[C[i + 724*t]] : R[B[i + 724*t]] + R[C[i + 724*t]];
R[i + 1638*t] = Op[i + 725*t] ? R[B[i + 725*t]] * R[C[i + 725*t]] : R[B[i + 725*t]] + R[C[i + 725*t]];
R[i + 1639*t] = Op[i + 726*t] ? R[B[i + 726*t]] * R[C[i + 726*t]] : R[B[i + 726*t]] + R[C[i + 726*t]];
R[i + 1640*t] = Op[i + 727*t] ? R[B[i + 727*t]] * R[C[i + 727*t]] : R[B[i + 727*t]] + R[C[i + 727*t]];
R[i + 1641*t] = Op[i + 728*t] ? R[B[i + 728*t]] * R[C[i + 728*t]] : R[B[i + 728*t]] + R[C[i + 728*t]];
R[i + 1642*t] = Op[i + 729*t] ? R[B[i + 729*t]] * R[C[i + 729*t]] : R[B[i + 729*t]] + R[C[i + 729*t]];
R[i + 1643*t] = Op[i + 730*t] ? R[B[i + 730*t]] * R[C[i + 730*t]] : R[B[i + 730*t]] + R[C[i + 730*t]];
R[i + 1644*t] = Op[i + 731*t] ? R[B[i + 731*t]] * R[C[i + 731*t]] : R[B[i + 731*t]] + R[C[i + 731*t]];
R[i + 1645*t] = Op[i + 732*t] ? R[B[i + 732*t]] * R[C[i + 732*t]] : R[B[i + 732*t]] + R[C[i + 732*t]];
__syncthreads();
R[i + 1646*t] = Op[i + 733*t] ? R[B[i + 733*t]] * R[C[i + 733*t]] : R[B[i + 733*t]] + R[C[i + 733*t]];
R[i + 1647*t] = Op[i + 734*t] ? R[B[i + 734*t]] * R[C[i + 734*t]] : R[B[i + 734*t]] + R[C[i + 734*t]];
R[i + 1648*t] = Op[i + 735*t] ? R[B[i + 735*t]] * R[C[i + 735*t]] : R[B[i + 735*t]] + R[C[i + 735*t]];
R[i + 1649*t] = Op[i + 736*t] ? R[B[i + 736*t]] * R[C[i + 736*t]] : R[B[i + 736*t]] + R[C[i + 736*t]];
R[i + 1650*t] = Op[i + 737*t] ? R[B[i + 737*t]] * R[C[i + 737*t]] : R[B[i + 737*t]] + R[C[i + 737*t]];
R[i + 1651*t] = Op[i + 738*t] ? R[B[i + 738*t]] * R[C[i + 738*t]] : R[B[i + 738*t]] + R[C[i + 738*t]];
R[i + 1652*t] = Op[i + 739*t] ? R[B[i + 739*t]] * R[C[i + 739*t]] : R[B[i + 739*t]] + R[C[i + 739*t]];
R[i + 1653*t] = Op[i + 740*t] ? R[B[i + 740*t]] * R[C[i + 740*t]] : R[B[i + 740*t]] + R[C[i + 740*t]];
R[i + 1654*t] = Op[i + 741*t] ? R[B[i + 741*t]] * R[C[i + 741*t]] : R[B[i + 741*t]] + R[C[i + 741*t]];
R[i + 1655*t] = Op[i + 742*t] ? R[B[i + 742*t]] * R[C[i + 742*t]] : R[B[i + 742*t]] + R[C[i + 742*t]];
R[i + 1656*t] = Op[i + 743*t] ? R[B[i + 743*t]] * R[C[i + 743*t]] : R[B[i + 743*t]] + R[C[i + 743*t]];
R[i + 1657*t] = Op[i + 744*t] ? R[B[i + 744*t]] * R[C[i + 744*t]] : R[B[i + 744*t]] + R[C[i + 744*t]];
R[i + 1658*t] = Op[i + 745*t] ? R[B[i + 745*t]] * R[C[i + 745*t]] : R[B[i + 745*t]] + R[C[i + 745*t]];
R[i + 1659*t] = Op[i + 746*t] ? R[B[i + 746*t]] * R[C[i + 746*t]] : R[B[i + 746*t]] + R[C[i + 746*t]];
R[i + 1660*t] = Op[i + 747*t] ? R[B[i + 747*t]] * R[C[i + 747*t]] : R[B[i + 747*t]] + R[C[i + 747*t]];
R[i + 1661*t] = Op[i + 748*t] ? R[B[i + 748*t]] * R[C[i + 748*t]] : R[B[i + 748*t]] + R[C[i + 748*t]];
R[i + 1662*t] = Op[i + 749*t] ? R[B[i + 749*t]] * R[C[i + 749*t]] : R[B[i + 749*t]] + R[C[i + 749*t]];
R[i + 1663*t] = Op[i + 750*t] ? R[B[i + 750*t]] * R[C[i + 750*t]] : R[B[i + 750*t]] + R[C[i + 750*t]];
R[i + 1664*t] = Op[i + 751*t] ? R[B[i + 751*t]] * R[C[i + 751*t]] : R[B[i + 751*t]] + R[C[i + 751*t]];
R[i + 1665*t] = Op[i + 752*t] ? R[B[i + 752*t]] * R[C[i + 752*t]] : R[B[i + 752*t]] + R[C[i + 752*t]];
R[i + 1666*t] = Op[i + 753*t] ? R[B[i + 753*t]] * R[C[i + 753*t]] : R[B[i + 753*t]] + R[C[i + 753*t]];
R[i + 1667*t] = Op[i + 754*t] ? R[B[i + 754*t]] * R[C[i + 754*t]] : R[B[i + 754*t]] + R[C[i + 754*t]];
R[i + 1668*t] = Op[i + 755*t] ? R[B[i + 755*t]] * R[C[i + 755*t]] : R[B[i + 755*t]] + R[C[i + 755*t]];
R[i + 1669*t] = Op[i + 756*t] ? R[B[i + 756*t]] * R[C[i + 756*t]] : R[B[i + 756*t]] + R[C[i + 756*t]];
R[i + 1670*t] = Op[i + 757*t] ? R[B[i + 757*t]] * R[C[i + 757*t]] : R[B[i + 757*t]] + R[C[i + 757*t]];
R[i + 1671*t] = Op[i + 758*t] ? R[B[i + 758*t]] * R[C[i + 758*t]] : R[B[i + 758*t]] + R[C[i + 758*t]];
R[i + 1672*t] = Op[i + 759*t] ? R[B[i + 759*t]] * R[C[i + 759*t]] : R[B[i + 759*t]] + R[C[i + 759*t]];
R[i + 1673*t] = Op[i + 760*t] ? R[B[i + 760*t]] * R[C[i + 760*t]] : R[B[i + 760*t]] + R[C[i + 760*t]];
R[i + 1674*t] = Op[i + 761*t] ? R[B[i + 761*t]] * R[C[i + 761*t]] : R[B[i + 761*t]] + R[C[i + 761*t]];
R[i + 1675*t] = Op[i + 762*t] ? R[B[i + 762*t]] * R[C[i + 762*t]] : R[B[i + 762*t]] + R[C[i + 762*t]];
R[i + 1676*t] = Op[i + 763*t] ? R[B[i + 763*t]] * R[C[i + 763*t]] : R[B[i + 763*t]] + R[C[i + 763*t]];
R[i + 1677*t] = Op[i + 764*t] ? R[B[i + 764*t]] * R[C[i + 764*t]] : R[B[i + 764*t]] + R[C[i + 764*t]];
R[i + 1678*t] = Op[i + 765*t] ? R[B[i + 765*t]] * R[C[i + 765*t]] : R[B[i + 765*t]] + R[C[i + 765*t]];
R[i + 1679*t] = Op[i + 766*t] ? R[B[i + 766*t]] * R[C[i + 766*t]] : R[B[i + 766*t]] + R[C[i + 766*t]];
R[i + 1680*t] = Op[i + 767*t] ? R[B[i + 767*t]] * R[C[i + 767*t]] : R[B[i + 767*t]] + R[C[i + 767*t]];
R[i + 1681*t] = Op[i + 768*t] ? R[B[i + 768*t]] * R[C[i + 768*t]] : R[B[i + 768*t]] + R[C[i + 768*t]];
R[i + 1682*t] = Op[i + 769*t] ? R[B[i + 769*t]] * R[C[i + 769*t]] : R[B[i + 769*t]] + R[C[i + 769*t]];
R[i + 1683*t] = Op[i + 770*t] ? R[B[i + 770*t]] * R[C[i + 770*t]] : R[B[i + 770*t]] + R[C[i + 770*t]];
R[i + 1684*t] = Op[i + 771*t] ? R[B[i + 771*t]] * R[C[i + 771*t]] : R[B[i + 771*t]] + R[C[i + 771*t]];
R[i + 1685*t] = Op[i + 772*t] ? R[B[i + 772*t]] * R[C[i + 772*t]] : R[B[i + 772*t]] + R[C[i + 772*t]];
R[i + 1686*t] = Op[i + 773*t] ? R[B[i + 773*t]] * R[C[i + 773*t]] : R[B[i + 773*t]] + R[C[i + 773*t]];
R[i + 1687*t] = Op[i + 774*t] ? R[B[i + 774*t]] * R[C[i + 774*t]] : R[B[i + 774*t]] + R[C[i + 774*t]];
R[i + 1688*t] = Op[i + 775*t] ? R[B[i + 775*t]] * R[C[i + 775*t]] : R[B[i + 775*t]] + R[C[i + 775*t]];
R[i + 1689*t] = Op[i + 776*t] ? R[B[i + 776*t]] * R[C[i + 776*t]] : R[B[i + 776*t]] + R[C[i + 776*t]];
R[i + 1690*t] = Op[i + 777*t] ? R[B[i + 777*t]] * R[C[i + 777*t]] : R[B[i + 777*t]] + R[C[i + 777*t]];
R[i + 1691*t] = Op[i + 778*t] ? R[B[i + 778*t]] * R[C[i + 778*t]] : R[B[i + 778*t]] + R[C[i + 778*t]];
R[i + 1692*t] = Op[i + 779*t] ? R[B[i + 779*t]] * R[C[i + 779*t]] : R[B[i + 779*t]] + R[C[i + 779*t]];
R[i + 1693*t] = Op[i + 780*t] ? R[B[i + 780*t]] * R[C[i + 780*t]] : R[B[i + 780*t]] + R[C[i + 780*t]];
R[i + 1694*t] = Op[i + 781*t] ? R[B[i + 781*t]] * R[C[i + 781*t]] : R[B[i + 781*t]] + R[C[i + 781*t]];
R[i + 1695*t] = Op[i + 782*t] ? R[B[i + 782*t]] * R[C[i + 782*t]] : R[B[i + 782*t]] + R[C[i + 782*t]];
R[i + 1696*t] = Op[i + 783*t] ? R[B[i + 783*t]] * R[C[i + 783*t]] : R[B[i + 783*t]] + R[C[i + 783*t]];
R[i + 1697*t] = Op[i + 784*t] ? R[B[i + 784*t]] * R[C[i + 784*t]] : R[B[i + 784*t]] + R[C[i + 784*t]];
R[i + 1698*t] = Op[i + 785*t] ? R[B[i + 785*t]] * R[C[i + 785*t]] : R[B[i + 785*t]] + R[C[i + 785*t]];
R[i + 1699*t] = Op[i + 786*t] ? R[B[i + 786*t]] * R[C[i + 786*t]] : R[B[i + 786*t]] + R[C[i + 786*t]];
R[i + 1700*t] = Op[i + 787*t] ? R[B[i + 787*t]] * R[C[i + 787*t]] : R[B[i + 787*t]] + R[C[i + 787*t]];
R[i + 1701*t] = Op[i + 788*t] ? R[B[i + 788*t]] * R[C[i + 788*t]] : R[B[i + 788*t]] + R[C[i + 788*t]];
R[i + 1702*t] = Op[i + 789*t] ? R[B[i + 789*t]] * R[C[i + 789*t]] : R[B[i + 789*t]] + R[C[i + 789*t]];
R[i + 1703*t] = Op[i + 790*t] ? R[B[i + 790*t]] * R[C[i + 790*t]] : R[B[i + 790*t]] + R[C[i + 790*t]];
R[i + 1704*t] = Op[i + 791*t] ? R[B[i + 791*t]] * R[C[i + 791*t]] : R[B[i + 791*t]] + R[C[i + 791*t]];
R[i + 1705*t] = Op[i + 792*t] ? R[B[i + 792*t]] * R[C[i + 792*t]] : R[B[i + 792*t]] + R[C[i + 792*t]];
R[i + 1706*t] = Op[i + 793*t] ? R[B[i + 793*t]] * R[C[i + 793*t]] : R[B[i + 793*t]] + R[C[i + 793*t]];
R[i + 1707*t] = Op[i + 794*t] ? R[B[i + 794*t]] * R[C[i + 794*t]] : R[B[i + 794*t]] + R[C[i + 794*t]];
R[i + 1708*t] = Op[i + 795*t] ? R[B[i + 795*t]] * R[C[i + 795*t]] : R[B[i + 795*t]] + R[C[i + 795*t]];
R[i + 1709*t] = Op[i + 796*t] ? R[B[i + 796*t]] * R[C[i + 796*t]] : R[B[i + 796*t]] + R[C[i + 796*t]];
R[i + 1710*t] = Op[i + 797*t] ? R[B[i + 797*t]] * R[C[i + 797*t]] : R[B[i + 797*t]] + R[C[i + 797*t]];
R[i + 1711*t] = Op[i + 798*t] ? R[B[i + 798*t]] * R[C[i + 798*t]] : R[B[i + 798*t]] + R[C[i + 798*t]];
R[i + 1712*t] = Op[i + 799*t] ? R[B[i + 799*t]] * R[C[i + 799*t]] : R[B[i + 799*t]] + R[C[i + 799*t]];
R[i + 1713*t] = Op[i + 800*t] ? R[B[i + 800*t]] * R[C[i + 800*t]] : R[B[i + 800*t]] + R[C[i + 800*t]];
R[i + 1714*t] = Op[i + 801*t] ? R[B[i + 801*t]] * R[C[i + 801*t]] : R[B[i + 801*t]] + R[C[i + 801*t]];
R[i + 1715*t] = Op[i + 802*t] ? R[B[i + 802*t]] * R[C[i + 802*t]] : R[B[i + 802*t]] + R[C[i + 802*t]];
R[i + 1716*t] = Op[i + 803*t] ? R[B[i + 803*t]] * R[C[i + 803*t]] : R[B[i + 803*t]] + R[C[i + 803*t]];
R[i + 1717*t] = Op[i + 804*t] ? R[B[i + 804*t]] * R[C[i + 804*t]] : R[B[i + 804*t]] + R[C[i + 804*t]];
R[i + 1718*t] = Op[i + 805*t] ? R[B[i + 805*t]] * R[C[i + 805*t]] : R[B[i + 805*t]] + R[C[i + 805*t]];
R[i + 1719*t] = Op[i + 806*t] ? R[B[i + 806*t]] * R[C[i + 806*t]] : R[B[i + 806*t]] + R[C[i + 806*t]];
R[i + 1720*t] = Op[i + 807*t] ? R[B[i + 807*t]] * R[C[i + 807*t]] : R[B[i + 807*t]] + R[C[i + 807*t]];
R[i + 1721*t] = Op[i + 808*t] ? R[B[i + 808*t]] * R[C[i + 808*t]] : R[B[i + 808*t]] + R[C[i + 808*t]];
R[i + 1722*t] = Op[i + 809*t] ? R[B[i + 809*t]] * R[C[i + 809*t]] : R[B[i + 809*t]] + R[C[i + 809*t]];
R[i + 1723*t] = Op[i + 810*t] ? R[B[i + 810*t]] * R[C[i + 810*t]] : R[B[i + 810*t]] + R[C[i + 810*t]];
R[i + 1724*t] = Op[i + 811*t] ? R[B[i + 811*t]] * R[C[i + 811*t]] : R[B[i + 811*t]] + R[C[i + 811*t]];
R[i + 1725*t] = Op[i + 812*t] ? R[B[i + 812*t]] * R[C[i + 812*t]] : R[B[i + 812*t]] + R[C[i + 812*t]];
R[i + 1726*t] = Op[i + 813*t] ? R[B[i + 813*t]] * R[C[i + 813*t]] : R[B[i + 813*t]] + R[C[i + 813*t]];
R[i + 1727*t] = Op[i + 814*t] ? R[B[i + 814*t]] * R[C[i + 814*t]] : R[B[i + 814*t]] + R[C[i + 814*t]];
R[i + 1728*t] = Op[i + 815*t] ? R[B[i + 815*t]] * R[C[i + 815*t]] : R[B[i + 815*t]] + R[C[i + 815*t]];
R[i + 1729*t] = Op[i + 816*t] ? R[B[i + 816*t]] * R[C[i + 816*t]] : R[B[i + 816*t]] + R[C[i + 816*t]];
R[i + 1730*t] = Op[i + 817*t] ? R[B[i + 817*t]] * R[C[i + 817*t]] : R[B[i + 817*t]] + R[C[i + 817*t]];
R[i + 1731*t] = Op[i + 818*t] ? R[B[i + 818*t]] * R[C[i + 818*t]] : R[B[i + 818*t]] + R[C[i + 818*t]];
R[i + 1732*t] = Op[i + 819*t] ? R[B[i + 819*t]] * R[C[i + 819*t]] : R[B[i + 819*t]] + R[C[i + 819*t]];
R[i + 1733*t] = Op[i + 820*t] ? R[B[i + 820*t]] * R[C[i + 820*t]] : R[B[i + 820*t]] + R[C[i + 820*t]];
R[i + 1734*t] = Op[i + 821*t] ? R[B[i + 821*t]] * R[C[i + 821*t]] : R[B[i + 821*t]] + R[C[i + 821*t]];
R[i + 1735*t] = Op[i + 822*t] ? R[B[i + 822*t]] * R[C[i + 822*t]] : R[B[i + 822*t]] + R[C[i + 822*t]];
R[i + 1736*t] = Op[i + 823*t] ? R[B[i + 823*t]] * R[C[i + 823*t]] : R[B[i + 823*t]] + R[C[i + 823*t]];
__syncthreads();
R[i + 1737*t] = Op[i + 824*t] ? R[B[i + 824*t]] * R[C[i + 824*t]] : R[B[i + 824*t]] + R[C[i + 824*t]];
R[i + 1738*t] = Op[i + 825*t] ? R[B[i + 825*t]] * R[C[i + 825*t]] : R[B[i + 825*t]] + R[C[i + 825*t]];
R[i + 1739*t] = Op[i + 826*t] ? R[B[i + 826*t]] * R[C[i + 826*t]] : R[B[i + 826*t]] + R[C[i + 826*t]];
R[i + 1740*t] = Op[i + 827*t] ? R[B[i + 827*t]] * R[C[i + 827*t]] : R[B[i + 827*t]] + R[C[i + 827*t]];
R[i + 1741*t] = Op[i + 828*t] ? R[B[i + 828*t]] * R[C[i + 828*t]] : R[B[i + 828*t]] + R[C[i + 828*t]];
R[i + 1742*t] = Op[i + 829*t] ? R[B[i + 829*t]] * R[C[i + 829*t]] : R[B[i + 829*t]] + R[C[i + 829*t]];
R[i + 1743*t] = Op[i + 830*t] ? R[B[i + 830*t]] * R[C[i + 830*t]] : R[B[i + 830*t]] + R[C[i + 830*t]];
R[i + 1744*t] = Op[i + 831*t] ? R[B[i + 831*t]] * R[C[i + 831*t]] : R[B[i + 831*t]] + R[C[i + 831*t]];
R[i + 1745*t] = Op[i + 832*t] ? R[B[i + 832*t]] * R[C[i + 832*t]] : R[B[i + 832*t]] + R[C[i + 832*t]];
R[i + 1746*t] = Op[i + 833*t] ? R[B[i + 833*t]] * R[C[i + 833*t]] : R[B[i + 833*t]] + R[C[i + 833*t]];
R[i + 1747*t] = Op[i + 834*t] ? R[B[i + 834*t]] * R[C[i + 834*t]] : R[B[i + 834*t]] + R[C[i + 834*t]];
R[i + 1748*t] = Op[i + 835*t] ? R[B[i + 835*t]] * R[C[i + 835*t]] : R[B[i + 835*t]] + R[C[i + 835*t]];
R[i + 1749*t] = Op[i + 836*t] ? R[B[i + 836*t]] * R[C[i + 836*t]] : R[B[i + 836*t]] + R[C[i + 836*t]];
R[i + 1750*t] = Op[i + 837*t] ? R[B[i + 837*t]] * R[C[i + 837*t]] : R[B[i + 837*t]] + R[C[i + 837*t]];
R[i + 1751*t] = Op[i + 838*t] ? R[B[i + 838*t]] * R[C[i + 838*t]] : R[B[i + 838*t]] + R[C[i + 838*t]];
R[i + 1752*t] = Op[i + 839*t] ? R[B[i + 839*t]] * R[C[i + 839*t]] : R[B[i + 839*t]] + R[C[i + 839*t]];
R[i + 1753*t] = Op[i + 840*t] ? R[B[i + 840*t]] * R[C[i + 840*t]] : R[B[i + 840*t]] + R[C[i + 840*t]];
R[i + 1754*t] = Op[i + 841*t] ? R[B[i + 841*t]] * R[C[i + 841*t]] : R[B[i + 841*t]] + R[C[i + 841*t]];
R[i + 1755*t] = Op[i + 842*t] ? R[B[i + 842*t]] * R[C[i + 842*t]] : R[B[i + 842*t]] + R[C[i + 842*t]];
R[i + 1756*t] = Op[i + 843*t] ? R[B[i + 843*t]] * R[C[i + 843*t]] : R[B[i + 843*t]] + R[C[i + 843*t]];
R[i + 1757*t] = Op[i + 844*t] ? R[B[i + 844*t]] * R[C[i + 844*t]] : R[B[i + 844*t]] + R[C[i + 844*t]];
R[i + 1758*t] = Op[i + 845*t] ? R[B[i + 845*t]] * R[C[i + 845*t]] : R[B[i + 845*t]] + R[C[i + 845*t]];
R[i + 1759*t] = Op[i + 846*t] ? R[B[i + 846*t]] * R[C[i + 846*t]] : R[B[i + 846*t]] + R[C[i + 846*t]];
R[i + 1760*t] = Op[i + 847*t] ? R[B[i + 847*t]] * R[C[i + 847*t]] : R[B[i + 847*t]] + R[C[i + 847*t]];
R[i + 1761*t] = Op[i + 848*t] ? R[B[i + 848*t]] * R[C[i + 848*t]] : R[B[i + 848*t]] + R[C[i + 848*t]];
R[i + 1762*t] = Op[i + 849*t] ? R[B[i + 849*t]] * R[C[i + 849*t]] : R[B[i + 849*t]] + R[C[i + 849*t]];
R[i + 1763*t] = Op[i + 850*t] ? R[B[i + 850*t]] * R[C[i + 850*t]] : R[B[i + 850*t]] + R[C[i + 850*t]];
R[i + 1764*t] = Op[i + 851*t] ? R[B[i + 851*t]] * R[C[i + 851*t]] : R[B[i + 851*t]] + R[C[i + 851*t]];
R[i + 1765*t] = Op[i + 852*t] ? R[B[i + 852*t]] * R[C[i + 852*t]] : R[B[i + 852*t]] + R[C[i + 852*t]];
R[i + 1766*t] = Op[i + 853*t] ? R[B[i + 853*t]] * R[C[i + 853*t]] : R[B[i + 853*t]] + R[C[i + 853*t]];
R[i + 1767*t] = Op[i + 854*t] ? R[B[i + 854*t]] * R[C[i + 854*t]] : R[B[i + 854*t]] + R[C[i + 854*t]];
R[i + 1768*t] = Op[i + 855*t] ? R[B[i + 855*t]] * R[C[i + 855*t]] : R[B[i + 855*t]] + R[C[i + 855*t]];
R[i + 1769*t] = Op[i + 856*t] ? R[B[i + 856*t]] * R[C[i + 856*t]] : R[B[i + 856*t]] + R[C[i + 856*t]];
R[i + 1770*t] = Op[i + 857*t] ? R[B[i + 857*t]] * R[C[i + 857*t]] : R[B[i + 857*t]] + R[C[i + 857*t]];
R[i + 1771*t] = Op[i + 858*t] ? R[B[i + 858*t]] * R[C[i + 858*t]] : R[B[i + 858*t]] + R[C[i + 858*t]];
R[i + 1772*t] = Op[i + 859*t] ? R[B[i + 859*t]] * R[C[i + 859*t]] : R[B[i + 859*t]] + R[C[i + 859*t]];
R[i + 1773*t] = Op[i + 860*t] ? R[B[i + 860*t]] * R[C[i + 860*t]] : R[B[i + 860*t]] + R[C[i + 860*t]];
R[i + 1774*t] = Op[i + 861*t] ? R[B[i + 861*t]] * R[C[i + 861*t]] : R[B[i + 861*t]] + R[C[i + 861*t]];
R[i + 1775*t] = Op[i + 862*t] ? R[B[i + 862*t]] * R[C[i + 862*t]] : R[B[i + 862*t]] + R[C[i + 862*t]];
R[i + 1776*t] = Op[i + 863*t] ? R[B[i + 863*t]] * R[C[i + 863*t]] : R[B[i + 863*t]] + R[C[i + 863*t]];
R[i + 1777*t] = Op[i + 864*t] ? R[B[i + 864*t]] * R[C[i + 864*t]] : R[B[i + 864*t]] + R[C[i + 864*t]];
R[i + 1778*t] = Op[i + 865*t] ? R[B[i + 865*t]] * R[C[i + 865*t]] : R[B[i + 865*t]] + R[C[i + 865*t]];
R[i + 1779*t] = Op[i + 866*t] ? R[B[i + 866*t]] * R[C[i + 866*t]] : R[B[i + 866*t]] + R[C[i + 866*t]];
R[i + 1780*t] = Op[i + 867*t] ? R[B[i + 867*t]] * R[C[i + 867*t]] : R[B[i + 867*t]] + R[C[i + 867*t]];
R[i + 1781*t] = Op[i + 868*t] ? R[B[i + 868*t]] * R[C[i + 868*t]] : R[B[i + 868*t]] + R[C[i + 868*t]];
R[i + 1782*t] = Op[i + 869*t] ? R[B[i + 869*t]] * R[C[i + 869*t]] : R[B[i + 869*t]] + R[C[i + 869*t]];
R[i + 1783*t] = Op[i + 870*t] ? R[B[i + 870*t]] * R[C[i + 870*t]] : R[B[i + 870*t]] + R[C[i + 870*t]];
R[i + 1784*t] = Op[i + 871*t] ? R[B[i + 871*t]] * R[C[i + 871*t]] : R[B[i + 871*t]] + R[C[i + 871*t]];
R[i + 1785*t] = Op[i + 872*t] ? R[B[i + 872*t]] * R[C[i + 872*t]] : R[B[i + 872*t]] + R[C[i + 872*t]];
R[i + 1786*t] = Op[i + 873*t] ? R[B[i + 873*t]] * R[C[i + 873*t]] : R[B[i + 873*t]] + R[C[i + 873*t]];
R[i + 1787*t] = Op[i + 874*t] ? R[B[i + 874*t]] * R[C[i + 874*t]] : R[B[i + 874*t]] + R[C[i + 874*t]];
R[i + 1788*t] = Op[i + 875*t] ? R[B[i + 875*t]] * R[C[i + 875*t]] : R[B[i + 875*t]] + R[C[i + 875*t]];
R[i + 1789*t] = Op[i + 876*t] ? R[B[i + 876*t]] * R[C[i + 876*t]] : R[B[i + 876*t]] + R[C[i + 876*t]];
R[i + 1790*t] = Op[i + 877*t] ? R[B[i + 877*t]] * R[C[i + 877*t]] : R[B[i + 877*t]] + R[C[i + 877*t]];
R[i + 1791*t] = Op[i + 878*t] ? R[B[i + 878*t]] * R[C[i + 878*t]] : R[B[i + 878*t]] + R[C[i + 878*t]];
R[i + 1792*t] = Op[i + 879*t] ? R[B[i + 879*t]] * R[C[i + 879*t]] : R[B[i + 879*t]] + R[C[i + 879*t]];
R[i + 1793*t] = Op[i + 880*t] ? R[B[i + 880*t]] * R[C[i + 880*t]] : R[B[i + 880*t]] + R[C[i + 880*t]];
R[i + 1794*t] = Op[i + 881*t] ? R[B[i + 881*t]] * R[C[i + 881*t]] : R[B[i + 881*t]] + R[C[i + 881*t]];
R[i + 1795*t] = Op[i + 882*t] ? R[B[i + 882*t]] * R[C[i + 882*t]] : R[B[i + 882*t]] + R[C[i + 882*t]];
R[i + 1796*t] = Op[i + 883*t] ? R[B[i + 883*t]] * R[C[i + 883*t]] : R[B[i + 883*t]] + R[C[i + 883*t]];
R[i + 1797*t] = Op[i + 884*t] ? R[B[i + 884*t]] * R[C[i + 884*t]] : R[B[i + 884*t]] + R[C[i + 884*t]];
R[i + 1798*t] = Op[i + 885*t] ? R[B[i + 885*t]] * R[C[i + 885*t]] : R[B[i + 885*t]] + R[C[i + 885*t]];
R[i + 1799*t] = Op[i + 886*t] ? R[B[i + 886*t]] * R[C[i + 886*t]] : R[B[i + 886*t]] + R[C[i + 886*t]];
R[i + 1800*t] = Op[i + 887*t] ? R[B[i + 887*t]] * R[C[i + 887*t]] : R[B[i + 887*t]] + R[C[i + 887*t]];
R[i + 1801*t] = Op[i + 888*t] ? R[B[i + 888*t]] * R[C[i + 888*t]] : R[B[i + 888*t]] + R[C[i + 888*t]];
R[i + 1802*t] = Op[i + 889*t] ? R[B[i + 889*t]] * R[C[i + 889*t]] : R[B[i + 889*t]] + R[C[i + 889*t]];
R[i + 1803*t] = Op[i + 890*t] ? R[B[i + 890*t]] * R[C[i + 890*t]] : R[B[i + 890*t]] + R[C[i + 890*t]];
R[i + 1804*t] = Op[i + 891*t] ? R[B[i + 891*t]] * R[C[i + 891*t]] : R[B[i + 891*t]] + R[C[i + 891*t]];
R[i + 1805*t] = Op[i + 892*t] ? R[B[i + 892*t]] * R[C[i + 892*t]] : R[B[i + 892*t]] + R[C[i + 892*t]];
R[i + 1806*t] = Op[i + 893*t] ? R[B[i + 893*t]] * R[C[i + 893*t]] : R[B[i + 893*t]] + R[C[i + 893*t]];
R[i + 1807*t] = Op[i + 894*t] ? R[B[i + 894*t]] * R[C[i + 894*t]] : R[B[i + 894*t]] + R[C[i + 894*t]];
R[i + 1808*t] = Op[i + 895*t] ? R[B[i + 895*t]] * R[C[i + 895*t]] : R[B[i + 895*t]] + R[C[i + 895*t]];
R[i + 1809*t] = Op[i + 896*t] ? R[B[i + 896*t]] * R[C[i + 896*t]] : R[B[i + 896*t]] + R[C[i + 896*t]];
R[i + 1810*t] = Op[i + 897*t] ? R[B[i + 897*t]] * R[C[i + 897*t]] : R[B[i + 897*t]] + R[C[i + 897*t]];
R[i + 1811*t] = Op[i + 898*t] ? R[B[i + 898*t]] * R[C[i + 898*t]] : R[B[i + 898*t]] + R[C[i + 898*t]];
R[i + 1812*t] = Op[i + 899*t] ? R[B[i + 899*t]] * R[C[i + 899*t]] : R[B[i + 899*t]] + R[C[i + 899*t]];
R[i + 1813*t] = Op[i + 900*t] ? R[B[i + 900*t]] * R[C[i + 900*t]] : R[B[i + 900*t]] + R[C[i + 900*t]];
R[i + 1814*t] = Op[i + 901*t] ? R[B[i + 901*t]] * R[C[i + 901*t]] : R[B[i + 901*t]] + R[C[i + 901*t]];
R[i + 1815*t] = Op[i + 902*t] ? R[B[i + 902*t]] * R[C[i + 902*t]] : R[B[i + 902*t]] + R[C[i + 902*t]];
R[i + 1816*t] = Op[i + 903*t] ? R[B[i + 903*t]] * R[C[i + 903*t]] : R[B[i + 903*t]] + R[C[i + 903*t]];
R[i + 1817*t] = Op[i + 904*t] ? R[B[i + 904*t]] * R[C[i + 904*t]] : R[B[i + 904*t]] + R[C[i + 904*t]];
R[i + 1818*t] = Op[i + 905*t] ? R[B[i + 905*t]] * R[C[i + 905*t]] : R[B[i + 905*t]] + R[C[i + 905*t]];
R[i + 1819*t] = Op[i + 906*t] ? R[B[i + 906*t]] * R[C[i + 906*t]] : R[B[i + 906*t]] + R[C[i + 906*t]];
R[i + 1820*t] = Op[i + 907*t] ? R[B[i + 907*t]] * R[C[i + 907*t]] : R[B[i + 907*t]] + R[C[i + 907*t]];
R[i + 1821*t] = Op[i + 908*t] ? R[B[i + 908*t]] * R[C[i + 908*t]] : R[B[i + 908*t]] + R[C[i + 908*t]];
R[i + 1822*t] = Op[i + 909*t] ? R[B[i + 909*t]] * R[C[i + 909*t]] : R[B[i + 909*t]] + R[C[i + 909*t]];
R[i + 1823*t] = Op[i + 910*t] ? R[B[i + 910*t]] * R[C[i + 910*t]] : R[B[i + 910*t]] + R[C[i + 910*t]];
R[i + 1824*t] = Op[i + 911*t] ? R[B[i + 911*t]] * R[C[i + 911*t]] : R[B[i + 911*t]] + R[C[i + 911*t]];
R[i + 1825*t] = Op[i + 912*t] ? R[B[i + 912*t]] * R[C[i + 912*t]] : R[B[i + 912*t]] + R[C[i + 912*t]];
R[i + 1826*t] = Op[i + 913*t] ? R[B[i + 913*t]] * R[C[i + 913*t]] : R[B[i + 913*t]] + R[C[i + 913*t]];
R[i + 1827*t] = Op[i + 914*t] ? R[B[i + 914*t]] * R[C[i + 914*t]] : R[B[i + 914*t]] + R[C[i + 914*t]];
R[i + 1828*t] = Op[i + 915*t] ? R[B[i + 915*t]] * R[C[i + 915*t]] : R[B[i + 915*t]] + R[C[i + 915*t]];
R[i + 1829*t] = Op[i + 916*t] ? R[B[i + 916*t]] * R[C[i + 916*t]] : R[B[i + 916*t]] + R[C[i + 916*t]];
R[i + 1830*t] = Op[i + 917*t] ? R[B[i + 917*t]] * R[C[i + 917*t]] : R[B[i + 917*t]] + R[C[i + 917*t]];
R[i + 1831*t] = Op[i + 918*t] ? R[B[i + 918*t]] * R[C[i + 918*t]] : R[B[i + 918*t]] + R[C[i + 918*t]];
R[i + 1832*t] = Op[i + 919*t] ? R[B[i + 919*t]] * R[C[i + 919*t]] : R[B[i + 919*t]] + R[C[i + 919*t]];
R[i + 1833*t] = Op[i + 920*t] ? R[B[i + 920*t]] * R[C[i + 920*t]] : R[B[i + 920*t]] + R[C[i + 920*t]];
R[i + 1834*t] = Op[i + 921*t] ? R[B[i + 921*t]] * R[C[i + 921*t]] : R[B[i + 921*t]] + R[C[i + 921*t]];
R[i + 1835*t] = Op[i + 922*t] ? R[B[i + 922*t]] * R[C[i + 922*t]] : R[B[i + 922*t]] + R[C[i + 922*t]];
R[i + 1836*t] = Op[i + 923*t] ? R[B[i + 923*t]] * R[C[i + 923*t]] : R[B[i + 923*t]] + R[C[i + 923*t]];
R[i + 1837*t] = Op[i + 924*t] ? R[B[i + 924*t]] * R[C[i + 924*t]] : R[B[i + 924*t]] + R[C[i + 924*t]];
R[i + 1838*t] = Op[i + 925*t] ? R[B[i + 925*t]] * R[C[i + 925*t]] : R[B[i + 925*t]] + R[C[i + 925*t]];
R[i + 1839*t] = Op[i + 926*t] ? R[B[i + 926*t]] * R[C[i + 926*t]] : R[B[i + 926*t]] + R[C[i + 926*t]];
R[i + 1840*t] = Op[i + 927*t] ? R[B[i + 927*t]] * R[C[i + 927*t]] : R[B[i + 927*t]] + R[C[i + 927*t]];
R[i + 1841*t] = Op[i + 928*t] ? R[B[i + 928*t]] * R[C[i + 928*t]] : R[B[i + 928*t]] + R[C[i + 928*t]];
R[i + 1842*t] = Op[i + 929*t] ? R[B[i + 929*t]] * R[C[i + 929*t]] : R[B[i + 929*t]] + R[C[i + 929*t]];
R[i + 1843*t] = Op[i + 930*t] ? R[B[i + 930*t]] * R[C[i + 930*t]] : R[B[i + 930*t]] + R[C[i + 930*t]];
R[i + 1844*t] = Op[i + 931*t] ? R[B[i + 931*t]] * R[C[i + 931*t]] : R[B[i + 931*t]] + R[C[i + 931*t]];
R[i + 1845*t] = Op[i + 932*t] ? R[B[i + 932*t]] * R[C[i + 932*t]] : R[B[i + 932*t]] + R[C[i + 932*t]];
R[i + 1846*t] = Op[i + 933*t] ? R[B[i + 933*t]] * R[C[i + 933*t]] : R[B[i + 933*t]] + R[C[i + 933*t]];
R[i + 1847*t] = Op[i + 934*t] ? R[B[i + 934*t]] * R[C[i + 934*t]] : R[B[i + 934*t]] + R[C[i + 934*t]];
R[i + 1848*t] = Op[i + 935*t] ? R[B[i + 935*t]] * R[C[i + 935*t]] : R[B[i + 935*t]] + R[C[i + 935*t]];
R[i + 1849*t] = Op[i + 936*t] ? R[B[i + 936*t]] * R[C[i + 936*t]] : R[B[i + 936*t]] + R[C[i + 936*t]];
R[i + 1850*t] = Op[i + 937*t] ? R[B[i + 937*t]] * R[C[i + 937*t]] : R[B[i + 937*t]] + R[C[i + 937*t]];
R[i + 1851*t] = Op[i + 938*t] ? R[B[i + 938*t]] * R[C[i + 938*t]] : R[B[i + 938*t]] + R[C[i + 938*t]];
R[i + 1852*t] = Op[i + 939*t] ? R[B[i + 939*t]] * R[C[i + 939*t]] : R[B[i + 939*t]] + R[C[i + 939*t]];
R[i + 1853*t] = Op[i + 940*t] ? R[B[i + 940*t]] * R[C[i + 940*t]] : R[B[i + 940*t]] + R[C[i + 940*t]];
R[i + 1854*t] = Op[i + 941*t] ? R[B[i + 941*t]] * R[C[i + 941*t]] : R[B[i + 941*t]] + R[C[i + 941*t]];
R[i + 1855*t] = Op[i + 942*t] ? R[B[i + 942*t]] * R[C[i + 942*t]] : R[B[i + 942*t]] + R[C[i + 942*t]];
R[i + 1856*t] = Op[i + 943*t] ? R[B[i + 943*t]] * R[C[i + 943*t]] : R[B[i + 943*t]] + R[C[i + 943*t]];
R[i + 1857*t] = Op[i + 944*t] ? R[B[i + 944*t]] * R[C[i + 944*t]] : R[B[i + 944*t]] + R[C[i + 944*t]];
R[i + 1858*t] = Op[i + 945*t] ? R[B[i + 945*t]] * R[C[i + 945*t]] : R[B[i + 945*t]] + R[C[i + 945*t]];
R[i + 1859*t] = Op[i + 946*t] ? R[B[i + 946*t]] * R[C[i + 946*t]] : R[B[i + 946*t]] + R[C[i + 946*t]];
R[i + 1860*t] = Op[i + 947*t] ? R[B[i + 947*t]] * R[C[i + 947*t]] : R[B[i + 947*t]] + R[C[i + 947*t]];
R[i + 1861*t] = Op[i + 948*t] ? R[B[i + 948*t]] * R[C[i + 948*t]] : R[B[i + 948*t]] + R[C[i + 948*t]];
R[i + 1862*t] = Op[i + 949*t] ? R[B[i + 949*t]] * R[C[i + 949*t]] : R[B[i + 949*t]] + R[C[i + 949*t]];
R[i + 1863*t] = Op[i + 950*t] ? R[B[i + 950*t]] * R[C[i + 950*t]] : R[B[i + 950*t]] + R[C[i + 950*t]];
R[i + 1864*t] = Op[i + 951*t] ? R[B[i + 951*t]] * R[C[i + 951*t]] : R[B[i + 951*t]] + R[C[i + 951*t]];
R[i + 1865*t] = Op[i + 952*t] ? R[B[i + 952*t]] * R[C[i + 952*t]] : R[B[i + 952*t]] + R[C[i + 952*t]];
R[i + 1866*t] = Op[i + 953*t] ? R[B[i + 953*t]] * R[C[i + 953*t]] : R[B[i + 953*t]] + R[C[i + 953*t]];
R[i + 1867*t] = Op[i + 954*t] ? R[B[i + 954*t]] * R[C[i + 954*t]] : R[B[i + 954*t]] + R[C[i + 954*t]];
R[i + 1868*t] = Op[i + 955*t] ? R[B[i + 955*t]] * R[C[i + 955*t]] : R[B[i + 955*t]] + R[C[i + 955*t]];
R[i + 1869*t] = Op[i + 956*t] ? R[B[i + 956*t]] * R[C[i + 956*t]] : R[B[i + 956*t]] + R[C[i + 956*t]];
R[i + 1870*t] = Op[i + 957*t] ? R[B[i + 957*t]] * R[C[i + 957*t]] : R[B[i + 957*t]] + R[C[i + 957*t]];
R[i + 1871*t] = Op[i + 958*t] ? R[B[i + 958*t]] * R[C[i + 958*t]] : R[B[i + 958*t]] + R[C[i + 958*t]];
R[i + 1872*t] = Op[i + 959*t] ? R[B[i + 959*t]] * R[C[i + 959*t]] : R[B[i + 959*t]] + R[C[i + 959*t]];
R[i + 1873*t] = Op[i + 960*t] ? R[B[i + 960*t]] * R[C[i + 960*t]] : R[B[i + 960*t]] + R[C[i + 960*t]];
R[i + 1874*t] = Op[i + 961*t] ? R[B[i + 961*t]] * R[C[i + 961*t]] : R[B[i + 961*t]] + R[C[i + 961*t]];
R[i + 1875*t] = Op[i + 962*t] ? R[B[i + 962*t]] * R[C[i + 962*t]] : R[B[i + 962*t]] + R[C[i + 962*t]];
R[i + 1876*t] = Op[i + 963*t] ? R[B[i + 963*t]] * R[C[i + 963*t]] : R[B[i + 963*t]] + R[C[i + 963*t]];
R[i + 1877*t] = Op[i + 964*t] ? R[B[i + 964*t]] * R[C[i + 964*t]] : R[B[i + 964*t]] + R[C[i + 964*t]];
R[i + 1878*t] = Op[i + 965*t] ? R[B[i + 965*t]] * R[C[i + 965*t]] : R[B[i + 965*t]] + R[C[i + 965*t]];
R[i + 1879*t] = Op[i + 966*t] ? R[B[i + 966*t]] * R[C[i + 966*t]] : R[B[i + 966*t]] + R[C[i + 966*t]];
R[i + 1880*t] = Op[i + 967*t] ? R[B[i + 967*t]] * R[C[i + 967*t]] : R[B[i + 967*t]] + R[C[i + 967*t]];
R[i + 1881*t] = Op[i + 968*t] ? R[B[i + 968*t]] * R[C[i + 968*t]] : R[B[i + 968*t]] + R[C[i + 968*t]];
R[i + 1882*t] = Op[i + 969*t] ? R[B[i + 969*t]] * R[C[i + 969*t]] : R[B[i + 969*t]] + R[C[i + 969*t]];
R[i + 1883*t] = Op[i + 970*t] ? R[B[i + 970*t]] * R[C[i + 970*t]] : R[B[i + 970*t]] + R[C[i + 970*t]];
R[i + 1884*t] = Op[i + 971*t] ? R[B[i + 971*t]] * R[C[i + 971*t]] : R[B[i + 971*t]] + R[C[i + 971*t]];
R[i + 1885*t] = Op[i + 972*t] ? R[B[i + 972*t]] * R[C[i + 972*t]] : R[B[i + 972*t]] + R[C[i + 972*t]];
R[i + 1886*t] = Op[i + 973*t] ? R[B[i + 973*t]] * R[C[i + 973*t]] : R[B[i + 973*t]] + R[C[i + 973*t]];
R[i + 1887*t] = Op[i + 974*t] ? R[B[i + 974*t]] * R[C[i + 974*t]] : R[B[i + 974*t]] + R[C[i + 974*t]];
R[i + 1888*t] = Op[i + 975*t] ? R[B[i + 975*t]] * R[C[i + 975*t]] : R[B[i + 975*t]] + R[C[i + 975*t]];
__syncthreads();
R[i + 1889*t] = Op[i + 976*t] ? R[B[i + 976*t]] * R[C[i + 976*t]] : R[B[i + 976*t]] + R[C[i + 976*t]];
R[i + 1890*t] = Op[i + 977*t] ? R[B[i + 977*t]] * R[C[i + 977*t]] : R[B[i + 977*t]] + R[C[i + 977*t]];
R[i + 1891*t] = Op[i + 978*t] ? R[B[i + 978*t]] * R[C[i + 978*t]] : R[B[i + 978*t]] + R[C[i + 978*t]];
R[i + 1892*t] = Op[i + 979*t] ? R[B[i + 979*t]] * R[C[i + 979*t]] : R[B[i + 979*t]] + R[C[i + 979*t]];
R[i + 1893*t] = Op[i + 980*t] ? R[B[i + 980*t]] * R[C[i + 980*t]] : R[B[i + 980*t]] + R[C[i + 980*t]];
R[i + 1894*t] = Op[i + 981*t] ? R[B[i + 981*t]] * R[C[i + 981*t]] : R[B[i + 981*t]] + R[C[i + 981*t]];
R[i + 1895*t] = Op[i + 982*t] ? R[B[i + 982*t]] * R[C[i + 982*t]] : R[B[i + 982*t]] + R[C[i + 982*t]];
R[i + 1896*t] = Op[i + 983*t] ? R[B[i + 983*t]] * R[C[i + 983*t]] : R[B[i + 983*t]] + R[C[i + 983*t]];
R[i + 1897*t] = Op[i + 984*t] ? R[B[i + 984*t]] * R[C[i + 984*t]] : R[B[i + 984*t]] + R[C[i + 984*t]];
R[i + 1898*t] = Op[i + 985*t] ? R[B[i + 985*t]] * R[C[i + 985*t]] : R[B[i + 985*t]] + R[C[i + 985*t]];
R[i + 1899*t] = Op[i + 986*t] ? R[B[i + 986*t]] * R[C[i + 986*t]] : R[B[i + 986*t]] + R[C[i + 986*t]];
R[i + 1900*t] = Op[i + 987*t] ? R[B[i + 987*t]] * R[C[i + 987*t]] : R[B[i + 987*t]] + R[C[i + 987*t]];
R[i + 1901*t] = Op[i + 988*t] ? R[B[i + 988*t]] * R[C[i + 988*t]] : R[B[i + 988*t]] + R[C[i + 988*t]];
R[i + 1902*t] = Op[i + 989*t] ? R[B[i + 989*t]] * R[C[i + 989*t]] : R[B[i + 989*t]] + R[C[i + 989*t]];
R[i + 1903*t] = Op[i + 990*t] ? R[B[i + 990*t]] * R[C[i + 990*t]] : R[B[i + 990*t]] + R[C[i + 990*t]];
R[i + 1904*t] = Op[i + 991*t] ? R[B[i + 991*t]] * R[C[i + 991*t]] : R[B[i + 991*t]] + R[C[i + 991*t]];
R[i + 1905*t] = Op[i + 992*t] ? R[B[i + 992*t]] * R[C[i + 992*t]] : R[B[i + 992*t]] + R[C[i + 992*t]];
R[i + 1906*t] = Op[i + 993*t] ? R[B[i + 993*t]] * R[C[i + 993*t]] : R[B[i + 993*t]] + R[C[i + 993*t]];
R[i + 1907*t] = Op[i + 994*t] ? R[B[i + 994*t]] * R[C[i + 994*t]] : R[B[i + 994*t]] + R[C[i + 994*t]];
R[i + 1908*t] = Op[i + 995*t] ? R[B[i + 995*t]] * R[C[i + 995*t]] : R[B[i + 995*t]] + R[C[i + 995*t]];
R[i + 1909*t] = Op[i + 996*t] ? R[B[i + 996*t]] * R[C[i + 996*t]] : R[B[i + 996*t]] + R[C[i + 996*t]];
R[i + 1910*t] = Op[i + 997*t] ? R[B[i + 997*t]] * R[C[i + 997*t]] : R[B[i + 997*t]] + R[C[i + 997*t]];
R[i + 1911*t] = Op[i + 998*t] ? R[B[i + 998*t]] * R[C[i + 998*t]] : R[B[i + 998*t]] + R[C[i + 998*t]];
R[i + 1912*t] = Op[i + 999*t] ? R[B[i + 999*t]] * R[C[i + 999*t]] : R[B[i + 999*t]] + R[C[i + 999*t]];
R[i + 1913*t] = Op[i + 1000*t] ? R[B[i + 1000*t]] * R[C[i + 1000*t]] : R[B[i + 1000*t]] + R[C[i + 1000*t]];
R[i + 1914*t] = Op[i + 1001*t] ? R[B[i + 1001*t]] * R[C[i + 1001*t]] : R[B[i + 1001*t]] + R[C[i + 1001*t]];
R[i + 1915*t] = Op[i + 1002*t] ? R[B[i + 1002*t]] * R[C[i + 1002*t]] : R[B[i + 1002*t]] + R[C[i + 1002*t]];
R[i + 1916*t] = Op[i + 1003*t] ? R[B[i + 1003*t]] * R[C[i + 1003*t]] : R[B[i + 1003*t]] + R[C[i + 1003*t]];
R[i + 1917*t] = Op[i + 1004*t] ? R[B[i + 1004*t]] * R[C[i + 1004*t]] : R[B[i + 1004*t]] + R[C[i + 1004*t]];
R[i + 1918*t] = Op[i + 1005*t] ? R[B[i + 1005*t]] * R[C[i + 1005*t]] : R[B[i + 1005*t]] + R[C[i + 1005*t]];
R[i + 1919*t] = Op[i + 1006*t] ? R[B[i + 1006*t]] * R[C[i + 1006*t]] : R[B[i + 1006*t]] + R[C[i + 1006*t]];
R[i + 1920*t] = Op[i + 1007*t] ? R[B[i + 1007*t]] * R[C[i + 1007*t]] : R[B[i + 1007*t]] + R[C[i + 1007*t]];
R[i + 1921*t] = Op[i + 1008*t] ? R[B[i + 1008*t]] * R[C[i + 1008*t]] : R[B[i + 1008*t]] + R[C[i + 1008*t]];
R[i + 1922*t] = Op[i + 1009*t] ? R[B[i + 1009*t]] * R[C[i + 1009*t]] : R[B[i + 1009*t]] + R[C[i + 1009*t]];
R[i + 1923*t] = Op[i + 1010*t] ? R[B[i + 1010*t]] * R[C[i + 1010*t]] : R[B[i + 1010*t]] + R[C[i + 1010*t]];
R[i + 1924*t] = Op[i + 1011*t] ? R[B[i + 1011*t]] * R[C[i + 1011*t]] : R[B[i + 1011*t]] + R[C[i + 1011*t]];
R[i + 1925*t] = Op[i + 1012*t] ? R[B[i + 1012*t]] * R[C[i + 1012*t]] : R[B[i + 1012*t]] + R[C[i + 1012*t]];
R[i + 1926*t] = Op[i + 1013*t] ? R[B[i + 1013*t]] * R[C[i + 1013*t]] : R[B[i + 1013*t]] + R[C[i + 1013*t]];
R[i + 1927*t] = Op[i + 1014*t] ? R[B[i + 1014*t]] * R[C[i + 1014*t]] : R[B[i + 1014*t]] + R[C[i + 1014*t]];
R[i + 1928*t] = Op[i + 1015*t] ? R[B[i + 1015*t]] * R[C[i + 1015*t]] : R[B[i + 1015*t]] + R[C[i + 1015*t]];
R[i + 1929*t] = Op[i + 1016*t] ? R[B[i + 1016*t]] * R[C[i + 1016*t]] : R[B[i + 1016*t]] + R[C[i + 1016*t]];
R[i + 1930*t] = Op[i + 1017*t] ? R[B[i + 1017*t]] * R[C[i + 1017*t]] : R[B[i + 1017*t]] + R[C[i + 1017*t]];
R[i + 1931*t] = Op[i + 1018*t] ? R[B[i + 1018*t]] * R[C[i + 1018*t]] : R[B[i + 1018*t]] + R[C[i + 1018*t]];
R[i + 1932*t] = Op[i + 1019*t] ? R[B[i + 1019*t]] * R[C[i + 1019*t]] : R[B[i + 1019*t]] + R[C[i + 1019*t]];
R[i + 1933*t] = Op[i + 1020*t] ? R[B[i + 1020*t]] * R[C[i + 1020*t]] : R[B[i + 1020*t]] + R[C[i + 1020*t]];
R[i + 1934*t] = Op[i + 1021*t] ? R[B[i + 1021*t]] * R[C[i + 1021*t]] : R[B[i + 1021*t]] + R[C[i + 1021*t]];
R[i + 1935*t] = Op[i + 1022*t] ? R[B[i + 1022*t]] * R[C[i + 1022*t]] : R[B[i + 1022*t]] + R[C[i + 1022*t]];
R[i + 1936*t] = Op[i + 1023*t] ? R[B[i + 1023*t]] * R[C[i + 1023*t]] : R[B[i + 1023*t]] + R[C[i + 1023*t]];
R[i + 1937*t] = Op[i + 1024*t] ? R[B[i + 1024*t]] * R[C[i + 1024*t]] : R[B[i + 1024*t]] + R[C[i + 1024*t]];
R[i + 1938*t] = Op[i + 1025*t] ? R[B[i + 1025*t]] * R[C[i + 1025*t]] : R[B[i + 1025*t]] + R[C[i + 1025*t]];
R[i + 1939*t] = Op[i + 1026*t] ? R[B[i + 1026*t]] * R[C[i + 1026*t]] : R[B[i + 1026*t]] + R[C[i + 1026*t]];
R[i + 1940*t] = Op[i + 1027*t] ? R[B[i + 1027*t]] * R[C[i + 1027*t]] : R[B[i + 1027*t]] + R[C[i + 1027*t]];
R[i + 1941*t] = Op[i + 1028*t] ? R[B[i + 1028*t]] * R[C[i + 1028*t]] : R[B[i + 1028*t]] + R[C[i + 1028*t]];
R[i + 1942*t] = Op[i + 1029*t] ? R[B[i + 1029*t]] * R[C[i + 1029*t]] : R[B[i + 1029*t]] + R[C[i + 1029*t]];
R[i + 1943*t] = Op[i + 1030*t] ? R[B[i + 1030*t]] * R[C[i + 1030*t]] : R[B[i + 1030*t]] + R[C[i + 1030*t]];
R[i + 1944*t] = Op[i + 1031*t] ? R[B[i + 1031*t]] * R[C[i + 1031*t]] : R[B[i + 1031*t]] + R[C[i + 1031*t]];
R[i + 1945*t] = Op[i + 1032*t] ? R[B[i + 1032*t]] * R[C[i + 1032*t]] : R[B[i + 1032*t]] + R[C[i + 1032*t]];
R[i + 1946*t] = Op[i + 1033*t] ? R[B[i + 1033*t]] * R[C[i + 1033*t]] : R[B[i + 1033*t]] + R[C[i + 1033*t]];
R[i + 1947*t] = Op[i + 1034*t] ? R[B[i + 1034*t]] * R[C[i + 1034*t]] : R[B[i + 1034*t]] + R[C[i + 1034*t]];
R[i + 1948*t] = Op[i + 1035*t] ? R[B[i + 1035*t]] * R[C[i + 1035*t]] : R[B[i + 1035*t]] + R[C[i + 1035*t]];
R[i + 1949*t] = Op[i + 1036*t] ? R[B[i + 1036*t]] * R[C[i + 1036*t]] : R[B[i + 1036*t]] + R[C[i + 1036*t]];
R[i + 1950*t] = Op[i + 1037*t] ? R[B[i + 1037*t]] * R[C[i + 1037*t]] : R[B[i + 1037*t]] + R[C[i + 1037*t]];
R[i + 1951*t] = Op[i + 1038*t] ? R[B[i + 1038*t]] * R[C[i + 1038*t]] : R[B[i + 1038*t]] + R[C[i + 1038*t]];
R[i + 1952*t] = Op[i + 1039*t] ? R[B[i + 1039*t]] * R[C[i + 1039*t]] : R[B[i + 1039*t]] + R[C[i + 1039*t]];
R[i + 1953*t] = Op[i + 1040*t] ? R[B[i + 1040*t]] * R[C[i + 1040*t]] : R[B[i + 1040*t]] + R[C[i + 1040*t]];
R[i + 1954*t] = Op[i + 1041*t] ? R[B[i + 1041*t]] * R[C[i + 1041*t]] : R[B[i + 1041*t]] + R[C[i + 1041*t]];
R[i + 1955*t] = Op[i + 1042*t] ? R[B[i + 1042*t]] * R[C[i + 1042*t]] : R[B[i + 1042*t]] + R[C[i + 1042*t]];
R[i + 1956*t] = Op[i + 1043*t] ? R[B[i + 1043*t]] * R[C[i + 1043*t]] : R[B[i + 1043*t]] + R[C[i + 1043*t]];
R[i + 1957*t] = Op[i + 1044*t] ? R[B[i + 1044*t]] * R[C[i + 1044*t]] : R[B[i + 1044*t]] + R[C[i + 1044*t]];
R[i + 1958*t] = Op[i + 1045*t] ? R[B[i + 1045*t]] * R[C[i + 1045*t]] : R[B[i + 1045*t]] + R[C[i + 1045*t]];
R[i + 1959*t] = Op[i + 1046*t] ? R[B[i + 1046*t]] * R[C[i + 1046*t]] : R[B[i + 1046*t]] + R[C[i + 1046*t]];
R[i + 1960*t] = Op[i + 1047*t] ? R[B[i + 1047*t]] * R[C[i + 1047*t]] : R[B[i + 1047*t]] + R[C[i + 1047*t]];
R[i + 1961*t] = Op[i + 1048*t] ? R[B[i + 1048*t]] * R[C[i + 1048*t]] : R[B[i + 1048*t]] + R[C[i + 1048*t]];
R[i + 1962*t] = Op[i + 1049*t] ? R[B[i + 1049*t]] * R[C[i + 1049*t]] : R[B[i + 1049*t]] + R[C[i + 1049*t]];
R[i + 1963*t] = Op[i + 1050*t] ? R[B[i + 1050*t]] * R[C[i + 1050*t]] : R[B[i + 1050*t]] + R[C[i + 1050*t]];
R[i + 1964*t] = Op[i + 1051*t] ? R[B[i + 1051*t]] * R[C[i + 1051*t]] : R[B[i + 1051*t]] + R[C[i + 1051*t]];
R[i + 1965*t] = Op[i + 1052*t] ? R[B[i + 1052*t]] * R[C[i + 1052*t]] : R[B[i + 1052*t]] + R[C[i + 1052*t]];
R[i + 1966*t] = Op[i + 1053*t] ? R[B[i + 1053*t]] * R[C[i + 1053*t]] : R[B[i + 1053*t]] + R[C[i + 1053*t]];
R[i + 1967*t] = Op[i + 1054*t] ? R[B[i + 1054*t]] * R[C[i + 1054*t]] : R[B[i + 1054*t]] + R[C[i + 1054*t]];
R[i + 1968*t] = Op[i + 1055*t] ? R[B[i + 1055*t]] * R[C[i + 1055*t]] : R[B[i + 1055*t]] + R[C[i + 1055*t]];
R[i + 1969*t] = Op[i + 1056*t] ? R[B[i + 1056*t]] * R[C[i + 1056*t]] : R[B[i + 1056*t]] + R[C[i + 1056*t]];
R[i + 1970*t] = Op[i + 1057*t] ? R[B[i + 1057*t]] * R[C[i + 1057*t]] : R[B[i + 1057*t]] + R[C[i + 1057*t]];
R[i + 1971*t] = Op[i + 1058*t] ? R[B[i + 1058*t]] * R[C[i + 1058*t]] : R[B[i + 1058*t]] + R[C[i + 1058*t]];
R[i + 1972*t] = Op[i + 1059*t] ? R[B[i + 1059*t]] * R[C[i + 1059*t]] : R[B[i + 1059*t]] + R[C[i + 1059*t]];
R[i + 1973*t] = Op[i + 1060*t] ? R[B[i + 1060*t]] * R[C[i + 1060*t]] : R[B[i + 1060*t]] + R[C[i + 1060*t]];
R[i + 1974*t] = Op[i + 1061*t] ? R[B[i + 1061*t]] * R[C[i + 1061*t]] : R[B[i + 1061*t]] + R[C[i + 1061*t]];
R[i + 1975*t] = Op[i + 1062*t] ? R[B[i + 1062*t]] * R[C[i + 1062*t]] : R[B[i + 1062*t]] + R[C[i + 1062*t]];
R[i + 1976*t] = Op[i + 1063*t] ? R[B[i + 1063*t]] * R[C[i + 1063*t]] : R[B[i + 1063*t]] + R[C[i + 1063*t]];
R[i + 1977*t] = Op[i + 1064*t] ? R[B[i + 1064*t]] * R[C[i + 1064*t]] : R[B[i + 1064*t]] + R[C[i + 1064*t]];
R[i + 1978*t] = Op[i + 1065*t] ? R[B[i + 1065*t]] * R[C[i + 1065*t]] : R[B[i + 1065*t]] + R[C[i + 1065*t]];
R[i + 1979*t] = Op[i + 1066*t] ? R[B[i + 1066*t]] * R[C[i + 1066*t]] : R[B[i + 1066*t]] + R[C[i + 1066*t]];
R[i + 1980*t] = Op[i + 1067*t] ? R[B[i + 1067*t]] * R[C[i + 1067*t]] : R[B[i + 1067*t]] + R[C[i + 1067*t]];
R[i + 1981*t] = Op[i + 1068*t] ? R[B[i + 1068*t]] * R[C[i + 1068*t]] : R[B[i + 1068*t]] + R[C[i + 1068*t]];
R[i + 1982*t] = Op[i + 1069*t] ? R[B[i + 1069*t]] * R[C[i + 1069*t]] : R[B[i + 1069*t]] + R[C[i + 1069*t]];
R[i + 1983*t] = Op[i + 1070*t] ? R[B[i + 1070*t]] * R[C[i + 1070*t]] : R[B[i + 1070*t]] + R[C[i + 1070*t]];
R[i + 1984*t] = Op[i + 1071*t] ? R[B[i + 1071*t]] * R[C[i + 1071*t]] : R[B[i + 1071*t]] + R[C[i + 1071*t]];
R[i + 1985*t] = Op[i + 1072*t] ? R[B[i + 1072*t]] * R[C[i + 1072*t]] : R[B[i + 1072*t]] + R[C[i + 1072*t]];
R[i + 1986*t] = Op[i + 1073*t] ? R[B[i + 1073*t]] * R[C[i + 1073*t]] : R[B[i + 1073*t]] + R[C[i + 1073*t]];
R[i + 1987*t] = Op[i + 1074*t] ? R[B[i + 1074*t]] * R[C[i + 1074*t]] : R[B[i + 1074*t]] + R[C[i + 1074*t]];
R[i + 1988*t] = Op[i + 1075*t] ? R[B[i + 1075*t]] * R[C[i + 1075*t]] : R[B[i + 1075*t]] + R[C[i + 1075*t]];
R[i + 1989*t] = Op[i + 1076*t] ? R[B[i + 1076*t]] * R[C[i + 1076*t]] : R[B[i + 1076*t]] + R[C[i + 1076*t]];
R[i + 1990*t] = Op[i + 1077*t] ? R[B[i + 1077*t]] * R[C[i + 1077*t]] : R[B[i + 1077*t]] + R[C[i + 1077*t]];
R[i + 1991*t] = Op[i + 1078*t] ? R[B[i + 1078*t]] * R[C[i + 1078*t]] : R[B[i + 1078*t]] + R[C[i + 1078*t]];
R[i + 1992*t] = Op[i + 1079*t] ? R[B[i + 1079*t]] * R[C[i + 1079*t]] : R[B[i + 1079*t]] + R[C[i + 1079*t]];
R[i + 1993*t] = Op[i + 1080*t] ? R[B[i + 1080*t]] * R[C[i + 1080*t]] : R[B[i + 1080*t]] + R[C[i + 1080*t]];
R[i + 1994*t] = Op[i + 1081*t] ? R[B[i + 1081*t]] * R[C[i + 1081*t]] : R[B[i + 1081*t]] + R[C[i + 1081*t]];
R[i + 1995*t] = Op[i + 1082*t] ? R[B[i + 1082*t]] * R[C[i + 1082*t]] : R[B[i + 1082*t]] + R[C[i + 1082*t]];
R[i + 1996*t] = Op[i + 1083*t] ? R[B[i + 1083*t]] * R[C[i + 1083*t]] : R[B[i + 1083*t]] + R[C[i + 1083*t]];
R[i + 1997*t] = Op[i + 1084*t] ? R[B[i + 1084*t]] * R[C[i + 1084*t]] : R[B[i + 1084*t]] + R[C[i + 1084*t]];
R[i + 1998*t] = Op[i + 1085*t] ? R[B[i + 1085*t]] * R[C[i + 1085*t]] : R[B[i + 1085*t]] + R[C[i + 1085*t]];
R[i + 1999*t] = Op[i + 1086*t] ? R[B[i + 1086*t]] * R[C[i + 1086*t]] : R[B[i + 1086*t]] + R[C[i + 1086*t]];
R[i + 2000*t] = Op[i + 1087*t] ? R[B[i + 1087*t]] * R[C[i + 1087*t]] : R[B[i + 1087*t]] + R[C[i + 1087*t]];
R[i + 2001*t] = Op[i + 1088*t] ? R[B[i + 1088*t]] * R[C[i + 1088*t]] : R[B[i + 1088*t]] + R[C[i + 1088*t]];
R[i + 2002*t] = Op[i + 1089*t] ? R[B[i + 1089*t]] * R[C[i + 1089*t]] : R[B[i + 1089*t]] + R[C[i + 1089*t]];
R[i + 2003*t] = Op[i + 1090*t] ? R[B[i + 1090*t]] * R[C[i + 1090*t]] : R[B[i + 1090*t]] + R[C[i + 1090*t]];
R[i + 2004*t] = Op[i + 1091*t] ? R[B[i + 1091*t]] * R[C[i + 1091*t]] : R[B[i + 1091*t]] + R[C[i + 1091*t]];
R[i + 2005*t] = Op[i + 1092*t] ? R[B[i + 1092*t]] * R[C[i + 1092*t]] : R[B[i + 1092*t]] + R[C[i + 1092*t]];
R[i + 2006*t] = Op[i + 1093*t] ? R[B[i + 1093*t]] * R[C[i + 1093*t]] : R[B[i + 1093*t]] + R[C[i + 1093*t]];
R[i + 2007*t] = Op[i + 1094*t] ? R[B[i + 1094*t]] * R[C[i + 1094*t]] : R[B[i + 1094*t]] + R[C[i + 1094*t]];
R[i + 2008*t] = Op[i + 1095*t] ? R[B[i + 1095*t]] * R[C[i + 1095*t]] : R[B[i + 1095*t]] + R[C[i + 1095*t]];
R[i + 2009*t] = Op[i + 1096*t] ? R[B[i + 1096*t]] * R[C[i + 1096*t]] : R[B[i + 1096*t]] + R[C[i + 1096*t]];
R[i + 2010*t] = Op[i + 1097*t] ? R[B[i + 1097*t]] * R[C[i + 1097*t]] : R[B[i + 1097*t]] + R[C[i + 1097*t]];
R[i + 2011*t] = Op[i + 1098*t] ? R[B[i + 1098*t]] * R[C[i + 1098*t]] : R[B[i + 1098*t]] + R[C[i + 1098*t]];
R[i + 2012*t] = Op[i + 1099*t] ? R[B[i + 1099*t]] * R[C[i + 1099*t]] : R[B[i + 1099*t]] + R[C[i + 1099*t]];
R[i + 2013*t] = Op[i + 1100*t] ? R[B[i + 1100*t]] * R[C[i + 1100*t]] : R[B[i + 1100*t]] + R[C[i + 1100*t]];
R[i + 2014*t] = Op[i + 1101*t] ? R[B[i + 1101*t]] * R[C[i + 1101*t]] : R[B[i + 1101*t]] + R[C[i + 1101*t]];
R[i + 2015*t] = Op[i + 1102*t] ? R[B[i + 1102*t]] * R[C[i + 1102*t]] : R[B[i + 1102*t]] + R[C[i + 1102*t]];
R[i + 2016*t] = Op[i + 1103*t] ? R[B[i + 1103*t]] * R[C[i + 1103*t]] : R[B[i + 1103*t]] + R[C[i + 1103*t]];
R[i + 2017*t] = Op[i + 1104*t] ? R[B[i + 1104*t]] * R[C[i + 1104*t]] : R[B[i + 1104*t]] + R[C[i + 1104*t]];
R[i + 2018*t] = Op[i + 1105*t] ? R[B[i + 1105*t]] * R[C[i + 1105*t]] : R[B[i + 1105*t]] + R[C[i + 1105*t]];
R[i + 2019*t] = Op[i + 1106*t] ? R[B[i + 1106*t]] * R[C[i + 1106*t]] : R[B[i + 1106*t]] + R[C[i + 1106*t]];
R[i + 2020*t] = Op[i + 1107*t] ? R[B[i + 1107*t]] * R[C[i + 1107*t]] : R[B[i + 1107*t]] + R[C[i + 1107*t]];
R[i + 2021*t] = Op[i + 1108*t] ? R[B[i + 1108*t]] * R[C[i + 1108*t]] : R[B[i + 1108*t]] + R[C[i + 1108*t]];
R[i + 2022*t] = Op[i + 1109*t] ? R[B[i + 1109*t]] * R[C[i + 1109*t]] : R[B[i + 1109*t]] + R[C[i + 1109*t]];
R[i + 2023*t] = Op[i + 1110*t] ? R[B[i + 1110*t]] * R[C[i + 1110*t]] : R[B[i + 1110*t]] + R[C[i + 1110*t]];
__syncthreads();
R[i + 2024*t] = Op[i + 1111*t] ? R[B[i + 1111*t]] * R[C[i + 1111*t]] : R[B[i + 1111*t]] + R[C[i + 1111*t]];
R[i + 2025*t] = Op[i + 1112*t] ? R[B[i + 1112*t]] * R[C[i + 1112*t]] : R[B[i + 1112*t]] + R[C[i + 1112*t]];
R[i + 2026*t] = Op[i + 1113*t] ? R[B[i + 1113*t]] * R[C[i + 1113*t]] : R[B[i + 1113*t]] + R[C[i + 1113*t]];
R[i + 2027*t] = Op[i + 1114*t] ? R[B[i + 1114*t]] * R[C[i + 1114*t]] : R[B[i + 1114*t]] + R[C[i + 1114*t]];
R[i + 2028*t] = Op[i + 1115*t] ? R[B[i + 1115*t]] * R[C[i + 1115*t]] : R[B[i + 1115*t]] + R[C[i + 1115*t]];
R[i + 2029*t] = Op[i + 1116*t] ? R[B[i + 1116*t]] * R[C[i + 1116*t]] : R[B[i + 1116*t]] + R[C[i + 1116*t]];
R[i + 2030*t] = Op[i + 1117*t] ? R[B[i + 1117*t]] * R[C[i + 1117*t]] : R[B[i + 1117*t]] + R[C[i + 1117*t]];
R[i + 2031*t] = Op[i + 1118*t] ? R[B[i + 1118*t]] * R[C[i + 1118*t]] : R[B[i + 1118*t]] + R[C[i + 1118*t]];
R[i + 2032*t] = Op[i + 1119*t] ? R[B[i + 1119*t]] * R[C[i + 1119*t]] : R[B[i + 1119*t]] + R[C[i + 1119*t]];
R[i + 2033*t] = Op[i + 1120*t] ? R[B[i + 1120*t]] * R[C[i + 1120*t]] : R[B[i + 1120*t]] + R[C[i + 1120*t]];
R[i + 2034*t] = Op[i + 1121*t] ? R[B[i + 1121*t]] * R[C[i + 1121*t]] : R[B[i + 1121*t]] + R[C[i + 1121*t]];
R[i + 2035*t] = Op[i + 1122*t] ? R[B[i + 1122*t]] * R[C[i + 1122*t]] : R[B[i + 1122*t]] + R[C[i + 1122*t]];
R[i + 2036*t] = Op[i + 1123*t] ? R[B[i + 1123*t]] * R[C[i + 1123*t]] : R[B[i + 1123*t]] + R[C[i + 1123*t]];
R[i + 2037*t] = Op[i + 1124*t] ? R[B[i + 1124*t]] * R[C[i + 1124*t]] : R[B[i + 1124*t]] + R[C[i + 1124*t]];
R[i + 2038*t] = Op[i + 1125*t] ? R[B[i + 1125*t]] * R[C[i + 1125*t]] : R[B[i + 1125*t]] + R[C[i + 1125*t]];
R[i + 2039*t] = Op[i + 1126*t] ? R[B[i + 1126*t]] * R[C[i + 1126*t]] : R[B[i + 1126*t]] + R[C[i + 1126*t]];
R[i + 2040*t] = Op[i + 1127*t] ? R[B[i + 1127*t]] * R[C[i + 1127*t]] : R[B[i + 1127*t]] + R[C[i + 1127*t]];
R[i + 2041*t] = Op[i + 1128*t] ? R[B[i + 1128*t]] * R[C[i + 1128*t]] : R[B[i + 1128*t]] + R[C[i + 1128*t]];
R[i + 2042*t] = Op[i + 1129*t] ? R[B[i + 1129*t]] * R[C[i + 1129*t]] : R[B[i + 1129*t]] + R[C[i + 1129*t]];
R[i + 2043*t] = Op[i + 1130*t] ? R[B[i + 1130*t]] * R[C[i + 1130*t]] : R[B[i + 1130*t]] + R[C[i + 1130*t]];
R[i + 2044*t] = Op[i + 1131*t] ? R[B[i + 1131*t]] * R[C[i + 1131*t]] : R[B[i + 1131*t]] + R[C[i + 1131*t]];
R[i + 2045*t] = Op[i + 1132*t] ? R[B[i + 1132*t]] * R[C[i + 1132*t]] : R[B[i + 1132*t]] + R[C[i + 1132*t]];
R[i + 2046*t] = Op[i + 1133*t] ? R[B[i + 1133*t]] * R[C[i + 1133*t]] : R[B[i + 1133*t]] + R[C[i + 1133*t]];
R[i + 2047*t] = Op[i + 1134*t] ? R[B[i + 1134*t]] * R[C[i + 1134*t]] : R[B[i + 1134*t]] + R[C[i + 1134*t]];
R[i + 2048*t] = Op[i + 1135*t] ? R[B[i + 1135*t]] * R[C[i + 1135*t]] : R[B[i + 1135*t]] + R[C[i + 1135*t]];
R[i + 2049*t] = Op[i + 1136*t] ? R[B[i + 1136*t]] * R[C[i + 1136*t]] : R[B[i + 1136*t]] + R[C[i + 1136*t]];
R[i + 2050*t] = Op[i + 1137*t] ? R[B[i + 1137*t]] * R[C[i + 1137*t]] : R[B[i + 1137*t]] + R[C[i + 1137*t]];
R[i + 2051*t] = Op[i + 1138*t] ? R[B[i + 1138*t]] * R[C[i + 1138*t]] : R[B[i + 1138*t]] + R[C[i + 1138*t]];
R[i + 2052*t] = Op[i + 1139*t] ? R[B[i + 1139*t]] * R[C[i + 1139*t]] : R[B[i + 1139*t]] + R[C[i + 1139*t]];
R[i + 2053*t] = Op[i + 1140*t] ? R[B[i + 1140*t]] * R[C[i + 1140*t]] : R[B[i + 1140*t]] + R[C[i + 1140*t]];
R[i + 2054*t] = Op[i + 1141*t] ? R[B[i + 1141*t]] * R[C[i + 1141*t]] : R[B[i + 1141*t]] + R[C[i + 1141*t]];
R[i + 2055*t] = Op[i + 1142*t] ? R[B[i + 1142*t]] * R[C[i + 1142*t]] : R[B[i + 1142*t]] + R[C[i + 1142*t]];
R[i + 2056*t] = Op[i + 1143*t] ? R[B[i + 1143*t]] * R[C[i + 1143*t]] : R[B[i + 1143*t]] + R[C[i + 1143*t]];
R[i + 2057*t] = Op[i + 1144*t] ? R[B[i + 1144*t]] * R[C[i + 1144*t]] : R[B[i + 1144*t]] + R[C[i + 1144*t]];
R[i + 2058*t] = Op[i + 1145*t] ? R[B[i + 1145*t]] * R[C[i + 1145*t]] : R[B[i + 1145*t]] + R[C[i + 1145*t]];
R[i + 2059*t] = Op[i + 1146*t] ? R[B[i + 1146*t]] * R[C[i + 1146*t]] : R[B[i + 1146*t]] + R[C[i + 1146*t]];
R[i + 2060*t] = Op[i + 1147*t] ? R[B[i + 1147*t]] * R[C[i + 1147*t]] : R[B[i + 1147*t]] + R[C[i + 1147*t]];
R[i + 2061*t] = Op[i + 1148*t] ? R[B[i + 1148*t]] * R[C[i + 1148*t]] : R[B[i + 1148*t]] + R[C[i + 1148*t]];
R[i + 2062*t] = Op[i + 1149*t] ? R[B[i + 1149*t]] * R[C[i + 1149*t]] : R[B[i + 1149*t]] + R[C[i + 1149*t]];
R[i + 2063*t] = Op[i + 1150*t] ? R[B[i + 1150*t]] * R[C[i + 1150*t]] : R[B[i + 1150*t]] + R[C[i + 1150*t]];
R[i + 2064*t] = Op[i + 1151*t] ? R[B[i + 1151*t]] * R[C[i + 1151*t]] : R[B[i + 1151*t]] + R[C[i + 1151*t]];
R[i + 2065*t] = Op[i + 1152*t] ? R[B[i + 1152*t]] * R[C[i + 1152*t]] : R[B[i + 1152*t]] + R[C[i + 1152*t]];
R[i + 2066*t] = Op[i + 1153*t] ? R[B[i + 1153*t]] * R[C[i + 1153*t]] : R[B[i + 1153*t]] + R[C[i + 1153*t]];
R[i + 2067*t] = Op[i + 1154*t] ? R[B[i + 1154*t]] * R[C[i + 1154*t]] : R[B[i + 1154*t]] + R[C[i + 1154*t]];
R[i + 2068*t] = Op[i + 1155*t] ? R[B[i + 1155*t]] * R[C[i + 1155*t]] : R[B[i + 1155*t]] + R[C[i + 1155*t]];
R[i + 2069*t] = Op[i + 1156*t] ? R[B[i + 1156*t]] * R[C[i + 1156*t]] : R[B[i + 1156*t]] + R[C[i + 1156*t]];
R[i + 2070*t] = Op[i + 1157*t] ? R[B[i + 1157*t]] * R[C[i + 1157*t]] : R[B[i + 1157*t]] + R[C[i + 1157*t]];
R[i + 2071*t] = Op[i + 1158*t] ? R[B[i + 1158*t]] * R[C[i + 1158*t]] : R[B[i + 1158*t]] + R[C[i + 1158*t]];
R[i + 2072*t] = Op[i + 1159*t] ? R[B[i + 1159*t]] * R[C[i + 1159*t]] : R[B[i + 1159*t]] + R[C[i + 1159*t]];
R[i + 2073*t] = Op[i + 1160*t] ? R[B[i + 1160*t]] * R[C[i + 1160*t]] : R[B[i + 1160*t]] + R[C[i + 1160*t]];
R[i + 2074*t] = Op[i + 1161*t] ? R[B[i + 1161*t]] * R[C[i + 1161*t]] : R[B[i + 1161*t]] + R[C[i + 1161*t]];
R[i + 2075*t] = Op[i + 1162*t] ? R[B[i + 1162*t]] * R[C[i + 1162*t]] : R[B[i + 1162*t]] + R[C[i + 1162*t]];
R[i + 2076*t] = Op[i + 1163*t] ? R[B[i + 1163*t]] * R[C[i + 1163*t]] : R[B[i + 1163*t]] + R[C[i + 1163*t]];
R[i + 2077*t] = Op[i + 1164*t] ? R[B[i + 1164*t]] * R[C[i + 1164*t]] : R[B[i + 1164*t]] + R[C[i + 1164*t]];
R[i + 2078*t] = Op[i + 1165*t] ? R[B[i + 1165*t]] * R[C[i + 1165*t]] : R[B[i + 1165*t]] + R[C[i + 1165*t]];
R[i + 2079*t] = Op[i + 1166*t] ? R[B[i + 1166*t]] * R[C[i + 1166*t]] : R[B[i + 1166*t]] + R[C[i + 1166*t]];
R[i + 2080*t] = Op[i + 1167*t] ? R[B[i + 1167*t]] * R[C[i + 1167*t]] : R[B[i + 1167*t]] + R[C[i + 1167*t]];
R[i + 2081*t] = Op[i + 1168*t] ? R[B[i + 1168*t]] * R[C[i + 1168*t]] : R[B[i + 1168*t]] + R[C[i + 1168*t]];
R[i + 2082*t] = Op[i + 1169*t] ? R[B[i + 1169*t]] * R[C[i + 1169*t]] : R[B[i + 1169*t]] + R[C[i + 1169*t]];
R[i + 2083*t] = Op[i + 1170*t] ? R[B[i + 1170*t]] * R[C[i + 1170*t]] : R[B[i + 1170*t]] + R[C[i + 1170*t]];
R[i + 2084*t] = Op[i + 1171*t] ? R[B[i + 1171*t]] * R[C[i + 1171*t]] : R[B[i + 1171*t]] + R[C[i + 1171*t]];
R[i + 2085*t] = Op[i + 1172*t] ? R[B[i + 1172*t]] * R[C[i + 1172*t]] : R[B[i + 1172*t]] + R[C[i + 1172*t]];
__syncthreads();
R[i + 2086*t] = Op[i + 1173*t] ? R[B[i + 1173*t]] * R[C[i + 1173*t]] : R[B[i + 1173*t]] + R[C[i + 1173*t]];
R[i + 2087*t] = Op[i + 1174*t] ? R[B[i + 1174*t]] * R[C[i + 1174*t]] : R[B[i + 1174*t]] + R[C[i + 1174*t]];
R[i + 2088*t] = Op[i + 1175*t] ? R[B[i + 1175*t]] * R[C[i + 1175*t]] : R[B[i + 1175*t]] + R[C[i + 1175*t]];
R[i + 2089*t] = Op[i + 1176*t] ? R[B[i + 1176*t]] * R[C[i + 1176*t]] : R[B[i + 1176*t]] + R[C[i + 1176*t]];
R[i + 2090*t] = Op[i + 1177*t] ? R[B[i + 1177*t]] * R[C[i + 1177*t]] : R[B[i + 1177*t]] + R[C[i + 1177*t]];
R[i + 2091*t] = Op[i + 1178*t] ? R[B[i + 1178*t]] * R[C[i + 1178*t]] : R[B[i + 1178*t]] + R[C[i + 1178*t]];
R[i + 2092*t] = Op[i + 1179*t] ? R[B[i + 1179*t]] * R[C[i + 1179*t]] : R[B[i + 1179*t]] + R[C[i + 1179*t]];
R[i + 2093*t] = Op[i + 1180*t] ? R[B[i + 1180*t]] * R[C[i + 1180*t]] : R[B[i + 1180*t]] + R[C[i + 1180*t]];
R[i + 2094*t] = Op[i + 1181*t] ? R[B[i + 1181*t]] * R[C[i + 1181*t]] : R[B[i + 1181*t]] + R[C[i + 1181*t]];
R[i + 2095*t] = Op[i + 1182*t] ? R[B[i + 1182*t]] * R[C[i + 1182*t]] : R[B[i + 1182*t]] + R[C[i + 1182*t]];
R[i + 2096*t] = Op[i + 1183*t] ? R[B[i + 1183*t]] * R[C[i + 1183*t]] : R[B[i + 1183*t]] + R[C[i + 1183*t]];
R[i + 2097*t] = Op[i + 1184*t] ? R[B[i + 1184*t]] * R[C[i + 1184*t]] : R[B[i + 1184*t]] + R[C[i + 1184*t]];
R[i + 2098*t] = Op[i + 1185*t] ? R[B[i + 1185*t]] * R[C[i + 1185*t]] : R[B[i + 1185*t]] + R[C[i + 1185*t]];
R[i + 2099*t] = Op[i + 1186*t] ? R[B[i + 1186*t]] * R[C[i + 1186*t]] : R[B[i + 1186*t]] + R[C[i + 1186*t]];
R[i + 2100*t] = Op[i + 1187*t] ? R[B[i + 1187*t]] * R[C[i + 1187*t]] : R[B[i + 1187*t]] + R[C[i + 1187*t]];
R[i + 2101*t] = Op[i + 1188*t] ? R[B[i + 1188*t]] * R[C[i + 1188*t]] : R[B[i + 1188*t]] + R[C[i + 1188*t]];
R[i + 2102*t] = Op[i + 1189*t] ? R[B[i + 1189*t]] * R[C[i + 1189*t]] : R[B[i + 1189*t]] + R[C[i + 1189*t]];
R[i + 2103*t] = Op[i + 1190*t] ? R[B[i + 1190*t]] * R[C[i + 1190*t]] : R[B[i + 1190*t]] + R[C[i + 1190*t]];
R[i + 2104*t] = Op[i + 1191*t] ? R[B[i + 1191*t]] * R[C[i + 1191*t]] : R[B[i + 1191*t]] + R[C[i + 1191*t]];
R[i + 2105*t] = Op[i + 1192*t] ? R[B[i + 1192*t]] * R[C[i + 1192*t]] : R[B[i + 1192*t]] + R[C[i + 1192*t]];
R[i + 2106*t] = Op[i + 1193*t] ? R[B[i + 1193*t]] * R[C[i + 1193*t]] : R[B[i + 1193*t]] + R[C[i + 1193*t]];
R[i + 2107*t] = Op[i + 1194*t] ? R[B[i + 1194*t]] * R[C[i + 1194*t]] : R[B[i + 1194*t]] + R[C[i + 1194*t]];
R[i + 2108*t] = Op[i + 1195*t] ? R[B[i + 1195*t]] * R[C[i + 1195*t]] : R[B[i + 1195*t]] + R[C[i + 1195*t]];
R[i + 2109*t] = Op[i + 1196*t] ? R[B[i + 1196*t]] * R[C[i + 1196*t]] : R[B[i + 1196*t]] + R[C[i + 1196*t]];
R[i + 2110*t] = Op[i + 1197*t] ? R[B[i + 1197*t]] * R[C[i + 1197*t]] : R[B[i + 1197*t]] + R[C[i + 1197*t]];
R[i + 2111*t] = Op[i + 1198*t] ? R[B[i + 1198*t]] * R[C[i + 1198*t]] : R[B[i + 1198*t]] + R[C[i + 1198*t]];
R[i + 2112*t] = Op[i + 1199*t] ? R[B[i + 1199*t]] * R[C[i + 1199*t]] : R[B[i + 1199*t]] + R[C[i + 1199*t]];
R[i + 2113*t] = Op[i + 1200*t] ? R[B[i + 1200*t]] * R[C[i + 1200*t]] : R[B[i + 1200*t]] + R[C[i + 1200*t]];
R[i + 2114*t] = Op[i + 1201*t] ? R[B[i + 1201*t]] * R[C[i + 1201*t]] : R[B[i + 1201*t]] + R[C[i + 1201*t]];
R[i + 2115*t] = Op[i + 1202*t] ? R[B[i + 1202*t]] * R[C[i + 1202*t]] : R[B[i + 1202*t]] + R[C[i + 1202*t]];
R[i + 2116*t] = Op[i + 1203*t] ? R[B[i + 1203*t]] * R[C[i + 1203*t]] : R[B[i + 1203*t]] + R[C[i + 1203*t]];
R[i + 2117*t] = Op[i + 1204*t] ? R[B[i + 1204*t]] * R[C[i + 1204*t]] : R[B[i + 1204*t]] + R[C[i + 1204*t]];
R[i + 2118*t] = Op[i + 1205*t] ? R[B[i + 1205*t]] * R[C[i + 1205*t]] : R[B[i + 1205*t]] + R[C[i + 1205*t]];
R[i + 2119*t] = Op[i + 1206*t] ? R[B[i + 1206*t]] * R[C[i + 1206*t]] : R[B[i + 1206*t]] + R[C[i + 1206*t]];
R[i + 2120*t] = Op[i + 1207*t] ? R[B[i + 1207*t]] * R[C[i + 1207*t]] : R[B[i + 1207*t]] + R[C[i + 1207*t]];
R[i + 2121*t] = Op[i + 1208*t] ? R[B[i + 1208*t]] * R[C[i + 1208*t]] : R[B[i + 1208*t]] + R[C[i + 1208*t]];
R[i + 2122*t] = Op[i + 1209*t] ? R[B[i + 1209*t]] * R[C[i + 1209*t]] : R[B[i + 1209*t]] + R[C[i + 1209*t]];
R[i + 2123*t] = Op[i + 1210*t] ? R[B[i + 1210*t]] * R[C[i + 1210*t]] : R[B[i + 1210*t]] + R[C[i + 1210*t]];
R[i + 2124*t] = Op[i + 1211*t] ? R[B[i + 1211*t]] * R[C[i + 1211*t]] : R[B[i + 1211*t]] + R[C[i + 1211*t]];
R[i + 2125*t] = Op[i + 1212*t] ? R[B[i + 1212*t]] * R[C[i + 1212*t]] : R[B[i + 1212*t]] + R[C[i + 1212*t]];
R[i + 2126*t] = Op[i + 1213*t] ? R[B[i + 1213*t]] * R[C[i + 1213*t]] : R[B[i + 1213*t]] + R[C[i + 1213*t]];
__syncthreads();
R[i + 2127*t] = Op[i + 1214*t] ? R[B[i + 1214*t]] * R[C[i + 1214*t]] : R[B[i + 1214*t]] + R[C[i + 1214*t]];
R[i + 2128*t] = Op[i + 1215*t] ? R[B[i + 1215*t]] * R[C[i + 1215*t]] : R[B[i + 1215*t]] + R[C[i + 1215*t]];
R[i + 2129*t] = Op[i + 1216*t] ? R[B[i + 1216*t]] * R[C[i + 1216*t]] : R[B[i + 1216*t]] + R[C[i + 1216*t]];
R[i + 2130*t] = Op[i + 1217*t] ? R[B[i + 1217*t]] * R[C[i + 1217*t]] : R[B[i + 1217*t]] + R[C[i + 1217*t]];
R[i + 2131*t] = Op[i + 1218*t] ? R[B[i + 1218*t]] * R[C[i + 1218*t]] : R[B[i + 1218*t]] + R[C[i + 1218*t]];
R[i + 2132*t] = Op[i + 1219*t] ? R[B[i + 1219*t]] * R[C[i + 1219*t]] : R[B[i + 1219*t]] + R[C[i + 1219*t]];
R[i + 2133*t] = Op[i + 1220*t] ? R[B[i + 1220*t]] * R[C[i + 1220*t]] : R[B[i + 1220*t]] + R[C[i + 1220*t]];
R[i + 2134*t] = Op[i + 1221*t] ? R[B[i + 1221*t]] * R[C[i + 1221*t]] : R[B[i + 1221*t]] + R[C[i + 1221*t]];
R[i + 2135*t] = Op[i + 1222*t] ? R[B[i + 1222*t]] * R[C[i + 1222*t]] : R[B[i + 1222*t]] + R[C[i + 1222*t]];
R[i + 2136*t] = Op[i + 1223*t] ? R[B[i + 1223*t]] * R[C[i + 1223*t]] : R[B[i + 1223*t]] + R[C[i + 1223*t]];
R[i + 2137*t] = Op[i + 1224*t] ? R[B[i + 1224*t]] * R[C[i + 1224*t]] : R[B[i + 1224*t]] + R[C[i + 1224*t]];
R[i + 2138*t] = Op[i + 1225*t] ? R[B[i + 1225*t]] * R[C[i + 1225*t]] : R[B[i + 1225*t]] + R[C[i + 1225*t]];
R[i + 2139*t] = Op[i + 1226*t] ? R[B[i + 1226*t]] * R[C[i + 1226*t]] : R[B[i + 1226*t]] + R[C[i + 1226*t]];
R[i + 2140*t] = Op[i + 1227*t] ? R[B[i + 1227*t]] * R[C[i + 1227*t]] : R[B[i + 1227*t]] + R[C[i + 1227*t]];
R[i + 2141*t] = Op[i + 1228*t] ? R[B[i + 1228*t]] * R[C[i + 1228*t]] : R[B[i + 1228*t]] + R[C[i + 1228*t]];
R[i + 2142*t] = Op[i + 1229*t] ? R[B[i + 1229*t]] * R[C[i + 1229*t]] : R[B[i + 1229*t]] + R[C[i + 1229*t]];
R[i + 2143*t] = Op[i + 1230*t] ? R[B[i + 1230*t]] * R[C[i + 1230*t]] : R[B[i + 1230*t]] + R[C[i + 1230*t]];
R[i + 2144*t] = Op[i + 1231*t] ? R[B[i + 1231*t]] * R[C[i + 1231*t]] : R[B[i + 1231*t]] + R[C[i + 1231*t]];
R[i + 2145*t] = Op[i + 1232*t] ? R[B[i + 1232*t]] * R[C[i + 1232*t]] : R[B[i + 1232*t]] + R[C[i + 1232*t]];
R[i + 2146*t] = Op[i + 1233*t] ? R[B[i + 1233*t]] * R[C[i + 1233*t]] : R[B[i + 1233*t]] + R[C[i + 1233*t]];
R[i + 2147*t] = Op[i + 1234*t] ? R[B[i + 1234*t]] * R[C[i + 1234*t]] : R[B[i + 1234*t]] + R[C[i + 1234*t]];
R[i + 2148*t] = Op[i + 1235*t] ? R[B[i + 1235*t]] * R[C[i + 1235*t]] : R[B[i + 1235*t]] + R[C[i + 1235*t]];
R[i + 2149*t] = Op[i + 1236*t] ? R[B[i + 1236*t]] * R[C[i + 1236*t]] : R[B[i + 1236*t]] + R[C[i + 1236*t]];
R[i + 2150*t] = Op[i + 1237*t] ? R[B[i + 1237*t]] * R[C[i + 1237*t]] : R[B[i + 1237*t]] + R[C[i + 1237*t]];
R[i + 2151*t] = Op[i + 1238*t] ? R[B[i + 1238*t]] * R[C[i + 1238*t]] : R[B[i + 1238*t]] + R[C[i + 1238*t]];
R[i + 2152*t] = Op[i + 1239*t] ? R[B[i + 1239*t]] * R[C[i + 1239*t]] : R[B[i + 1239*t]] + R[C[i + 1239*t]];
R[i + 2153*t] = Op[i + 1240*t] ? R[B[i + 1240*t]] * R[C[i + 1240*t]] : R[B[i + 1240*t]] + R[C[i + 1240*t]];
R[i + 2154*t] = Op[i + 1241*t] ? R[B[i + 1241*t]] * R[C[i + 1241*t]] : R[B[i + 1241*t]] + R[C[i + 1241*t]];
R[i + 2155*t] = Op[i + 1242*t] ? R[B[i + 1242*t]] * R[C[i + 1242*t]] : R[B[i + 1242*t]] + R[C[i + 1242*t]];
R[i + 2156*t] = Op[i + 1243*t] ? R[B[i + 1243*t]] * R[C[i + 1243*t]] : R[B[i + 1243*t]] + R[C[i + 1243*t]];
R[i + 2157*t] = Op[i + 1244*t] ? R[B[i + 1244*t]] * R[C[i + 1244*t]] : R[B[i + 1244*t]] + R[C[i + 1244*t]];
R[i + 2158*t] = Op[i + 1245*t] ? R[B[i + 1245*t]] * R[C[i + 1245*t]] : R[B[i + 1245*t]] + R[C[i + 1245*t]];
R[i + 2159*t] = Op[i + 1246*t] ? R[B[i + 1246*t]] * R[C[i + 1246*t]] : R[B[i + 1246*t]] + R[C[i + 1246*t]];
R[i + 2160*t] = Op[i + 1247*t] ? R[B[i + 1247*t]] * R[C[i + 1247*t]] : R[B[i + 1247*t]] + R[C[i + 1247*t]];
R[i + 2161*t] = Op[i + 1248*t] ? R[B[i + 1248*t]] * R[C[i + 1248*t]] : R[B[i + 1248*t]] + R[C[i + 1248*t]];
R[i + 2162*t] = Op[i + 1249*t] ? R[B[i + 1249*t]] * R[C[i + 1249*t]] : R[B[i + 1249*t]] + R[C[i + 1249*t]];
R[i + 2163*t] = Op[i + 1250*t] ? R[B[i + 1250*t]] * R[C[i + 1250*t]] : R[B[i + 1250*t]] + R[C[i + 1250*t]];
R[i + 2164*t] = Op[i + 1251*t] ? R[B[i + 1251*t]] * R[C[i + 1251*t]] : R[B[i + 1251*t]] + R[C[i + 1251*t]];
R[i + 2165*t] = Op[i + 1252*t] ? R[B[i + 1252*t]] * R[C[i + 1252*t]] : R[B[i + 1252*t]] + R[C[i + 1252*t]];
R[i + 2166*t] = Op[i + 1253*t] ? R[B[i + 1253*t]] * R[C[i + 1253*t]] : R[B[i + 1253*t]] + R[C[i + 1253*t]];
R[i + 2167*t] = Op[i + 1254*t] ? R[B[i + 1254*t]] * R[C[i + 1254*t]] : R[B[i + 1254*t]] + R[C[i + 1254*t]];
R[i + 2168*t] = Op[i + 1255*t] ? R[B[i + 1255*t]] * R[C[i + 1255*t]] : R[B[i + 1255*t]] + R[C[i + 1255*t]];
R[i + 2169*t] = Op[i + 1256*t] ? R[B[i + 1256*t]] * R[C[i + 1256*t]] : R[B[i + 1256*t]] + R[C[i + 1256*t]];
R[i + 2170*t] = Op[i + 1257*t] ? R[B[i + 1257*t]] * R[C[i + 1257*t]] : R[B[i + 1257*t]] + R[C[i + 1257*t]];
R[i + 2171*t] = Op[i + 1258*t] ? R[B[i + 1258*t]] * R[C[i + 1258*t]] : R[B[i + 1258*t]] + R[C[i + 1258*t]];
R[i + 2172*t] = Op[i + 1259*t] ? R[B[i + 1259*t]] * R[C[i + 1259*t]] : R[B[i + 1259*t]] + R[C[i + 1259*t]];
R[i + 2173*t] = Op[i + 1260*t] ? R[B[i + 1260*t]] * R[C[i + 1260*t]] : R[B[i + 1260*t]] + R[C[i + 1260*t]];
R[i + 2174*t] = Op[i + 1261*t] ? R[B[i + 1261*t]] * R[C[i + 1261*t]] : R[B[i + 1261*t]] + R[C[i + 1261*t]];
R[i + 2175*t] = Op[i + 1262*t] ? R[B[i + 1262*t]] * R[C[i + 1262*t]] : R[B[i + 1262*t]] + R[C[i + 1262*t]];
R[i + 2176*t] = Op[i + 1263*t] ? R[B[i + 1263*t]] * R[C[i + 1263*t]] : R[B[i + 1263*t]] + R[C[i + 1263*t]];
R[i + 2177*t] = Op[i + 1264*t] ? R[B[i + 1264*t]] * R[C[i + 1264*t]] : R[B[i + 1264*t]] + R[C[i + 1264*t]];
R[i + 2178*t] = Op[i + 1265*t] ? R[B[i + 1265*t]] * R[C[i + 1265*t]] : R[B[i + 1265*t]] + R[C[i + 1265*t]];
R[i + 2179*t] = Op[i + 1266*t] ? R[B[i + 1266*t]] * R[C[i + 1266*t]] : R[B[i + 1266*t]] + R[C[i + 1266*t]];
R[i + 2180*t] = Op[i + 1267*t] ? R[B[i + 1267*t]] * R[C[i + 1267*t]] : R[B[i + 1267*t]] + R[C[i + 1267*t]];
R[i + 2181*t] = Op[i + 1268*t] ? R[B[i + 1268*t]] * R[C[i + 1268*t]] : R[B[i + 1268*t]] + R[C[i + 1268*t]];
R[i + 2182*t] = Op[i + 1269*t] ? R[B[i + 1269*t]] * R[C[i + 1269*t]] : R[B[i + 1269*t]] + R[C[i + 1269*t]];
__syncthreads();
R[i + 2183*t] = Op[i + 1270*t] ? R[B[i + 1270*t]] * R[C[i + 1270*t]] : R[B[i + 1270*t]] + R[C[i + 1270*t]];
R[i + 2184*t] = Op[i + 1271*t] ? R[B[i + 1271*t]] * R[C[i + 1271*t]] : R[B[i + 1271*t]] + R[C[i + 1271*t]];
R[i + 2185*t] = Op[i + 1272*t] ? R[B[i + 1272*t]] * R[C[i + 1272*t]] : R[B[i + 1272*t]] + R[C[i + 1272*t]];
R[i + 2186*t] = Op[i + 1273*t] ? R[B[i + 1273*t]] * R[C[i + 1273*t]] : R[B[i + 1273*t]] + R[C[i + 1273*t]];
R[i + 2187*t] = Op[i + 1274*t] ? R[B[i + 1274*t]] * R[C[i + 1274*t]] : R[B[i + 1274*t]] + R[C[i + 1274*t]];
R[i + 2188*t] = Op[i + 1275*t] ? R[B[i + 1275*t]] * R[C[i + 1275*t]] : R[B[i + 1275*t]] + R[C[i + 1275*t]];
R[i + 2189*t] = Op[i + 1276*t] ? R[B[i + 1276*t]] * R[C[i + 1276*t]] : R[B[i + 1276*t]] + R[C[i + 1276*t]];
R[i + 2190*t] = Op[i + 1277*t] ? R[B[i + 1277*t]] * R[C[i + 1277*t]] : R[B[i + 1277*t]] + R[C[i + 1277*t]];
R[i + 2191*t] = Op[i + 1278*t] ? R[B[i + 1278*t]] * R[C[i + 1278*t]] : R[B[i + 1278*t]] + R[C[i + 1278*t]];
R[i + 2192*t] = Op[i + 1279*t] ? R[B[i + 1279*t]] * R[C[i + 1279*t]] : R[B[i + 1279*t]] + R[C[i + 1279*t]];
R[i + 2193*t] = Op[i + 1280*t] ? R[B[i + 1280*t]] * R[C[i + 1280*t]] : R[B[i + 1280*t]] + R[C[i + 1280*t]];
R[i + 2194*t] = Op[i + 1281*t] ? R[B[i + 1281*t]] * R[C[i + 1281*t]] : R[B[i + 1281*t]] + R[C[i + 1281*t]];
R[i + 2195*t] = Op[i + 1282*t] ? R[B[i + 1282*t]] * R[C[i + 1282*t]] : R[B[i + 1282*t]] + R[C[i + 1282*t]];
R[i + 2196*t] = Op[i + 1283*t] ? R[B[i + 1283*t]] * R[C[i + 1283*t]] : R[B[i + 1283*t]] + R[C[i + 1283*t]];
R[i + 2197*t] = Op[i + 1284*t] ? R[B[i + 1284*t]] * R[C[i + 1284*t]] : R[B[i + 1284*t]] + R[C[i + 1284*t]];
R[i + 2198*t] = Op[i + 1285*t] ? R[B[i + 1285*t]] * R[C[i + 1285*t]] : R[B[i + 1285*t]] + R[C[i + 1285*t]];
R[i + 2199*t] = Op[i + 1286*t] ? R[B[i + 1286*t]] * R[C[i + 1286*t]] : R[B[i + 1286*t]] + R[C[i + 1286*t]];
R[i + 2200*t] = Op[i + 1287*t] ? R[B[i + 1287*t]] * R[C[i + 1287*t]] : R[B[i + 1287*t]] + R[C[i + 1287*t]];
R[i + 2201*t] = Op[i + 1288*t] ? R[B[i + 1288*t]] * R[C[i + 1288*t]] : R[B[i + 1288*t]] + R[C[i + 1288*t]];
R[i + 2202*t] = Op[i + 1289*t] ? R[B[i + 1289*t]] * R[C[i + 1289*t]] : R[B[i + 1289*t]] + R[C[i + 1289*t]];
R[i + 2203*t] = Op[i + 1290*t] ? R[B[i + 1290*t]] * R[C[i + 1290*t]] : R[B[i + 1290*t]] + R[C[i + 1290*t]];
R[i + 2204*t] = Op[i + 1291*t] ? R[B[i + 1291*t]] * R[C[i + 1291*t]] : R[B[i + 1291*t]] + R[C[i + 1291*t]];
R[i + 2205*t] = Op[i + 1292*t] ? R[B[i + 1292*t]] * R[C[i + 1292*t]] : R[B[i + 1292*t]] + R[C[i + 1292*t]];
R[i + 2206*t] = Op[i + 1293*t] ? R[B[i + 1293*t]] * R[C[i + 1293*t]] : R[B[i + 1293*t]] + R[C[i + 1293*t]];
R[i + 2207*t] = Op[i + 1294*t] ? R[B[i + 1294*t]] * R[C[i + 1294*t]] : R[B[i + 1294*t]] + R[C[i + 1294*t]];
R[i + 2208*t] = Op[i + 1295*t] ? R[B[i + 1295*t]] * R[C[i + 1295*t]] : R[B[i + 1295*t]] + R[C[i + 1295*t]];
R[i + 2209*t] = Op[i + 1296*t] ? R[B[i + 1296*t]] * R[C[i + 1296*t]] : R[B[i + 1296*t]] + R[C[i + 1296*t]];
R[i + 2210*t] = Op[i + 1297*t] ? R[B[i + 1297*t]] * R[C[i + 1297*t]] : R[B[i + 1297*t]] + R[C[i + 1297*t]];
R[i + 2211*t] = Op[i + 1298*t] ? R[B[i + 1298*t]] * R[C[i + 1298*t]] : R[B[i + 1298*t]] + R[C[i + 1298*t]];
R[i + 2212*t] = Op[i + 1299*t] ? R[B[i + 1299*t]] * R[C[i + 1299*t]] : R[B[i + 1299*t]] + R[C[i + 1299*t]];
R[i + 2213*t] = Op[i + 1300*t] ? R[B[i + 1300*t]] * R[C[i + 1300*t]] : R[B[i + 1300*t]] + R[C[i + 1300*t]];
R[i + 2214*t] = Op[i + 1301*t] ? R[B[i + 1301*t]] * R[C[i + 1301*t]] : R[B[i + 1301*t]] + R[C[i + 1301*t]];
R[i + 2215*t] = Op[i + 1302*t] ? R[B[i + 1302*t]] * R[C[i + 1302*t]] : R[B[i + 1302*t]] + R[C[i + 1302*t]];
R[i + 2216*t] = Op[i + 1303*t] ? R[B[i + 1303*t]] * R[C[i + 1303*t]] : R[B[i + 1303*t]] + R[C[i + 1303*t]];
R[i + 2217*t] = Op[i + 1304*t] ? R[B[i + 1304*t]] * R[C[i + 1304*t]] : R[B[i + 1304*t]] + R[C[i + 1304*t]];
R[i + 2218*t] = Op[i + 1305*t] ? R[B[i + 1305*t]] * R[C[i + 1305*t]] : R[B[i + 1305*t]] + R[C[i + 1305*t]];
R[i + 2219*t] = Op[i + 1306*t] ? R[B[i + 1306*t]] * R[C[i + 1306*t]] : R[B[i + 1306*t]] + R[C[i + 1306*t]];
R[i + 2220*t] = Op[i + 1307*t] ? R[B[i + 1307*t]] * R[C[i + 1307*t]] : R[B[i + 1307*t]] + R[C[i + 1307*t]];
R[i + 2221*t] = Op[i + 1308*t] ? R[B[i + 1308*t]] * R[C[i + 1308*t]] : R[B[i + 1308*t]] + R[C[i + 1308*t]];
R[i + 2222*t] = Op[i + 1309*t] ? R[B[i + 1309*t]] * R[C[i + 1309*t]] : R[B[i + 1309*t]] + R[C[i + 1309*t]];
R[i + 2223*t] = Op[i + 1310*t] ? R[B[i + 1310*t]] * R[C[i + 1310*t]] : R[B[i + 1310*t]] + R[C[i + 1310*t]];
R[i + 2224*t] = Op[i + 1311*t] ? R[B[i + 1311*t]] * R[C[i + 1311*t]] : R[B[i + 1311*t]] + R[C[i + 1311*t]];
R[i + 2225*t] = Op[i + 1312*t] ? R[B[i + 1312*t]] * R[C[i + 1312*t]] : R[B[i + 1312*t]] + R[C[i + 1312*t]];
R[i + 2226*t] = Op[i + 1313*t] ? R[B[i + 1313*t]] * R[C[i + 1313*t]] : R[B[i + 1313*t]] + R[C[i + 1313*t]];
R[i + 2227*t] = Op[i + 1314*t] ? R[B[i + 1314*t]] * R[C[i + 1314*t]] : R[B[i + 1314*t]] + R[C[i + 1314*t]];
__syncthreads();
R[i + 2228*t] = Op[i + 1315*t] ? R[B[i + 1315*t]] * R[C[i + 1315*t]] : R[B[i + 1315*t]] + R[C[i + 1315*t]];
R[i + 2229*t] = Op[i + 1316*t] ? R[B[i + 1316*t]] * R[C[i + 1316*t]] : R[B[i + 1316*t]] + R[C[i + 1316*t]];
R[i + 2230*t] = Op[i + 1317*t] ? R[B[i + 1317*t]] * R[C[i + 1317*t]] : R[B[i + 1317*t]] + R[C[i + 1317*t]];
R[i + 2231*t] = Op[i + 1318*t] ? R[B[i + 1318*t]] * R[C[i + 1318*t]] : R[B[i + 1318*t]] + R[C[i + 1318*t]];
R[i + 2232*t] = Op[i + 1319*t] ? R[B[i + 1319*t]] * R[C[i + 1319*t]] : R[B[i + 1319*t]] + R[C[i + 1319*t]];
R[i + 2233*t] = Op[i + 1320*t] ? R[B[i + 1320*t]] * R[C[i + 1320*t]] : R[B[i + 1320*t]] + R[C[i + 1320*t]];
R[i + 2234*t] = Op[i + 1321*t] ? R[B[i + 1321*t]] * R[C[i + 1321*t]] : R[B[i + 1321*t]] + R[C[i + 1321*t]];
R[i + 2235*t] = Op[i + 1322*t] ? R[B[i + 1322*t]] * R[C[i + 1322*t]] : R[B[i + 1322*t]] + R[C[i + 1322*t]];
R[i + 2236*t] = Op[i + 1323*t] ? R[B[i + 1323*t]] * R[C[i + 1323*t]] : R[B[i + 1323*t]] + R[C[i + 1323*t]];
R[i + 2237*t] = Op[i + 1324*t] ? R[B[i + 1324*t]] * R[C[i + 1324*t]] : R[B[i + 1324*t]] + R[C[i + 1324*t]];
R[i + 2238*t] = Op[i + 1325*t] ? R[B[i + 1325*t]] * R[C[i + 1325*t]] : R[B[i + 1325*t]] + R[C[i + 1325*t]];
R[i + 2239*t] = Op[i + 1326*t] ? R[B[i + 1326*t]] * R[C[i + 1326*t]] : R[B[i + 1326*t]] + R[C[i + 1326*t]];
R[i + 2240*t] = Op[i + 1327*t] ? R[B[i + 1327*t]] * R[C[i + 1327*t]] : R[B[i + 1327*t]] + R[C[i + 1327*t]];
R[i + 2241*t] = Op[i + 1328*t] ? R[B[i + 1328*t]] * R[C[i + 1328*t]] : R[B[i + 1328*t]] + R[C[i + 1328*t]];
R[i + 2242*t] = Op[i + 1329*t] ? R[B[i + 1329*t]] * R[C[i + 1329*t]] : R[B[i + 1329*t]] + R[C[i + 1329*t]];
R[i + 2243*t] = Op[i + 1330*t] ? R[B[i + 1330*t]] * R[C[i + 1330*t]] : R[B[i + 1330*t]] + R[C[i + 1330*t]];
R[i + 2244*t] = Op[i + 1331*t] ? R[B[i + 1331*t]] * R[C[i + 1331*t]] : R[B[i + 1331*t]] + R[C[i + 1331*t]];
R[i + 2245*t] = Op[i + 1332*t] ? R[B[i + 1332*t]] * R[C[i + 1332*t]] : R[B[i + 1332*t]] + R[C[i + 1332*t]];
R[i + 2246*t] = Op[i + 1333*t] ? R[B[i + 1333*t]] * R[C[i + 1333*t]] : R[B[i + 1333*t]] + R[C[i + 1333*t]];
R[i + 2247*t] = Op[i + 1334*t] ? R[B[i + 1334*t]] * R[C[i + 1334*t]] : R[B[i + 1334*t]] + R[C[i + 1334*t]];
R[i + 2248*t] = Op[i + 1335*t] ? R[B[i + 1335*t]] * R[C[i + 1335*t]] : R[B[i + 1335*t]] + R[C[i + 1335*t]];
R[i + 2249*t] = Op[i + 1336*t] ? R[B[i + 1336*t]] * R[C[i + 1336*t]] : R[B[i + 1336*t]] + R[C[i + 1336*t]];
R[i + 2250*t] = Op[i + 1337*t] ? R[B[i + 1337*t]] * R[C[i + 1337*t]] : R[B[i + 1337*t]] + R[C[i + 1337*t]];
R[i + 2251*t] = Op[i + 1338*t] ? R[B[i + 1338*t]] * R[C[i + 1338*t]] : R[B[i + 1338*t]] + R[C[i + 1338*t]];
R[i + 2252*t] = Op[i + 1339*t] ? R[B[i + 1339*t]] * R[C[i + 1339*t]] : R[B[i + 1339*t]] + R[C[i + 1339*t]];
R[i + 2253*t] = Op[i + 1340*t] ? R[B[i + 1340*t]] * R[C[i + 1340*t]] : R[B[i + 1340*t]] + R[C[i + 1340*t]];
__syncthreads();
R[i + 2254*t] = Op[i + 1341*t] ? R[B[i + 1341*t]] * R[C[i + 1341*t]] : R[B[i + 1341*t]] + R[C[i + 1341*t]];
R[i + 2255*t] = Op[i + 1342*t] ? R[B[i + 1342*t]] * R[C[i + 1342*t]] : R[B[i + 1342*t]] + R[C[i + 1342*t]];
R[i + 2256*t] = Op[i + 1343*t] ? R[B[i + 1343*t]] * R[C[i + 1343*t]] : R[B[i + 1343*t]] + R[C[i + 1343*t]];
R[i + 2257*t] = Op[i + 1344*t] ? R[B[i + 1344*t]] * R[C[i + 1344*t]] : R[B[i + 1344*t]] + R[C[i + 1344*t]];
R[i + 2258*t] = Op[i + 1345*t] ? R[B[i + 1345*t]] * R[C[i + 1345*t]] : R[B[i + 1345*t]] + R[C[i + 1345*t]];
R[i + 2259*t] = Op[i + 1346*t] ? R[B[i + 1346*t]] * R[C[i + 1346*t]] : R[B[i + 1346*t]] + R[C[i + 1346*t]];
R[i + 2260*t] = Op[i + 1347*t] ? R[B[i + 1347*t]] * R[C[i + 1347*t]] : R[B[i + 1347*t]] + R[C[i + 1347*t]];
R[i + 2261*t] = Op[i + 1348*t] ? R[B[i + 1348*t]] * R[C[i + 1348*t]] : R[B[i + 1348*t]] + R[C[i + 1348*t]];
R[i + 2262*t] = Op[i + 1349*t] ? R[B[i + 1349*t]] * R[C[i + 1349*t]] : R[B[i + 1349*t]] + R[C[i + 1349*t]];
R[i + 2263*t] = Op[i + 1350*t] ? R[B[i + 1350*t]] * R[C[i + 1350*t]] : R[B[i + 1350*t]] + R[C[i + 1350*t]];
R[i + 2264*t] = Op[i + 1351*t] ? R[B[i + 1351*t]] * R[C[i + 1351*t]] : R[B[i + 1351*t]] + R[C[i + 1351*t]];
R[i + 2265*t] = Op[i + 1352*t] ? R[B[i + 1352*t]] * R[C[i + 1352*t]] : R[B[i + 1352*t]] + R[C[i + 1352*t]];
R[i + 2266*t] = Op[i + 1353*t] ? R[B[i + 1353*t]] * R[C[i + 1353*t]] : R[B[i + 1353*t]] + R[C[i + 1353*t]];
R[i + 2267*t] = Op[i + 1354*t] ? R[B[i + 1354*t]] * R[C[i + 1354*t]] : R[B[i + 1354*t]] + R[C[i + 1354*t]];
R[i + 2268*t] = Op[i + 1355*t] ? R[B[i + 1355*t]] * R[C[i + 1355*t]] : R[B[i + 1355*t]] + R[C[i + 1355*t]];
R[i + 2269*t] = Op[i + 1356*t] ? R[B[i + 1356*t]] * R[C[i + 1356*t]] : R[B[i + 1356*t]] + R[C[i + 1356*t]];
R[i + 2270*t] = Op[i + 1357*t] ? R[B[i + 1357*t]] * R[C[i + 1357*t]] : R[B[i + 1357*t]] + R[C[i + 1357*t]];
R[i + 2271*t] = Op[i + 1358*t] ? R[B[i + 1358*t]] * R[C[i + 1358*t]] : R[B[i + 1358*t]] + R[C[i + 1358*t]];
R[i + 2272*t] = Op[i + 1359*t] ? R[B[i + 1359*t]] * R[C[i + 1359*t]] : R[B[i + 1359*t]] + R[C[i + 1359*t]];
R[i + 2273*t] = Op[i + 1360*t] ? R[B[i + 1360*t]] * R[C[i + 1360*t]] : R[B[i + 1360*t]] + R[C[i + 1360*t]];
R[i + 2274*t] = Op[i + 1361*t] ? R[B[i + 1361*t]] * R[C[i + 1361*t]] : R[B[i + 1361*t]] + R[C[i + 1361*t]];
R[i + 2275*t] = Op[i + 1362*t] ? R[B[i + 1362*t]] * R[C[i + 1362*t]] : R[B[i + 1362*t]] + R[C[i + 1362*t]];
R[i + 2276*t] = Op[i + 1363*t] ? R[B[i + 1363*t]] * R[C[i + 1363*t]] : R[B[i + 1363*t]] + R[C[i + 1363*t]];
R[i + 2277*t] = Op[i + 1364*t] ? R[B[i + 1364*t]] * R[C[i + 1364*t]] : R[B[i + 1364*t]] + R[C[i + 1364*t]];
R[i + 2278*t] = Op[i + 1365*t] ? R[B[i + 1365*t]] * R[C[i + 1365*t]] : R[B[i + 1365*t]] + R[C[i + 1365*t]];
__syncthreads();
R[i + 2279*t] = Op[i + 1366*t] ? R[B[i + 1366*t]] * R[C[i + 1366*t]] : R[B[i + 1366*t]] + R[C[i + 1366*t]];
R[i + 2280*t] = Op[i + 1367*t] ? R[B[i + 1367*t]] * R[C[i + 1367*t]] : R[B[i + 1367*t]] + R[C[i + 1367*t]];
R[i + 2281*t] = Op[i + 1368*t] ? R[B[i + 1368*t]] * R[C[i + 1368*t]] : R[B[i + 1368*t]] + R[C[i + 1368*t]];
R[i + 2282*t] = Op[i + 1369*t] ? R[B[i + 1369*t]] * R[C[i + 1369*t]] : R[B[i + 1369*t]] + R[C[i + 1369*t]];
R[i + 2283*t] = Op[i + 1370*t] ? R[B[i + 1370*t]] * R[C[i + 1370*t]] : R[B[i + 1370*t]] + R[C[i + 1370*t]];
R[i + 2284*t] = Op[i + 1371*t] ? R[B[i + 1371*t]] * R[C[i + 1371*t]] : R[B[i + 1371*t]] + R[C[i + 1371*t]];
R[i + 2285*t] = Op[i + 1372*t] ? R[B[i + 1372*t]] * R[C[i + 1372*t]] : R[B[i + 1372*t]] + R[C[i + 1372*t]];
R[i + 2286*t] = Op[i + 1373*t] ? R[B[i + 1373*t]] * R[C[i + 1373*t]] : R[B[i + 1373*t]] + R[C[i + 1373*t]];
R[i + 2287*t] = Op[i + 1374*t] ? R[B[i + 1374*t]] * R[C[i + 1374*t]] : R[B[i + 1374*t]] + R[C[i + 1374*t]];
R[i + 2288*t] = Op[i + 1375*t] ? R[B[i + 1375*t]] * R[C[i + 1375*t]] : R[B[i + 1375*t]] + R[C[i + 1375*t]];
R[i + 2289*t] = Op[i + 1376*t] ? R[B[i + 1376*t]] * R[C[i + 1376*t]] : R[B[i + 1376*t]] + R[C[i + 1376*t]];
R[i + 2290*t] = Op[i + 1377*t] ? R[B[i + 1377*t]] * R[C[i + 1377*t]] : R[B[i + 1377*t]] + R[C[i + 1377*t]];
R[i + 2291*t] = Op[i + 1378*t] ? R[B[i + 1378*t]] * R[C[i + 1378*t]] : R[B[i + 1378*t]] + R[C[i + 1378*t]];
R[i + 2292*t] = Op[i + 1379*t] ? R[B[i + 1379*t]] * R[C[i + 1379*t]] : R[B[i + 1379*t]] + R[C[i + 1379*t]];
R[i + 2293*t] = Op[i + 1380*t] ? R[B[i + 1380*t]] * R[C[i + 1380*t]] : R[B[i + 1380*t]] + R[C[i + 1380*t]];
R[i + 2294*t] = Op[i + 1381*t] ? R[B[i + 1381*t]] * R[C[i + 1381*t]] : R[B[i + 1381*t]] + R[C[i + 1381*t]];
R[i + 2295*t] = Op[i + 1382*t] ? R[B[i + 1382*t]] * R[C[i + 1382*t]] : R[B[i + 1382*t]] + R[C[i + 1382*t]];
R[i + 2296*t] = Op[i + 1383*t] ? R[B[i + 1383*t]] * R[C[i + 1383*t]] : R[B[i + 1383*t]] + R[C[i + 1383*t]];
R[i + 2297*t] = Op[i + 1384*t] ? R[B[i + 1384*t]] * R[C[i + 1384*t]] : R[B[i + 1384*t]] + R[C[i + 1384*t]];
R[i + 2298*t] = Op[i + 1385*t] ? R[B[i + 1385*t]] * R[C[i + 1385*t]] : R[B[i + 1385*t]] + R[C[i + 1385*t]];
__syncthreads();
R[i + 2299*t] = Op[i + 1386*t] ? R[B[i + 1386*t]] * R[C[i + 1386*t]] : R[B[i + 1386*t]] + R[C[i + 1386*t]];
R[i + 2300*t] = Op[i + 1387*t] ? R[B[i + 1387*t]] * R[C[i + 1387*t]] : R[B[i + 1387*t]] + R[C[i + 1387*t]];
R[i + 2301*t] = Op[i + 1388*t] ? R[B[i + 1388*t]] * R[C[i + 1388*t]] : R[B[i + 1388*t]] + R[C[i + 1388*t]];
R[i + 2302*t] = Op[i + 1389*t] ? R[B[i + 1389*t]] * R[C[i + 1389*t]] : R[B[i + 1389*t]] + R[C[i + 1389*t]];
R[i + 2303*t] = Op[i + 1390*t] ? R[B[i + 1390*t]] * R[C[i + 1390*t]] : R[B[i + 1390*t]] + R[C[i + 1390*t]];
R[i + 2304*t] = Op[i + 1391*t] ? R[B[i + 1391*t]] * R[C[i + 1391*t]] : R[B[i + 1391*t]] + R[C[i + 1391*t]];
R[i + 2305*t] = Op[i + 1392*t] ? R[B[i + 1392*t]] * R[C[i + 1392*t]] : R[B[i + 1392*t]] + R[C[i + 1392*t]];
R[i + 2306*t] = Op[i + 1393*t] ? R[B[i + 1393*t]] * R[C[i + 1393*t]] : R[B[i + 1393*t]] + R[C[i + 1393*t]];
R[i + 2307*t] = Op[i + 1394*t] ? R[B[i + 1394*t]] * R[C[i + 1394*t]] : R[B[i + 1394*t]] + R[C[i + 1394*t]];
R[i + 2308*t] = Op[i + 1395*t] ? R[B[i + 1395*t]] * R[C[i + 1395*t]] : R[B[i + 1395*t]] + R[C[i + 1395*t]];
R[i + 2309*t] = Op[i + 1396*t] ? R[B[i + 1396*t]] * R[C[i + 1396*t]] : R[B[i + 1396*t]] + R[C[i + 1396*t]];
R[i + 2310*t] = Op[i + 1397*t] ? R[B[i + 1397*t]] * R[C[i + 1397*t]] : R[B[i + 1397*t]] + R[C[i + 1397*t]];
R[i + 2311*t] = Op[i + 1398*t] ? R[B[i + 1398*t]] * R[C[i + 1398*t]] : R[B[i + 1398*t]] + R[C[i + 1398*t]];
__syncthreads();
R[i + 2312*t] = Op[i + 1399*t] ? R[B[i + 1399*t]] * R[C[i + 1399*t]] : R[B[i + 1399*t]] + R[C[i + 1399*t]];
R[i + 2313*t] = Op[i + 1400*t] ? R[B[i + 1400*t]] * R[C[i + 1400*t]] : R[B[i + 1400*t]] + R[C[i + 1400*t]];
R[i + 2314*t] = Op[i + 1401*t] ? R[B[i + 1401*t]] * R[C[i + 1401*t]] : R[B[i + 1401*t]] + R[C[i + 1401*t]];
R[i + 2315*t] = Op[i + 1402*t] ? R[B[i + 1402*t]] * R[C[i + 1402*t]] : R[B[i + 1402*t]] + R[C[i + 1402*t]];
R[i + 2316*t] = Op[i + 1403*t] ? R[B[i + 1403*t]] * R[C[i + 1403*t]] : R[B[i + 1403*t]] + R[C[i + 1403*t]];
R[i + 2317*t] = Op[i + 1404*t] ? R[B[i + 1404*t]] * R[C[i + 1404*t]] : R[B[i + 1404*t]] + R[C[i + 1404*t]];
R[i + 2318*t] = Op[i + 1405*t] ? R[B[i + 1405*t]] * R[C[i + 1405*t]] : R[B[i + 1405*t]] + R[C[i + 1405*t]];
R[i + 2319*t] = Op[i + 1406*t] ? R[B[i + 1406*t]] * R[C[i + 1406*t]] : R[B[i + 1406*t]] + R[C[i + 1406*t]];
R[i + 2320*t] = Op[i + 1407*t] ? R[B[i + 1407*t]] * R[C[i + 1407*t]] : R[B[i + 1407*t]] + R[C[i + 1407*t]];
R[i + 2321*t] = Op[i + 1408*t] ? R[B[i + 1408*t]] * R[C[i + 1408*t]] : R[B[i + 1408*t]] + R[C[i + 1408*t]];
__syncthreads();
R[i + 2322*t] = Op[i + 1409*t] ? R[B[i + 1409*t]] * R[C[i + 1409*t]] : R[B[i + 1409*t]] + R[C[i + 1409*t]];
R[i + 2323*t] = Op[i + 1410*t] ? R[B[i + 1410*t]] * R[C[i + 1410*t]] : R[B[i + 1410*t]] + R[C[i + 1410*t]];
R[i + 2324*t] = Op[i + 1411*t] ? R[B[i + 1411*t]] * R[C[i + 1411*t]] : R[B[i + 1411*t]] + R[C[i + 1411*t]];
R[i + 2325*t] = Op[i + 1412*t] ? R[B[i + 1412*t]] * R[C[i + 1412*t]] : R[B[i + 1412*t]] + R[C[i + 1412*t]];
R[i + 2326*t] = Op[i + 1413*t] ? R[B[i + 1413*t]] * R[C[i + 1413*t]] : R[B[i + 1413*t]] + R[C[i + 1413*t]];
R[i + 2327*t] = Op[i + 1414*t] ? R[B[i + 1414*t]] * R[C[i + 1414*t]] : R[B[i + 1414*t]] + R[C[i + 1414*t]];
__syncthreads();
R[i + 2328*t] = Op[i + 1415*t] ? R[B[i + 1415*t]] * R[C[i + 1415*t]] : R[B[i + 1415*t]] + R[C[i + 1415*t]];
R[i + 2329*t] = Op[i + 1416*t] ? R[B[i + 1416*t]] * R[C[i + 1416*t]] : R[B[i + 1416*t]] + R[C[i + 1416*t]];
R[i + 2330*t] = Op[i + 1417*t] ? R[B[i + 1417*t]] * R[C[i + 1417*t]] : R[B[i + 1417*t]] + R[C[i + 1417*t]];
R[i + 2331*t] = Op[i + 1418*t] ? R[B[i + 1418*t]] * R[C[i + 1418*t]] : R[B[i + 1418*t]] + R[C[i + 1418*t]];
R[i + 2332*t] = Op[i + 1419*t] ? R[B[i + 1419*t]] * R[C[i + 1419*t]] : R[B[i + 1419*t]] + R[C[i + 1419*t]];
__syncthreads();
R[i + 2333*t] = Op[i + 1420*t] ? R[B[i + 1420*t]] * R[C[i + 1420*t]] : R[B[i + 1420*t]] + R[C[i + 1420*t]];
R[i + 2334*t] = Op[i + 1421*t] ? R[B[i + 1421*t]] * R[C[i + 1421*t]] : R[B[i + 1421*t]] + R[C[i + 1421*t]];
R[i + 2335*t] = Op[i + 1422*t] ? R[B[i + 1422*t]] * R[C[i + 1422*t]] : R[B[i + 1422*t]] + R[C[i + 1422*t]];
R[i + 2336*t] = Op[i + 1423*t] ? R[B[i + 1423*t]] * R[C[i + 1423*t]] : R[B[i + 1423*t]] + R[C[i + 1423*t]];
R[i + 2337*t] = Op[i + 1424*t] ? R[B[i + 1424*t]] * R[C[i + 1424*t]] : R[B[i + 1424*t]] + R[C[i + 1424*t]];
__syncthreads();
R[i + 2338*t] = Op[i + 1425*t] ? R[B[i + 1425*t]] * R[C[i + 1425*t]] : R[B[i + 1425*t]] + R[C[i + 1425*t]];
R[i + 2339*t] = Op[i + 1426*t] ? R[B[i + 1426*t]] * R[C[i + 1426*t]] : R[B[i + 1426*t]] + R[C[i + 1426*t]];
R[i + 2340*t] = Op[i + 1427*t] ? R[B[i + 1427*t]] * R[C[i + 1427*t]] : R[B[i + 1427*t]] + R[C[i + 1427*t]];
__syncthreads();
R[i + 2341*t] = Op[i + 1428*t] ? R[B[i + 1428*t]] * R[C[i + 1428*t]] : R[B[i + 1428*t]] + R[C[i + 1428*t]];
R[i + 2342*t] = Op[i + 1429*t] ? R[B[i + 1429*t]] * R[C[i + 1429*t]] : R[B[i + 1429*t]] + R[C[i + 1429*t]];
__syncthreads();
R[i + 2343*t] = Op[i + 1430*t] ? R[B[i + 1430*t]] * R[C[i + 1430*t]] : R[B[i + 1430*t]] + R[C[i + 1430*t]];
R[i + 2344*t] = Op[i + 1431*t] ? R[B[i + 1431*t]] * R[C[i + 1431*t]] : R[B[i + 1431*t]] + R[C[i + 1431*t]];
__syncthreads();
R[i + 2345*t] = Op[i + 1432*t] ? R[B[i + 1432*t]] * R[C[i + 1432*t]] : R[B[i + 1432*t]] + R[C[i + 1432*t]];
__syncthreads();
R[i + 2346*t] = Op[i + 1433*t] ? R[B[i + 1433*t]] * R[C[i + 1433*t]] : R[B[i + 1433*t]] + R[C[i + 1433*t]];
__syncthreads();
R[i + 2347*t] = Op[i + 1434*t] ? R[B[i + 1434*t]] * R[C[i + 1434*t]] : R[B[i + 1434*t]] + R[C[i + 1434*t]];
__syncthreads();
R[i + 2348*t] = Op[i + 1435*t] ? R[B[i + 1435*t]] * R[C[i + 1435*t]] : R[B[i + 1435*t]] + R[C[i + 1435*t]];
__syncthreads();
R[i + 2349*t] = Op[i + 1436*t] ? R[B[i + 1436*t]] * R[C[i + 1436*t]] : R[B[i + 1436*t]] + R[C[i + 1436*t]];
__syncthreads();
R[i + 2350*t] = Op[i + 1437*t] ? R[B[i + 1437*t]] * R[C[i + 1437*t]] : R[B[i + 1437*t]] + R[C[i + 1437*t]];
if (i==0) { final += R[2350*t]; }
__syncthreads();
}
if (i==0) { A[0]= final;}
}
|
9,751 | #include<stdlib.h>
#include<stdio.h>
#include <math.h>
#include<sys/time.h>
__global__ void MatrixTranspose(float *a,float *b,int nx, int ny){
int ix = threadIdx.x+ blockIdx.x*blockDim.x;
int iy = threadIdx.y+ blockIdx.y*blockDim.y;
int idx = ix*ny + iy;
int odx= iy*nx + ix;
if((ix<nx)&&(iy<ny)){
b[odx]=a[idx];
}
}
__global__ void MatrixMul(float *a,float *b, float *c, int m, int n, int k)
{
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
int sum = 0;
if( col < k && row < m)
{
for(int i = 0; i < n; i++)
{
sum += a[row * n + i] * b[i * k + col];
}
c[row * k + col] = sum;
}
}
__global__ void MatAdd(float *A, float *B, float *C, int nx, int ny){
int ix = threadIdx.x+ blockIdx.x*blockDim.x;
int iy = threadIdx.y+ blockIdx.y*blockDim.y;
int idx = ix*ny + iy;
if((ix<nx)&&(iy<ny)){
C[idx]=A[idx]+B[idx];
}
}
__global__ void Mul(float *A, float *B, float *C, int nx, int ny){
int ix = threadIdx.x+ blockIdx.x*blockDim.x;
int iy = threadIdx.y+ blockIdx.y*blockDim.y;
int idx = ix*ny + iy;
if((ix<nx)&&(iy<ny)){
C[idx]=A[idx]*B[idx];
}
}
__global__ void div(float *A, float *B, float *C, int nx, int ny){
int ix = threadIdx.x+ blockIdx.x*blockDim.x;
int iy = threadIdx.y+ blockIdx.y*blockDim.y;
int idx = ix*ny + iy;
if((ix<nx)&&(iy<ny)){
C[idx]=A[idx]/B[idx];
}
}
__global__ void MatSub(float *A, float *B, float *C, int nx, int ny){
int ix = threadIdx.x+ blockIdx.x*blockDim.x;
int iy = threadIdx.y+ blockIdx.y*blockDim.y;
int idx = ix*ny + iy;
if((ix<nx)&&(iy<ny)){
C[idx]=A[idx]-B[idx];
}
}
double getTimeStamp(){
struct timeval tv;
gettimeofday(&tv, NULL);
return (double) tv.tv_usec/1000000+ tv.tv_sec;
}
struct matStruct{
float *m;
int x;
int y;
};
typedef struct matStruct matrix;
matrix setup_matrix(int x,int y)
{
matrix p;
p.m= (float *)malloc(x*y*sizeof(float *));
p.x=x;
p.y=y;
return p;
}
matrix transpose(matrix A){
matrix C;
C=setup_matrix(A.y,A.x);
float *d_A, *d_C;
cudaMalloc((void **) &d_A, ((A.x*A.y)*sizeof(float)));
cudaMalloc((void **) &d_C, ((C.x*C.y)*sizeof(float)));
cudaMemcpy(d_A,A.m, (A.x*A.y)*sizeof(float), cudaMemcpyHostToDevice );
dim3 block(32,32);
dim3 grid(1,1);
MatrixTranspose<<<grid,block>>>(d_A,d_C,A.x,A.y);
cudaMemcpy(C.m,d_C,(C.x*C.y)*sizeof(float), cudaMemcpyDeviceToHost);
return C;
}
matrix matmul(matrix A, matrix B){
if ((A.y==B.x))
{ matrix C;
C=setup_matrix(A.x,B.y);
float *d_A, *d_B, *d_C;
cudaMalloc((void **) &d_A, ((A.x*A.y)*sizeof(float)));
cudaMalloc((void **) &d_B, ((B.x*B.y)*sizeof(float)));
cudaMalloc((void **) &d_C, ((C.x*C.y)*sizeof(float)));
cudaMemcpy(d_A,A.m, (A.x*A.y)*sizeof(float), cudaMemcpyHostToDevice );
cudaMemcpy(d_B,B.m, (B.x*B.y)*sizeof(float), cudaMemcpyHostToDevice );
printf("%d %d\n",C.x,C.y);
dim3 block(32,32);
dim3 grid(1,1);
MatrixMul<<<grid,block>>>(d_A,d_B,d_C,A.x,A.y,B.y);
cudaMemcpy(C.m,d_C,(C.x*C.y)*sizeof(float), cudaMemcpyDeviceToHost);
return C;
}
else{
printf("Error:Vector Sum failed incompatible sizes");
matrix C;
C=setup_matrix(A.x,A.y);
return C;
}
}
matrix add_mat(matrix A, matrix B){
if ((A.x==B.x)&&(A.y==B.y))
{ matrix C;
C=setup_matrix(A.x,A.y);
float *d_A, *d_B, *d_C;
float *h_dC;
int bytes=(A.x*A.y)*sizeof(float);
cudaError_t status3 = cudaMallocHost((void**)&h_dC, bytes);
cudaMalloc((void **) &d_A, bytes);
cudaMalloc((void **) &d_B, bytes);
cudaMalloc((void **) &d_C,bytes);
cudaMemcpy(d_A,A.m, bytes, cudaMemcpyHostToDevice );
cudaMemcpy(d_B,B.m, bytes, cudaMemcpyHostToDevice );
dim3 block(A.x,A.y);
dim3 grid(1,1);
MatAdd<<<grid,block>>>(d_A,d_B,d_C, A.x,A.y);
cudaDeviceSynchronize();
cudaMemcpy(C.m,d_C,bytes, cudaMemcpyDeviceToHost);
return C;
}
else{
printf("Error:Vector Sum failed incompatible sizes");
matrix C;
C=setup_matrix(A.x,A.y);
return C;
}
}
matrix multiply(matrix A, matrix B){
if ((A.x==B.x)&&(A.y==B.y))
{ matrix C;
C=setup_matrix(A.x,A.y);
float *d_A, *d_B, *d_C;
float *h_dC;
int bytes=(A.x*A.y)*sizeof(float);
cudaError_t status3 = cudaMallocHost((void**)&h_dC, bytes);
cudaMalloc((void **) &d_A, bytes);
cudaMalloc((void **) &d_B, bytes);
cudaMalloc((void **) &d_C,bytes);
cudaMemcpy(d_A,A.m, bytes, cudaMemcpyHostToDevice );
cudaMemcpy(d_B,B.m, bytes, cudaMemcpyHostToDevice );
dim3 block(A.x,A.y);
dim3 grid(1,1);
Mul<<<grid,block>>>(d_A,d_B,d_C, A.x,A.y);
cudaDeviceSynchronize();
cudaMemcpy(C.m,d_C,bytes, cudaMemcpyDeviceToHost);
return C;
}
else{
printf("Error:Vector Sum failed incompatible sizes");
matrix C;
C=setup_matrix(A.x,A.y);
return C;
}
}
matrix sub_mat(matrix A, matrix B){
if ((A.x==B.x)&&(A.y==B.y))
{ matrix C;
C=setup_matrix(A.x,A.y);
float *d_A, *d_B, *d_C;
float *h_dC;
int bytes=(A.x*A.y)*sizeof(float);
cudaError_t status3 = cudaMallocHost((void**)&h_dC, bytes);
cudaMalloc((void **) &d_A, bytes);
cudaMalloc((void **) &d_B, bytes);
cudaMalloc((void **) &d_C,bytes);
cudaMemcpy(d_A,A.m, bytes, cudaMemcpyHostToDevice );
cudaMemcpy(d_B,B.m, bytes, cudaMemcpyHostToDevice );
dim3 block(A.x,A.y);
dim3 grid(1,1);
MatSub<<<grid,block>>>(d_A,d_B,d_C, A.x,A.y);
cudaDeviceSynchronize();
cudaMemcpy(C.m,d_C,bytes, cudaMemcpyDeviceToHost);
return C;
}
else{
printf("Error:Vector Sum failed incompatible sizes");
matrix C;
C=setup_matrix(A.x,A.y);
return C;
}
}
matrix divide(matrix A, matrix B){
if ((A.x==B.x)&&(A.y==B.y))
{ matrix C;
C=setup_matrix(A.x,A.y);
float *d_A, *d_B, *d_C;
float *h_dC;
int bytes=(A.x*A.y)*sizeof(float);
cudaError_t status3 = cudaMallocHost((void**)&h_dC, bytes);
cudaMalloc((void **) &d_A, bytes);
cudaMalloc((void **) &d_B, bytes);
cudaMalloc((void **) &d_C,bytes);
cudaMemcpy(d_A,A.m, bytes, cudaMemcpyHostToDevice );
cudaMemcpy(d_B,B.m, bytes, cudaMemcpyHostToDevice );
dim3 block(A.x,A.y);
dim3 grid(1,1);
div<<<grid,block>>>(d_A,d_B,d_C, A.x,A.y);
cudaDeviceSynchronize();
cudaMemcpy(C.m,d_C,bytes, cudaMemcpyDeviceToHost);
return C;
}
else{
printf("Error:Vector Sum failed incompatible sizes");
matrix C;
C=setup_matrix(A.x,A.y);
return C;
}
}
int main( int argc, char *argv[])
{
if (argc !=3){
printf("Error: wrong number of args\n");
exit(0);
}
int nx= atoi(argv[1]);
int ny = atoi( argv[2]);
matrix a1,b1,c1;
a1=setup_matrix(3,3);
b1=setup_matrix(3,6);
for(int i=0; i<a1.x; i++)
{for(int j=0;j<a1.y;j++)
{a1.m[a1.y*i+j]=2;
printf("%f ",a1.m[a1.y*i+j]);
}
printf("\n");
}
for(int i=0; i<b1.x; i++)
{for(int j=0;j<b1.y;j++)
{b1.m[b1.y*i+j]=1;
printf("%f ",b1.m[b1.y*i+j]);
}
printf("\n");
}
c1=matmul(a1,b1);
for(int i=0; i<c1.x; i++)
{for(int j=0;j<c1.y;j++)
{printf("%f ",c1.m[c1.y*i+j]);
}
printf("\n");
}
}
|
9,752 | #include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <cuda.h>
#define THREADS_PER_BLOCK 512
#define NUM_BLOCKS 512
/* used for debugging */
#define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, char *file, int line, bool abort=true) {
if(code != cudaSuccess) {
fprintf(stderr, "GPUassert: %s, %s, %d\n", cudaGetErrorString(code), file, line);
if(abort) exit(code);
}
}
/* function declarations */
unsigned int getmax(unsigned int *, unsigned int);
__global__ void getmaxcu(unsigned int *, unsigned int *, unsigned int);
int main(int argc, char *argv[])
{
unsigned int size = 0; // The size of the array
unsigned int i; // loop index
unsigned int * numbers; //pointer to the array
if(argc !=2)
{
printf("usage: maxseq num\n");
printf("num = size of the array\n");
exit(1);
}
size = atol(argv[1]);
numbers = (unsigned int *)malloc(size * sizeof(unsigned int));
if( !numbers )
{
printf("Unable to allocate mem for an array of size %u\n", size);
exit(1);
}
srand(time(NULL)); // setting a seed for the random number generator
// Fill-up the array with random numbers from 0 to size-1
for( i = 0; i < size; i++)
numbers[i] = rand() % size;
/* define the number of blocks, a host array for the maxes, and device arrays */
unsigned int *maxes = (unsigned int *)malloc(NUM_BLOCKS * sizeof(unsigned int));
unsigned int *dev_num, *dev_maxes;
/*allocate space on the device */
gpuErrchk(cudaMalloc((void**)&dev_num, size * sizeof(unsigned int)));
gpuErrchk(cudaMalloc((void**)&dev_maxes, NUM_BLOCKS * sizeof(unsigned int)));
/*do our copies and execute the kernel */
gpuErrchk(cudaMemcpy(dev_num, numbers, size * sizeof(unsigned int), cudaMemcpyHostToDevice));
getmaxcu<<<NUM_BLOCKS, THREADS_PER_BLOCK>>>(dev_num, dev_maxes, size);
gpuErrchk(cudaPeekAtLastError()); //debug info
gpuErrchk(cudaDeviceSynchronize());
gpuErrchk(cudaMemcpy(maxes, dev_maxes, NUM_BLOCKS * sizeof(unsigned int), cudaMemcpyDeviceToHost));
/* free space on the device */
cudaFree(dev_num);
cudaFree(dev_maxes);
/* the final max calculation is done on the host
* at this point we have few enough values that using the gpu is not necessary */
unsigned int overall_max = 0;
for(i = 0; i < NUM_BLOCKS; ++i) {
if(overall_max < maxes[i])
overall_max = maxes[i];
}
printf(" The maximum number in the array is: %u\n", overall_max);
free(numbers);
free(maxes);
exit(0);
}
/*
input: pointer to an array of long int
number of elements in the array
output: the maximum number of the array
*/
unsigned int getmax(unsigned int num[], unsigned int size)
{
unsigned int i;
unsigned int max = num[0];
for(i = 1; i < size; i++)
if(num[i] > max)
max = num[i];
return( max );
}
__global__ void getmaxcu(unsigned int * g_idata, unsigned int * g_odata, unsigned int size) {
unsigned int tid = threadIdx.x;
unsigned int bid = blockIdx.x;
unsigned int i = bid * blockDim.x + tid;
/* find the maximum value of each block using a reduction */
if(i < size) {
unsigned int stride;
for(stride = THREADS_PER_BLOCK / 2; stride > 0; stride >>= 1) {
if(tid < stride) {
if(g_idata[tid] < g_idata[tid + stride])
g_idata[tid] = g_idata[tid + stride];
}
}
}
__syncthreads();
/*write the result of each block to the output array */
if(tid == 0)
g_odata[bid] = g_idata[0];
} |
9,753 | #include "includes.h"
__global__ void CopyVariable(double *var_in, double *var_out, int size) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
while (tid < size) {
// Transfer data and memory
var_out[tid] = var_in[tid];
// Update thread id if vector is long
tid += blockDim.x * gridDim.x;
}
} |
9,754 | #include <cuda.h>
#include <cuda_runtime.h>
#include <curand.h>
#include "cuda_utils.cuh"
__host__ void random_init(data_t* data,
size_t size_in_bytes,
unsigned long long seed) {
curandGenerator_t gen;
curandCreateGenerator(&gen, CURAND_RNG_PSEUDO_DEFAULT);
curandSetPseudoRandomGeneratorSeed(gen, seed);
curandGenerate(gen, (unsigned int*)data,
size_in_bytes / sizeof(unsigned int));
curandDestroyGenerator(gen);
}
|
9,755 | /* File: mat_add.cu
* Purpose: Implement matrix addition on a gpu using cuda
*
* Output: Result of matrix addition.
*
* Notes:
* 1. There are m blocks with n threads each.
*/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
//#include "cuPrintf.cuh"
//#include "cuPrintf.cu"
//#include "utils/cuPrintf.cu"
/*---------------------------------------------------------------------
* Kernel: Mat_add
* Purpose: Implement matrix addition
* In args: A, B, m, n
* Out arg: C
*/
__global__ void Mat_add_Vector(float matIn[], float vRef[], float matOut[], int numVec, int vecDim) {
int threadCol = blockIdx.y * blockDim.x + threadIdx.x;
int threadRow = blockIdx.x ;
int indexOfMatrix = threadCol + threadRow * vecDim;
if(threadCol < vecDim )
matOut[indexOfMatrix] = matIn[indexOfMatrix] + vRef[threadCol];
} /* Mat_add */
/*---------------------------------------------------------------------
* Function: Fill_matrix
* Purpose: Fill an m x n matrix with random values
* In args: m, n
* Out arg: A
*/
void Fill_matrix(float A[], int m, int n) {
int i, j;
//numVec, dimVec
for (i = 0; i < m; i++)
for (j = 0; j < n; j++)
A[i*n+j]=rand()/(float)RAND_MAX;
} /* Read_matrix */
/*---------------------------------------------------------------------
* Function: Print_matrix
* Purpose: Print an m x n matrix to stdout
* In args: title, A, m, n
*/
void Print_matrix(const char title[], float A[], int numVec, int dimVec, int m, int n) {
int i, j;
//numVec, dimVec
printf("%s\n", title);
for (i = 0; i < m; i++) {
for (j = 0; j < n; j++)
printf("%.2f ", A[i*dimVec+j]);
printf("\n");
}
} /* Print_matrix */
void checkError(cudaError_t error, const char function[])
{
if(error != cudaSuccess)
{
printf("\"%s\" has a problem with error code %d and desc: %s\n", function, error, cudaGetErrorString(error));
exit(-1);
}
}
bool checkIfMatricesEqual(float * mat1, float * mat2, float matSize)
{
int i = 0;
for( ; i < matSize; i++)
if(mat1[i] != mat2[i]){
printf("values different for i: %d\n", i);
printf("mat1[i] = %d, mat2[i] = %d\n", mat1[i], mat2[i]);
return false;
}
return true;
}
/* Host code */
int main(int argc, char* argv[]) {
size_t numVec = 10000;//mat size
size_t dimVec = 10000;
// variables for threads per block, number of blocks.
int threadsPerBlock = 1024;//, blocksInGrid = 0;
//create cuda event variables
cudaEvent_t hostStart, hostStop, deviceStart, deviceStop;
float timeDifferenceOnHost, timeDifferenceOnDevice;
//initialize cuda timing variables
cudaEventCreate(&hostStart);
cudaEventCreate(&hostStop);
cudaEventCreate(&deviceStart);
cudaEventCreate(&deviceStop);
float *h_A, *h_B, *h_C, *h_C2;//PC
float *d_A, *d_B, *d_C;//GPU
size_t size, matrixSize;
/* Get size of matrices */
printf("dimVec = %d, numVec = %d\n", dimVec, numVec);
matrixSize = numVec*dimVec;
size = matrixSize*sizeof(float);
size_t vecSize=dimVec*sizeof(float);
h_A = (float*) malloc(size);
h_B = (float*) malloc(vecSize);
h_C = (float*) calloc(size,1);
h_C2 = (float*) calloc(size,1);
printf("size=%d vecSize=%d\n",size,vecSize);
Fill_matrix(h_A, numVec, dimVec);
Fill_matrix(h_B, 1, dimVec);
Print_matrix("A =", h_A, numVec, dimVec, 4, 5);
Print_matrix("B =", h_B, numVec, dimVec, 1, 5);
printf("Adding matrices on CPU...\n");
cudaEventRecord(hostStart, 0);
for(int i = 0 ; i < numVec; i++)
for(int j = 0 ; j < dimVec; j++){
h_C2[i*dimVec+j] = h_A[i*dimVec+j] + h_B[j];
//printf("i=%d, j=%d C2=%f a=%f b=%f i*dimVec+j=%d\n",i,j,h_C2[i*dimVec+j],h_A[i*dimVec+j],h_B[j],i*dimVec+j);
}
cudaEventRecord(hostStop, 0);
cudaEventElapsedTime(&timeDifferenceOnHost, hostStart, hostStop);
printf("Matrix addition over. Time taken on CPU: %5.5f\n",
timeDifferenceOnHost);
/* Allocate matrices in device memory */
cudaMalloc(&d_A, size);
cudaMalloc(&d_B, vecSize);
cudaMalloc(&d_C, size);
/* Copy matrices from host memory to device memory */
cudaMemcpy(d_A, h_A, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_B, h_B, vecSize, cudaMemcpyHostToDevice);
//create a proper grid block using dim3
/* Invoke kernel using m thread blocks, each of */
/* which contains n threads */
dim3 block(threadsPerBlock);
dim3 grid( numVec, (dimVec+threadsPerBlock-1)/threadsPerBlock );
cudaEventRecord(deviceStart, 0);
//d_A -> inMatrix, d_B vRef, d_C outMat
//block=1024, grid.x=10, grid.y=1024
printf("grid.x=%d grid.y=%d block.x=%d",grid.x, grid.y, block.x);
Mat_add_Vector<<<grid, block>>>(d_A, d_B, d_C, numVec, dimVec);
//error=invalid configuration argumentvalues different for i: 0
cudaError_t code=cudaGetLastError();
if (code)
printf("error=%s",cudaGetErrorString(code));
else
printf("code=%d",code);
cudaDeviceSynchronize();
cudaEventRecord(deviceStop, 0);
/* Wait for the kernel to complete */
cudaThreadSynchronize();
cudaEventElapsedTime(&timeDifferenceOnDevice, deviceStart, deviceStop);
/* Copy result from device memory to host memory */
checkError(cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost), "Matrix C Copy from device to Host");
if(checkIfMatricesEqual(h_C, h_C2, matrixSize))
printf("Kernels correct!\n");
else
printf("Kernel logic wrong!\n");
printf("Finished addition on GPU. Time taken: %5.5f\n", timeDifferenceOnDevice);
printf("Speedup: %5.5f\n", (float)timeDifferenceOnHost/timeDifferenceOnDevice);
Print_matrix("The sum (CPU) is: ", h_C2, numVec, dimVec, 4, 5);
Print_matrix("The sum (GPU) is: ", h_C, numVec, dimVec, 4, 5);
/* Free device memory */
cudaFree(d_A);
cudaFree(d_B);
cudaFree(d_C);
/* Free host memory */
free(h_A);
free(h_B);
free(h_C);
return 0;
} /* main */
|
9,756 | #include "includes.h"
__global__ void calc_histogram(char* dbuff, unsigned int* dcount, unsigned int size, float stride) {
unsigned int index = blockIdx.x * blockDim.x + threadIdx.x;
unsigned int start_pos = stride * index;
unsigned int stop_pos = start_pos + stride;
unsigned int lcount[10] = { 0 };
if (size < stop_pos) {
stop_pos = size;
}
for (unsigned int i = start_pos; i < stop_pos; i++) {
// Increment counter per occurances
if (dbuff[i] == '0') {
lcount[0] += 1;
} else if (dbuff[i] == '1') {
lcount[1] += 1;
} else if (dbuff[i] == '2') {
lcount[2] += 1;
} else if (dbuff[i] == '3') {
lcount[3] += 1;
} else if (dbuff[i] == '4') {
lcount[4] += 1;
} else if (dbuff[i] == '5') {
lcount[5] += 1;
} else if (dbuff[i] == '6') {
lcount[6] += 1;
} else if (dbuff[i] == '7') {
lcount[7] += 1;
} else if (dbuff[i] == '8') {
lcount[8] += 1;
} else if (dbuff[i] == '9') {
lcount[9] += 1;
}
}
__syncthreads();
dcount[0] += lcount[0];
dcount[1] += lcount[1];
dcount[2] += lcount[2];
dcount[3] += lcount[3];
dcount[4] += lcount[4];
dcount[5] += lcount[5];
dcount[6] += lcount[6];
dcount[7] += lcount[7];
dcount[8] += lcount[8];
dcount[9] += lcount[9];
} |
9,757 | #include<stdio.h>
__global__ void add(int *a, int *b, int *c)
{
int id = threadIdx.x;
c[id]=a[id]+b[id];
}
int main(void)
{
const int a[5] = {1,2,3,4,5};
const int b[5] = {10,20,30,40,50};
int c[5];
int *d_a,*d_b,*d_c;
int size = sizeof(int)*5;
cudaMalloc((void **)&d_a,sizeof(int)*5);
cudaMalloc((void **)&d_b,sizeof(int)*5);
cudaMalloc((void **)&d_c,sizeof(int)*5);
cudaMemcpy(d_a,a,size,cudaMemcpyHostToDevice);
cudaMemcpy(d_b,b,size,cudaMemcpyHostToDevice);
add<<<1,5>>>(d_a,d_b,d_c);
cudaMemcpy(c,d_c,size,cudaMemcpyDeviceToHost);
for(int i=0;i<5;i++)
{
printf("%d\t",c[i]);
}
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return 0;
}
|
9,758 | #include <stdio.h>
#include <stdlib.h>
#include <stdbool.h>
#include <math.h>
#include <cuda_runtime.h>
#define LIMIT 1200
#define NEGATOR 4294967295
#define SIZE 4
#define ul unsigned
#define ull unsigned long long
typedef struct{
ul* x;
ul* y;
}Point;
//Compare two numbers
__device__ int compare(ul* f, ul* s){
int i;
for (i = SIZE -1; i >= 0; i--){
if (f[i] < s[i]) return -1;
if (f[i] > s[i]) return 1;
}
return 0;
}
//Add two numbers
__device__ void add(ul* a, ul* b, ul* d){
int carry = 0, i;
ull temp;
for (i = 0; i < SIZE; i++){
temp = (ull) a[i] + (ull) b[i] + (ull) carry;
d[i] = temp & (ull) NEGATOR;
carry = temp >> 32;
}
}
//Subtract two numbers
__device__ void subtract(ul* s, ul* n, ul* d){
ull temp;
int takeaway = 0, i;
for (i = 0; i < SIZE; i++){
if (s[i] < n[i] || s[i] < n[i] + takeaway || takeaway*n[i] == NEGATOR){
temp = ((ull) 1 << 32) + (ull) s[i] - (ull) takeaway - (ull) n[i];
takeaway = 1;
}
else{
temp = s[i] - n[i] - takeaway;
takeaway = 0;
}
d[i] = (ul) temp;
}
}
//Distribute 64-bit number between two 32-bit numbers
__device__ void assignSandC(ull temp, ul *S, ul *C){
*S = temp;
*C = temp >> 32;
}
//Montgomery CIOS multiplication
__device__ void montMul(ul* a, ul* b, ul *N, ul nInv, ul *d){
int i,j;
ul C,S, m, overflow = 0, overflow2 = 0;
ull temp;
//Clear destination
for (i = 0; i < SIZE; i++){
d[i] = 0;
}
for (i = 0; i < SIZE; i++){
C = 0;
//Multiplication Step
for (j = 0; j < SIZE; j++){
assignSandC((ull) d[j] + (ull) a[j]*(ull) b[i] + (ull) C, &S, &C);
d[j] = S;
}
assignSandC( (ull) overflow + (ull) C, &S, &C);
overflow = S; overflow2 = C;
C = 0;
m = (ul) (d[0]*nInv)%((ull) 1<<32);
assignSandC( (ull) d[0] + (ull) m * (ull)N[0], &S, &C);
//Reduction Step
for (j=1; j<SIZE; j++){
assignSandC((ull) d[j] + (ull) m * (ull) N[j] + (ull) C, &S, &C);
d[j-1] = S;
}
assignSandC( (ull) overflow + (ull) C, &S, &C);
d[SIZE-1] = S; overflow = overflow2 + C;
}
}
//Standard Right-to-Left binary exponentiation
__device__ void montExp(ul *b, ul e, ul *N, ul nInv, ul *d){
int i, dswaps = 0;
bool first = true;
ul tmpArr[SIZE], baseArr[SIZE], baseTmpArr[SIZE];
ul *tmp = tmpArr, *tmp2, *base = baseArr, *baseTmp = baseTmpArr, *baseTmp2;
memcpy(base, b, SIZE*sizeof(ul));
for (i = 0; i < SIZE; i++){
d[i] = 0;
}
while (e > 0){
if (e & 1){
if (first){
memcpy(tmp, base, SIZE*sizeof(ul));
first = false;
}
else{
montMul(d, base, N, nInv, tmp);
}
tmp2 = d; d = tmp; tmp = tmp2;
dswaps = 1-dswaps;
}
e >>= 1;
montMul(base, base, N, nInv, baseTmp);
baseTmp2 = base; base = baseTmp; baseTmp = baseTmp2;
}
if (dswaps){
memcpy(tmp, d, SIZE*sizeof(ul));
}
}
//Add two Montgomery Curves
__device__ void addPoints(Point p1, Point p2, Point diff, ul *N, ul nInv, Point d, ul *ONE, ul *ZERO){
if (compare(ZERO, p1.x) == 0 && compare(ZERO, p1.y) == 0){
memcpy(d.x, p2.x, SIZE*sizeof(ul));
memcpy(d.y, p2.y, SIZE*sizeof(ul));
return;
}
if (compare(ZERO, p2.x) == 0 && compare(ZERO, p2.y) == 0){
memcpy(d.x, p1.x, SIZE*sizeof(ul));
memcpy(d.y, p1.y, SIZE*sizeof(ul));
return;
}
int i;
//UNeg and VNeg represents if the variables U and V actually contain -U and -V of the formulaes
bool UNeg = compare(p1.x, p1.y) == -1, VNeg = compare(p2.x, p2.y) == -1;
ul U[SIZE], V[SIZE], tmp[SIZE], tmp2[SIZE];
if (UNeg) subtract(p1.y, p1.x, tmp);
else subtract(p1.x, p1.y, tmp);
add(p2.x, p2.y, tmp2);
montMul(tmp, tmp2, N, nInv, U);
if (VNeg) subtract(p2.y, p2.x, tmp);
else subtract(p2.x, p2.y, tmp);
add(p1.x, p1.y, tmp2);
montMul(tmp, tmp2, N, nInv, V);
if (UNeg ^ VNeg){
if (compare(U,V) == 1) subtract(U,V,tmp);
else subtract(V,U,tmp);
}
else add(U,V,tmp);
montMul(tmp, tmp, N, nInv, tmp2);
montMul(diff.y, tmp2, N, nInv, d.x);
if (UNeg ^ VNeg) add(U,V,tmp);
else {
if (compare(U,V) == 1) subtract(U,V,tmp);
else subtract(V,U,tmp);
}
montMul(tmp, tmp, N, nInv, tmp2);
montMul(diff.x, tmp2, N, nInv, d.y);
}
//Double two points on a Montgomery curve
__device__ void doublePoint(Point p, ul *S, ul *N, ul nInv, Point d){
ul dp[SIZE], dm[SIZE], T[SIZE], tmp[SIZE], tmp2[SIZE];
add(p.x, p.y, tmp);
montMul(tmp, tmp, N, nInv, dp);
if (compare(p.x, p.y) == 1) subtract(p.x, p.y, tmp);
else subtract(p.y, p.x, tmp);
montMul(tmp, tmp, N, nInv, dm);
if (compare(dp, dm) > -1) subtract(dp, dm, T);
else{
subtract(dm, dp, tmp);
subtract(N, tmp, T);
}
montMul(dp, dm, N, nInv, d.x);
montMul(S, T, N, nInv, tmp);
add(tmp, dm, tmp2);
montMul(T, tmp2, N, nInv, d.y);
}
//Left-to-right binary scaling with Doubles and Adds
//Keeps track of nP and (n-1)P so that the difference is always P
__device__ void scalePoint(Point p, ul c, ul *S, ul *N, ul nInv, Point d, ul *ONE, ul *ZERO){
ul temp;
int i;
bool started = false;
//if (threadIdx.x + blockIdx.x == 0) printf("%u\n", c);
ul t[SIZE], t2[SIZE], t3[SIZE], t4[SIZE], t5[SIZE], t6[SIZE], t7[SIZE], t8[SIZE];
for (i = 0; i < SIZE; i++){
t[i] = 0;
t2[i] = 0;
t3[i] = p.x[i];
t4[i] = p.y[i];
}
Point kp = {t, t2}, kp1p = {t3, t4}, twokp1 = {t5, t6}, doub = {t7, t8}, pTemp;
for (temp = (ul) 1<<31; temp > 0; temp >>= 1){
if (!started){
if ((c&temp) != 0){
started = true;
}
}
if(started){
addPoints(kp, kp1p, p, N, nInv, twokp1, ONE, ZERO);
if ((c&temp) == 0) {
doublePoint(kp, S, N, nInv, doub);
pTemp = kp; kp = doub; doub = pTemp;
pTemp = kp1p; kp1p = twokp1; twokp1 = pTemp;
}
else{
doublePoint(kp1p, S, N, nInv, doub);
pTemp = kp; kp = twokp1; twokp1 = pTemp;
pTemp = kp1p; kp1p = doub; doub = pTemp;
}
}
}
memcpy(d.x, kp.x, SIZE*sizeof(ul));
memcpy(d.y, kp.y, SIZE*sizeof(ul));
}
//Convert s to Montgomery Representation by shifting right SIZE*32 times
__device__ void toMont(ul *s, ul *N, ul *d){
int i, j, carry, tmpCarry, swaps = 0;
ul tempArr[SIZE], *temp, *memTemp;
temp = tempArr;
memcpy(d, s, SIZE*sizeof(ul));
for (i = 0; i < SIZE*32; i++){
carry = 0;
for (j = 0; j < SIZE; j++){
tmpCarry = (d[j]>>31) != 0;
d[j] = ((ul) (d[j] << 1)) + carry;
carry = tmpCarry;
}
if (compare(d, N) != -1){
subtract(d, N, temp);
memTemp = d; d = temp; temp = memTemp;
swaps = 1-swaps;
}
}
if (swaps == 1){
memcpy(temp, d, SIZE*sizeof(ul));
}
}
//Integer division
__device__ void idiv(ul *b, ul *a, ul *quotient, ul *mod){
int i, shifts, carry, tmpCarry;
ul tempA[SIZE];
memcpy(mod, b, SIZE*sizeof(ul));
for (i = 0; i < SIZE; i++){
quotient[i] = 0;
}
while (compare(a, mod) != 1){
shifts = 0;
memcpy(tempA, a, SIZE*sizeof(ul));
while (compare(tempA, mod) != 1){
carry = 0;
for (i = 0; i < SIZE; i++){
tmpCarry = (tempA[i]>>31) != 0;
tempA[i] = ((ul) (tempA[i] << 1)) + carry;
carry = tmpCarry;
}
shifts += 1;
}
for (i = 0; i < SIZE; i++){
carry = 0;
if (i < SIZE-1) carry = tempA[i+1]%2;
tempA[i] = (tempA[i] >> 1) + (carry << 31);
}
shifts -= 1;
subtract(mod, tempA, mod);
quotient[shifts/32] += 1<<(shifts%32);
}
}
//Standard multiplication
__device__ void regMul(ul* a, ul* b, ul *d){
int i,j;
ul C,S, overflow = 0, overflow2 = 0;
for (i = 0; i < SIZE; i++){
d[i] = 0;
}
for (i = 0; i < SIZE; i++){
C = 0;
for (j = 0; j < SIZE; j++){
assignSandC((ull) d[j+i] + (ull) a[j]*(ull) b[i] + (ull) C, &S, &C);
d[j+i] = S;
}
}
}
//Extended Euclidean algorithm for GCD and modular inverse
__device__ void ee(ul *a, ul *b, ul* ainv, ul* gcd, ul *ZERO){
int i;
ul sArr[SIZE], old_sArr[SIZE], rArr[SIZE], old_rArr[SIZE], quotientArr[SIZE], prodArr[SIZE], tempArr[SIZE], tTemp[SIZE];
ul *s = sArr, *old_s = old_sArr, *r = rArr, *old_r = old_rArr, *quotient = quotientArr, *prod = prodArr, *temp = tempArr, *temp2;
for (i = 0; i < SIZE; i++){
s[i] = 0;
old_s[i] = i == 0;
r[i] = b[i];
old_r[i] = a[i];
}
while (compare(r,ZERO) != 0){
idiv(old_r, r, quotient, temp);
temp2 = old_r;
old_r = r;
r = temp;
temp = temp2;
regMul(quotient, s, prod);
temp2 = temp;
temp = old_s;
old_s = s;
if (compare(temp, prod) != -1){
subtract(temp,prod,temp);
}
else{
subtract(prod, temp, temp);
idiv(temp, b, quotient, tTemp);
subtract(b, tTemp, temp);
}
s = temp;
temp = temp2;
}
memcpy(ainv, old_s, SIZE*sizeof(ul));
memcpy(gcd, old_r, SIZE*sizeof(ul));
}
//Thread that handles all the curve computations
__global__ void curveThread(ul *N, ul *Rsquare, ul *nI, ul *primes, ul *ONE, ul *ZERO, int disp){
//Generate paramter for curve operations
ul sigma = 6+(blockIdx.x*blockDim.x)+threadIdx.x+disp;
ul tempId = threadIdx.x;
int i, j;
ul S[SIZE], t[SIZE], t2[SIZE], t3[SIZE], t4[SIZE], t5[SIZE], t6[SIZE], x[SIZE], z[SIZE], U[SIZE], V[SIZE], SMALLNUM[SIZE], nInv = *nI;
//Store primes in shared memory
__shared__ extern ul p[];
while(tempId < LIMIT){
p[tempId] = primes[tempId];
tempId += blockDim.x;
}
__syncthreads();
for (i = 0; i < SIZE; i++){
t[i] = 0;
t2[i] = 0;
t3[i] = (i==0)*sigma;
t4[i] = 0;
t5[i] = 0;
t6[i] = 0;
U[i] = 0;
V[i] = 0;
SMALLNUM[i] = 0;
}
//Generate Curve and point as per Suyama's Parametrization
SMALLNUM[0] = 5;
regMul(t3, t3, t);
subtract(t, SMALLNUM, t);
SMALLNUM[0] = 4;
regMul(t3, SMALLNUM, t2);
t3[0] = 0;
montMul(t, Rsquare, N, nInv, U);
montMul(t2, Rsquare, N, nInv, V);
montExp(U, 3, N, nInv, x);
montExp(V, 3, N, nInv, z);
t2[0] *= 16;
montMul(t2, Rsquare, N, nInv, t);
montMul(t, x, N, nInv, t3);
montMul(t3, ONE, N, nInv, t5);
ee(t5, N, t, t2, ZERO);
montMul(t, Rsquare, N, nInv, t2);
if(compare(U,V) == 1){
subtract(U, V, t);
montMul(t, t, N, nInv, t3);
montMul(t, t3, N, nInv, t4);
subtract(N, t4, t4);
}
else{
subtract(V, U, t);
montMul(t, t, N, nInv, t3);
montMul(t, t3, N, nInv, t4);
}
SMALLNUM[0] = 3;
montMul(SMALLNUM, Rsquare, N, nInv, t3);
montMul(U, t3, N, nInv, t5);
add(t5, V, t5);
montMul(t5, t4, N, nInv, t6);
montMul(t6, t2, N, nInv, S);
Point P = {x, z}, D = {t3, t4}, twoP = {t5, t6}, pTemp;
//Scale by k
for (i = 0; i < LIMIT; i+=2){
scalePoint(P, p[i]*p[i+1], S, N, nInv, D, ONE, ZERO);
pTemp = D; D = P; P = pTemp;
}
ee(P.x, N, t5, t6, ZERO);
if (compare(t6, ONE) != 0 && compare(t6,N) != 0)
printf("%i: %u %u %u %u\n", sigma, t6[0], t6[1], t6[2], t6[3]);
}
//Setup preliminary information (includes the input N)
__global__ void setup(ul *N, ul *primes, ul *nInv, ul *Rsquare, ul *ONE, ul *ZERO){
ul B1 = 20 * LIMIT, numFound = 0;
int i,j;
if (B1 < 100) B1 = 100;
int *primeOrNot;
size_t size = B1*sizeof(int);
primeOrNot = (int*) malloc(B1*sizeof(int));
for (i = 0; i < B1; i++){
primeOrNot[i] = 0;
}
ul t[SIZE], t2[SIZE], t3[SIZE];
i = 0;
while (i < B1 && numFound < LIMIT){
if (i > 1 && !primeOrNot[i]){
int temp = 1;
while (temp < B1) temp *= i;
temp = temp/i;
primes[numFound] = temp;
numFound += 1;
for (j = 2*i; j < B1; j += i){
primeOrNot[j] = 1;
}
}
i += 1;
}
free(primeOrNot);
for (i = 0; i < SIZE; i++){
ONE[i] = i==0;
ZERO[i] = 0;
t[i] = i==1;
}
//Input the value of N here
N[0] = 3521154867; N[1] = 785645112; N[2] = 2260700419; N[3] = 0; //N[4] = 0; N[5] = 0;
//N[0] = 3619132259; N[1] = 3251792858; N[2] = 2426605881; N[3] = 457503228; N[4] = 1;// N[5] = 0;
//Find negative of modular inverse of N
ee(N, t, t2, t3, ZERO);
*nInv = NEGATOR-t2[0]+1;
//Find conversion number R^2
toMont(ONE, N, t);
toMont(t, N, Rsquare);
}
int main(){
ul *N, *primes, B1, *S, *t, *t2, *t3, *t4, *t5, *t6, *Rsquare, *x, *z, *U, *V, *ONE, *ZERO, *SMALLNUM, *nInv;
ul *hN;
size_t size = sizeof(ul)*LIMIT;
cudaMalloc((void**) &primes, size);
size = sizeof(ul)*SIZE;
cudaMalloc((void**) &N,size);
cudaMalloc((void**) &Rsquare, size);
cudaMalloc((void**) &SMALLNUM, size);
cudaMalloc((void**) &ZERO, size);
cudaMalloc((void**) &ONE, size);
size = sizeof(ul);
cudaMalloc((void**) &nInv, size);
hN = (ul*) malloc(sizeof(ul)*SIZE);
setup<<<1,1>>>(N, primes, nInv, Rsquare, ONE, ZERO);
//Set number of threads here
curveThread<<<1024, 128, LIMIT*sizeof(ul)>>>(N, Rsquare, nInv, primes, ONE, ZERO, 0);
//cudaMemcpy(hN, N, sizeof(ul)*SIZE, cudaMemcpyDeviceToHost);
//printf("%u\n", hN[0]);
printf("DONE\n");
return 0;
} |
9,759 | #include <stdio.h>
#include <cuda.h>
#include <stdlib.h>
__global__ void kernel(float *a, float *b, int x, int y)
{
int i=threadIdx.x+blockIdx.x*blockDim.x;
int j=threadIdx.y+blockIdx.y*blockDim.y;
__shared__ float sm[128];
if (j<x && i<y)
{
sm[threadIdx.x+threadIdx.y*blockDim.x]=a[i+j*x];
__syncthreads();
for (int k=blockDim.x/2;k>0;k++)
{
if (threadIdx.x<k)
sm[threadIdx.x+threadIdx.y*blockDim.x]+=sm[threadIdx.x+k+threadIdx.x*blockDim.x];
__syncthreads();
}
if (threadIdx.x==0)
atomicAdd(&b[j],sm[threadIdx.y*blockDim.x]);
}
}
void initA(float *a, int sx, int sy)
{
for(int j=0;j<sy;j++)
{
for (int i=0;i<sx;i++)
{
a[i+j*sx]=(float)(i+1)/(j+1);
}
}
}
int checkResults(float *a, float *b, int sx, int sy)
{
for (int j=0;j<sy;j++)
{
float sum=0.0;
for (int i=0;i<sx;i++)
{
sum+=a[i+j*sx];
}
if (b[j]!=sum)
{
printf("Error occured in execution in line %i\n",j);
return(-1);
}
}
return 0;
}
int main()
{
int sx=72;
int sy=48;
float *a,*b,*a_dev,*b_dev;
//Memory Management
a=(float*)malloc(sx*sy*sizeof(float));
b=(float*)malloc(sy*sizeof(float));
initA(a,sx,sy);
cudaMalloc((void**)&a_dev,sx*sizeof(float));
cudaMalloc((void**)&b_dev,sizeof(float));
cudaMemcpy(a_dev,a,sx*sy*sizeof(float),cudaMemcpyHostToDevice);
cudaMemset(b_dev,0,sx*sizeof(float));
cudaError_t err=cudaGetLastError();
if (err!=cudaSuccess)
{
printf("An Error occured in Memory Management: %s (%i)\n",cudaGetErrorString(err),err);
return(-1);
}
//Kernel Execution
dim3 block(32,8);
dim3 grid(sx/block.x,sy/block.y);
kernel<<<grid,block>>>(a_dev,b_dev,sx,sy);
cudaDeviceSynchronize();
err=cudaGetLastError();
if (err!=cudaSuccess)
{
printf("An Error occured in Kernel Execution: %s (%i)\n",cudaGetErrorString(err),err);
return(-1);
}
cudaMemcpy(b,b_dev,sy*sizeof(float),cudaMemcpyDeviceToHost);
int result=checkResults(a,b,sx,sy);
free(a);
free(b);
cudaFree(a_dev);
cudaFree(b_dev);
return result;
}
|
9,760 | #include <cstdio>
#include <cstdlib>
#include <math.h>
#include <time.h>
#define MINVAL 0.00
#define MAXVAL 10.0
#define TOL 1e-5
#define NUM_THREADS 16
double CPS = 2.9e9;
int LEN; // to be defined via cmd args
//////////////////////////// CUDA RELATED ////////////////////////////////////
// Assertion to check for errors
#define CUDA_SAFE_CALL(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, char *file, int line, bool abort=true)
{
if (code != cudaSuccess)
{
fprintf(stderr,"CUDA_SAFE_CALL: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort) exit(code);
}
}
__global__ void MMM_kernel(float* A, float* B, float* dst, int len)
{
__shared__ float Ms [NUM_THREADS][NUM_THREADS];
__shared__ float Ns [NUM_THREADS][NUM_THREADS];
int bx, by, tx, ty, row, col;
bx = blockIdx.x;
by = blockIdx.y;
tx = threadIdx.x;
ty = threadIdx.y;
row = by * NUM_THREADS + ty;
col = bx * NUM_THREADS + tx;
float partial = 0;
for(int k = 0; k < len/NUM_THREADS; k++)
{
Ms[ty][tx] = A[row * len + (k * NUM_THREADS + tx)];
Ns[ty][tx] = B[col + (k * NUM_THREADS + ty) * len];
__syncthreads();
for(int r = 0; r < NUM_THREADS; r++)
partial += Ms[ty][r] * Ns[r][tx];
__syncthreads();
}
dst[row * len + col] = partial;
}
////////////////////////////// MATRIX /////////////////////////////////////////
float* matrix_create(int len);
int matrix_init(float* mat, int len);
int matrix_zero(float* mat, int len);
int matrix_copy(float* src, float* dst, int len);
void MMM_CPU(float* A, float* B, float* dst, int len);
///////////////// Time related //////////////////////////////
//rdtsc related
typedef union {
unsigned long long int64;
struct {unsigned int lo, hi;} int32;
} mcps_tctr;
#define MCPS_RDTSC(cpu_c) __asm__ __volatile__ ("rdtsc" : \
"=a" ((cpu_c).int32.lo), "=d"((cpu_c).int32.hi))
int clock_gettime(clockid_t clk_id, struct timespec *tp);
struct timespec diff(struct timespec start, struct timespec end);
double ts_ms(struct timespec ts);
struct timespec ts_diff(struct timespec start, struct timespec end);
double measure_cps(void);
////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////
int main(int argc, char *argv[])
{
if(argc != 2)
{
printf("\nPlease pass a length in.\n");
return 0;
}
LEN = strtol(argv[1], NULL, 10);
if(LEN <= 0)
{
printf("\nLength must be greater than zero\n");
return 0;
}
int size = LEN * LEN * sizeof(float);
int NUM_BLOCKS = LEN / NUM_THREADS;
if(LEN % NUM_THREADS != 0) // die if not a good fit
{
printf("\nOdd Numbr of blocks\n");
return 0;
}
// CUDA Timing
cudaEvent_t start_full, start_mmm, stop_full, stop_mmm;
float d_time_full, d_time_mmm;
// CPU Timing
struct timespec time1, time2;
double h_time;
// CPU set up
float *h_A, *h_B, *h_dst_gpu, *h_dst_cpu, *d_A, *d_B, *d_dst;
measure_cps();
h_A = matrix_create(LEN);
if(!h_A) return 0;
if(!matrix_init(h_A, LEN)) return 0;
h_B = matrix_create(LEN);
if(!h_B) return 0;
if(!matrix_init(h_B, LEN)) return 0;
h_dst_cpu = matrix_create(LEN); // cpu result
if(!h_dst_cpu) return 0;
if(!matrix_zero(h_dst_cpu, LEN)) return 0;
h_dst_gpu = matrix_create(LEN); // gpu result
if(!h_dst_gpu) return 0;
if(!matrix_zero(h_dst_gpu, LEN)) return 0;
// GPU Set up
d_A = NULL;
d_B = NULL;
d_dst = NULL;
CUDA_SAFE_CALL(cudaSetDevice(0));
CUDA_SAFE_CALL(cudaMalloc((void**)&d_A, size));
CUDA_SAFE_CALL(cudaMalloc((void**)&d_B, size));
CUDA_SAFE_CALL(cudaMalloc((void**)&d_dst, size));
cudaEventCreate(&start_full);
cudaEventCreate(&start_mmm);
cudaEventCreate(&stop_full);
cudaEventCreate(&stop_mmm);
// start the GPU calculations
dim3 dimBlock(NUM_THREADS, NUM_THREADS, 1);
dim3 dimGrid(NUM_BLOCKS, NUM_BLOCKS, 1);
cudaEventRecord(start_full,0);
CUDA_SAFE_CALL(cudaMemcpy(d_A, h_A, size, cudaMemcpyHostToDevice));
CUDA_SAFE_CALL(cudaMemcpy(d_B, h_B, size, cudaMemcpyHostToDevice));
cudaEventRecord(start_mmm,0);
MMM_kernel<<<dimGrid, dimBlock>>>(d_A, d_B, d_dst, LEN);
cudaEventRecord(stop_mmm,0);
cudaEventSynchronize(stop_mmm);
CUDA_SAFE_CALL(cudaPeekAtLastError());
CUDA_SAFE_CALL(cudaThreadSynchronize());
CUDA_SAFE_CALL(cudaMemcpy(h_dst_gpu, d_dst, size, cudaMemcpyDeviceToHost));
cudaEventRecord(stop_full, 0);
cudaEventSynchronize(stop_full);
cudaEventElapsedTime(&d_time_mmm, start_mmm, stop_mmm);
cudaEventElapsedTime(&d_time_full, start_full, stop_full);
printf("\nGPU MMM Time: %f ms", d_time_mmm);
printf("\nGPU FUll Time: %f ms", d_time_full);
cudaEventDestroy(start_full);
cudaEventDestroy(stop_full);
//CPU calculation
clock_gettime(CLOCK_REALTIME, &time1);
MMM_CPU(h_A, h_B, h_dst_cpu, LEN);
clock_gettime(CLOCK_REALTIME, &time2);
h_time = ts_ms(ts_diff(time1, time2));
printf("\nCPU Time: %lf ms\n", h_time);
int i, num_elements;
num_elements = LEN * LEN;
for(i = 0; i < num_elements; i++)
{
if((h_dst_cpu - h_dst_gpu) > (float) TOL)
{
printf("\nResult verification issue at element %d | CPU: %f | GPU: %f\n", i, h_dst_cpu, h_dst_gpu);
return 0;
}
}
// Free stuff
CUDA_SAFE_CALL(cudaFree(d_A));
CUDA_SAFE_CALL(cudaFree(d_B));
CUDA_SAFE_CALL(cudaFree(d_dst));
free(h_A);
free(h_B);
free(h_dst_gpu);
free(h_dst_cpu);
printf("\nDone\n");
return 0;
}
/////////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////// MATRIX IMPLEMENTATIONS ////////////////////////////////////////
float float_rand(float min, float max)
{
float f = (float)random()/RAND_MAX;
return min + f * (max - min);
}
float* matrix_create(int len)
{
float* arr;
if(len > 0)
{
arr = (float*) calloc(len*len, sizeof(float));
if(!arr)
{
printf("\n\tFailed to allocate array\n");
return NULL;
}
}
else return NULL;
return arr;
}
int matrix_init(float* mat, int len)
{
int len_sq, i;
if(len > 0)
{
len_sq = len * len;
for (i = 0; i < len_sq; i++)
{
mat[i] = float_rand(MINVAL, MAXVAL);
}
return 1;
}
printf("\nError in initializing matrix\n");
return 0;
}
int matrix_zero(float* mat, int len)
{
int len_sq, i;
if(len > 0)
{
len_sq = len * len;
for(i = 0; i < len_sq; i++)
{
mat[i] = 0;
}
return 1;
}
printf("\nFailed to zero matrix\n");
return 0;
}
int matrix_copy(float* src, float* dst, int len)
{
int len_sq, i;
if(len > 0)
{
len_sq = len * len;
for(i = 0; i < len_sq; i++)
{
dst[i] = src[i];
}
return 1;
}
printf("\nFailed to copy matrix\n");
return 0;
}
void MMM_CPU(float* A, float* B, float* dst, int len)
{
int i, j, k;
for (i = 0; i < len; i++)
{
for(j = 0; j < len; j++)
{
for(k = 0; k < len; k++)
dst[i * len + j] += A[i * len + k] * B[k * len + j];
}
}
}
///////////////////////////// Timing related ///////////////////////////////
double ts_ms(struct timespec ts)
{
return ((((double)(ts.tv_sec))*1.0e9) + ((double)(ts.tv_nsec)))/(1.0e6);
}
/* ---------------------------------------------------------------------------
| Make the CPU busy, and measure CPS (cycles per second).
|
| Explanation:
| If tests are very fast, they can run so quickly that the SpeedStep control
| (in kernel and/or on-chip) doesn't notice in time, and the first few tests
| might finish while the CPU is still in its sleep state (about 800 MHz,
| judging from my measurements)
| A simple way to get around this is to run some kind of busy-loop that
| forces the OS and/or CPU to notice it needs to go to full clock speed.
| We print out the results of the computation so the loop won't get optimised
| away.
|
| Copy this code into other programs as desired. It provides three entry
| points:
|
| double ts_sec(ts): converts a timespec into seconds
| timespec ts_diff(ts1, ts2): computes interval between two timespecs
| measure_cps(): Does the busy loop and prints out measured CPS (cycles/sec)
--------------------------------------------------------------------------- */
struct timespec ts_diff(struct timespec start, struct timespec end)
{
struct timespec temp;
if ((end.tv_nsec-start.tv_nsec)<0) {
temp.tv_sec = end.tv_sec-start.tv_sec-1;
temp.tv_nsec = 1000000000+end.tv_nsec-start.tv_nsec;
} else {
temp.tv_sec = end.tv_sec-start.tv_sec;
temp.tv_nsec = end.tv_nsec-start.tv_nsec;
}
return temp;
}
double measure_cps()
{
struct timespec cal_start, cal_end;
mcps_tctr tsc_start, tsc_end;
double total_time;
double total_cycles;
/* We perform a chaotic iteration and print the result, to defeat
compiler optimisation */
double chaosC = -1.8464323952913974; double z = 0.0;
long int i, ilim, j;
/* Do it twice and throw away results from the first time; this ensures the
* OS and CPU will notice it's busy and set the clock speed. */
for(j=0; j<2; j++) {
clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &cal_start);
MCPS_RDTSC(tsc_start);
ilim = 50*1000*1000;
for (i=0; i<ilim; i++)
z = z * z + chaosC;
clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &cal_end);
MCPS_RDTSC(tsc_end);
}
total_time = ts_ms(ts_diff(cal_start, cal_end));
total_cycles = (double)(tsc_end.int64-tsc_start.int64);
CPS = total_cycles / total_time;
printf("z == %f, CPS == %g\n", z, CPS);
return CPS;
}
/* ---------------------------------------------------------------------------
| End of measure_cps code
--------------------------------------------------------------------------- */
struct timespec diff(struct timespec start, struct timespec end)
{
struct timespec temp;
if ((end.tv_nsec-start.tv_nsec)<0) {
temp.tv_sec = end.tv_sec-start.tv_sec-1;
temp.tv_nsec = 1000000000+end.tv_nsec-start.tv_nsec;
} else {
temp.tv_sec = end.tv_sec-start.tv_sec;
temp.tv_nsec = end.tv_nsec-start.tv_nsec;
}
return temp;
}
|
9,761 | #include <stdio.h>
#include <sys/time.h>
/*
This file can be downloaded from supercomputingblog.com.
This is part of a series of tutorials that demonstrate how to use CUDA
The tutorials will also demonstrate the speed of using CUDA
*/
// IMPORTANT NOTE: for this data size, your graphics card should have at least 512 megabytes of memory.
// If your GPU has less memory, then you will need to decrease this data size.
#define MAX_DATA_SIZE 1024*1024*32 // about 32 million elements.
// The max data size must be an integer multiple of 128*256, because each block will have 256 threads,
// and the block grid width will be 128. These are arbitrary numbers I choose.
void get_walltime(double* wcTime) {
struct timeval tp;
gettimeofday(&tp, NULL);
*wcTime = (double)(tp.tv_sec + tp.tv_usec/1000000.0);
}
double myDiffTime(struct timeval &start, struct timeval &end)
{
double d_start, d_end;
d_start = (double)(start.tv_sec + start.tv_usec/1000000.0);
d_end = (double)(end.tv_sec + end.tv_usec/1000000.0);
return (d_end - d_start);
}
void GoldenBrick(float *pA, float *pB, float *pResult, int count)
{
for (int i=0; i < count; i++)
{
//pResult[count] = pA[count] * pB[count];
//pResult[count] = pA[count] * pB[count] / 12.34567;
//pResult[count] = sqrt(pA[count] * pB[count] / 12.34567);
pResult[count] = sqrt(pA[count] * pB[count] / 12.34567) * sin(pA[count]);
}
}
__global__ void multiplyNumbersGPU(float *pDataA, float *pDataB, float *pResult)
{
// Because of the simplicity of this tutorial, we are going to assume that
// every block has 256 threads. Each thread simply multiplies two numbers,
// and then stores the result.
// The grid of blocks is 128 blocks long.
int tid = (blockIdx.y * 128 * 256) + blockIdx.x * 256 + threadIdx.x; // This gives every thread a unique ID.
// By no coincidence, we'll be using this thread ID to determine which data elements to multiply.
//pResult[tid] = pDataA[tid] * pDataB[tid]; // Each thread only multiplies one data element.
//pResult[tid] = pDataA[tid] * pDataB[tid] / 12.34567;
//pResult[tid] = sqrt(pDataA[tid] * pDataB[tid] / 12.34567);
pResult[tid] = sqrt(pDataA[tid] * pDataB[tid] / 12.34567) * sin(pDataA[tid]);
}
////////////////////////////////////////////////////////////////////////////////
// Main program
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv){
float *h_dataA, *h_dataB, *h_resultC;
float *d_dataA, *d_dataB, *d_resultC;
double gpuTime;
int i;
timeval start, end;
printf("Initializing data...\n");
h_dataA = (float *)malloc(sizeof(float) * MAX_DATA_SIZE);
h_dataB = (float *)malloc(sizeof(float) * MAX_DATA_SIZE);
h_resultC = (float *)malloc(sizeof(float) * MAX_DATA_SIZE);
cudaMalloc( (void **)&d_dataA, sizeof(float) * MAX_DATA_SIZE) ;
cudaMalloc( (void **)&d_dataB, sizeof(float) * MAX_DATA_SIZE) ;
cudaMalloc( (void **)&d_resultC , sizeof(float) * MAX_DATA_SIZE) ;
srand(123);
for(i = 0; i < MAX_DATA_SIZE; i++)
{
h_dataA[i] = (float)rand() / (float)RAND_MAX;
h_dataB[i] = (float)rand() / (float)RAND_MAX;
}
int firstRun = 1; // Indicates if it's the first execution of the for loop
const int useGPU = 1; // When 0, only the CPU is used. When 1, only the GPU is used
for (int dataAmount = MAX_DATA_SIZE; dataAmount > 128*256; dataAmount /= 2)
{
int blockGridWidth = 128;
int blockGridHeight = (dataAmount / 256) / blockGridWidth;
dim3 blockGridRows(blockGridWidth, blockGridHeight);
dim3 threadBlockRows(256, 1);
// Start the timer.
// We want to measure copying data, running the kernel, and copying the results back to host
gettimeofday(&start, NULL);
if (useGPU == 0)
{
// Copy the data to the device
cudaMemcpy(d_dataA, h_dataA, sizeof(float) * dataAmount, cudaMemcpyHostToDevice) ;
cudaMemcpy(d_dataB, h_dataB, sizeof(float) * dataAmount, cudaMemcpyHostToDevice) ;
// Do the multiplication on the GPU
multiplyNumbersGPU<<<blockGridRows, threadBlockRows>>>(d_dataA, d_dataB, d_resultC);
cudaThreadSynchronize() ;
// Copy the data back to the host
cudaMemcpy(h_resultC, d_resultC, sizeof(float) * dataAmount, cudaMemcpyDeviceToHost) ;
}
else
{
// We're using the CPU only
GoldenBrick(h_dataA, h_dataB, h_resultC, dataAmount);
}
// Stop the timer, print the total round trip execution time.
gettimeofday(&end, NULL);
gpuTime = myDiffTime(start, end);
if (!firstRun || !useGPU)
{
printf("Elements: %d - convolution time : %f msec - %f Multiplications/sec\n", dataAmount, gpuTime, blockGridHeight * 128 * 256 / (gpuTime * 0.001));
}
else
{
firstRun = 0;
// We discard the results of the first run because of the extra overhead incurred
// during the first time a kernel is ever executed.
dataAmount *= 2; // reset to first run value
}
}
printf("Cleaning up...\n");
cudaFree(d_resultC ) ;
cudaFree(d_dataB) ;
cudaFree(d_dataA) ;
free(h_resultC);
free(h_dataB);
free(h_dataA);
}
|
9,762 | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
__device__ double constrain_d_gpu(double val, double min, double max)
{
double tmp = val;
if (tmp <= min) tmp = min; if (tmp >= max) tmp = max;
return tmp;
}
__device__ float constrain_f_gpu(float val, float min, float max)
{
float tmp = val;
if (tmp <= min) tmp = min; if (tmp >= max) tmp = max;
return tmp;
}
__device__ int constrain_i_gpu(int val, int min, int max)
{
int tmp = val;
if (tmp <= min) tmp = min; if (tmp >= max) tmp = max;
return tmp;
} |
9,763 | /*
#ifndef __CUDACC__
#define __CUDACC__
#endif
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include<stdio.h>
#include<conio.h>
__global__ void sessional(char *d_name[])
{
printf("\n %s",d_name);
unsigned int t=threadIdx.x;
char *alpha[26];
char lol='d';
for(int i=0;i<23;i++)
alpha[i]=lol++;
alpha[23]='a';
alpha[24]='b';
alpha[25]='c';
for(int i=0; d_name[i]!='\0'; i++)
{
for(char j='a';j<='z';j++)
if(&d_name[i]==j)
d_name[i]=alpha[j];
printf("%c",d_name[i]);
}
}
int main()
{
char *h_name="sakshi",*d_name[6];
int length=0;
for(int i=0;h_name[i]!='\0';i++)
length++;
int size = length*sizeof(char);
cudaMalloc((void**)&h_name, size);
cudaMemcpy(d_name,h_name, size, cudaMemcpyHostToDevice);
sessional<<<1, length>>>(d_name);
cudaMemcpy(h_name, d_name, size, cudaMemcpyDeviceToHost);
printf("\n %s",h_name);
getch();
return 0;
}*/ |
9,764 | /* Copyright (c) 2021-2023, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include <cassert>
#define checkCudaErrors(Code) assert((Code) == cudaSuccess)
#define checkCudaLaunch(...) checkCudaErrors((__VA_ARGS__, cudaPeekAtLastError()))
static constexpr int NumThreads = 32;
static constexpr int NumBlocks = 2;
__global__
void vectorAdd(int *v)
{
int tx = threadIdx.x + blockDim.x * blockIdx.x;
v[tx] += tx;
}
int main()
{
int *d_vec = nullptr;
checkCudaErrors(cudaMalloc((void**)&d_vec, sizeof(int) * NumBlocks * NumThreads));
// Size is missing `* sizeof(int)`
checkCudaErrors(cudaMemset(d_vec, 0, NumBlocks * NumThreads));
checkCudaLaunch(vectorAdd<<<NumBlocks, NumThreads>>>(d_vec));
checkCudaErrors(cudaDeviceSynchronize());
checkCudaErrors(cudaFree(d_vec));
return 0;
}
|
9,765 | // info.cu
#include <cuda_runtime.h>
#include <iostream>
int main() {
int count;
cudaDeviceProp prop;
cudaGetDeviceCount(&count);
std::cout << "devices count : " << count << std::endl;
cudaGetDeviceProperties(&prop, 0);
std::cout << "max block size : " << prop.maxGridSize[0] << ' '
<< prop.maxGridSize[1] << ' ' << prop.maxGridSize[2] << std::endl;
std::cout << "max thread size : " << prop.maxThreadsDim[0] << ' '
<< prop.maxThreadsDim[1] << ' ' << prop.maxThreadsDim[2]
<< std::endl;
return EXIT_SUCCESS;
}
|
9,766 |
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#define SOFTENING 1e-9f
// 使用cuda runtime API cudaOccupancyMaxPotentialBlockSize 来获取使得设备利用率最大的 blockSize
// API说明: Returns numBlocks and block size that achieves maximum potential occupancy for a device function.
#define BLOCKSIZE 768
/*
* Each body contains x, y, and z coordinate positions,
* as well as velocities in the x, y, and z directions.
*/
typedef struct
{
float x, y, z, vx, vy, vz;
} Body;
/*
* Do not modify this function. A constraint of this exercise is
* that it remain a host function.
*/
void randomizeBodies(float* data, int n)
{
for (int i = 0; i < n; i++)
{
data[i] = 2.0f * (rand() / (float)RAND_MAX) - 1.0f;
}
}
// 将body之间力的计算写成一个可供GPU调用的函数，方便对一个block中的循环进行展开从而得到优化
__device__ void bodyInteraction(float3& body, float3& body2, float3& F)
{
float dx = body.x - body2.x;
float dy = body.y - body2.y;
float dz = body.z - body2.z;
float distSqr = dx * dx + dy * dy + dz * dz + SOFTENING;
float invDist = rsqrtf(distSqr);
float invDist3 = invDist * invDist * invDist;
F.x += dx * invDist3;
F.y += dy * invDist3;
F.z += dz * invDist3;
}
/*
* This function calculates the gravitational impact of all bodies in the system
* on all others, but does not update their positions.
*/
// 思路：一个线程计算一个body
__global__ void bodyForce(Body* p, float dt, int nbodies)
{
int i = blockIdx.x * blockDim.x + threadIdx.x; // 计算线程位置，对应到数组的下标
int tx = threadIdx.x; // 线程位于块中的位置
__shared__ float3 pShare[BLOCKSIZE]; // 使用shared_memory, 将数据载入shared_memory, 提升读写性能，每个块中线程共同访问shared memory
if (i < nbodies)
{
float3 F = make_float3(0.0f, 0.0f, 0.0f); // 原Fx, Fy, Fz
float3 pCur = make_float3(p[i].x, p[i].y, p[i].z); // 将有用数据放入寄存器
// 将计算分为几个block进行，每个block的线程都进行gridDim.x(nbodies / blockDim.x)次循环，计算完一个body
for (int block = 0; block < gridDim.x; ++block)
{
// 由于Body中仅仅有x,y,z是对下面计算有用的数据，因此仅读取Body中的x,y,z数据，减少shared memory的空间浪费
Body temp = p[block * BLOCKSIZE + tx];
pShare[tx] = make_float3(temp.x, temp.y, temp.z); // 多个线程读取到shared memory
__syncthreads(); // 块内同步，防止数据未读取完就进入下一步
// 进行一个block循环BLOCKSIZE次计算，本次计算后，将会重新载入shared memory，进入下一个循环运算，直到运算完nbodies次
// 编译期参数，循环展开用
#pragma unroll
for (int j = 0; j < BLOCKSIZE; j++)
{
// 循环展开 计算body间力
bodyInteraction(pShare[j], pCur, F); ++j;
bodyInteraction(pShare[j], pCur, F); ++j;
bodyInteraction(pShare[j], pCur, F); ++j;
bodyInteraction(pShare[j], pCur, F); ++j;
}
__syncthreads(); // 块内同步，防止在部分线程未运算结束的情况下重载shared memory
// 原子加操作
atomicAdd(&p[i].vx, dt * F.x);
atomicAdd(&p[i].vy, dt * F.y);
atomicAdd(&p[i].vz, dt * F.z);
}
}
}
// 将原串行代码的每个循环分配到每个线程
__global__ void integratePosition(Body* p, float dt, int nbodies)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < nbodies)
{
p[i].x += p[i].vx * dt;
p[i].y += p[i].vy * dt;
p[i].z += p[i].vz * dt;
}
}
int main(const int argc, const char** argv)
{
/*
* Do not change the value for `nBodies` here. If you would like to modify it,
* pass values into the command line.
*/
int nBodies = 2 << 11;
int salt = 0;
if (argc > 1)
nBodies = 2 << atoi(argv[1]);
/*
* This salt is for assessment reasons. Tampering with it will result in automatic failure.
*/
if (argc > 2)
salt = atoi(argv[2]);
const float dt = 0.01f; // time step
const int nIters = 10; // simulation iterations
int bytes = nBodies * sizeof(Body);
float* buf;
cudaMallocManaged(&buf, bytes);
Body* p = (Body*)buf;
int numBlocks = (nBodies + BLOCKSIZE - 1) / BLOCKSIZE;
/*
* As a constraint of this exercise, `randomizeBodies` must remain a host function.
*/
randomizeBodies(buf, 6 * nBodies); // Init pos / vel data
double totalTime = 0.0;
/*
* This simulation will run for 10 cycles of time, calculating gravitational
* interaction amongst bodies, and adjusting their positions to reflect.
*/
/*******************************************************************/
// Do not modify this line of code.
for (int iter = 0; iter < nIters; iter++)
{
/*******************************************************************/
/*
* You will likely wish to refactor the work being done in `bodyForce`,
* as well as the work to integrate the positions.
*/
bodyForce <<<numBlocks, BLOCKSIZE>>> (p, dt, nBodies); // compute interbody forces
/*
* This position integration cannot occur until this round of `bodyForce` has completed.
* Also, the next round of `bodyForce` cannot begin until the integration is complete.
*/
integratePosition <<<numBlocks, BLOCKSIZE>>> (p, dt, nBodies);
cudaFree(buf);
}
} |
9,767 | extern "C" __global__ void kNMLLinearMinimize1_kernel( int numAtoms, int paddedNumAtoms, int numModes, float4 *velm, long long *force, float4 *modes, float *modeWeights ) {
extern __shared__ float dotBuffer[];
for( int mode = blockIdx.x; mode < numModes; mode += gridDim.x ) {
/* Compute the projection of the mass weighted force onto one normal mode vector.*/
float dot = 0.0f;
for( int atom = threadIdx.x; atom < numAtoms; atom += blockDim.x ) {
const float scale = sqrt( velm[atom].w );
const int modePos = mode * numAtoms + atom;
float fx = ( float )force[atom] / ( float )0x100000000;
float fy = ( float )force[atom + 1 * paddedNumAtoms] / ( float )0x100000000;
float fz = ( float )force[atom + 2 * paddedNumAtoms] / ( float )0x100000000;
float4 m = modes[modePos];
dot += scale * ( fx * m.x + fy * m.y + fz * m.z );
}
dotBuffer[threadIdx.x] = dot;
__syncthreads();
if( threadIdx.x == 0 ) {
float sum = 0;
for( int i = 0; i < blockDim.x; i++ ) {
sum += dotBuffer[i];
}
modeWeights[mode] = sum;
}
}
}
extern "C" __global__ void kNMLLinearMinimize2_kernel( int numAtoms, int paddedNumAtoms, int numModes, float invMaxEigen, float4 *posq, float4 *posqP, float4 *velm, long long *force, float4 *modes, float *modeWeights ) {
/* Load the weights into shared memory.*/
extern __shared__ float weightBuffer[];
for( int mode = threadIdx.x; mode < numModes; mode += blockDim.x ) {
weightBuffer[mode] = modeWeights[mode];
}
__syncthreads();
/* Compute the projected forces and update the atom positions.*/
for( int atom = threadIdx.x + blockIdx.x * blockDim.x; atom < numAtoms; atom += blockDim.x * gridDim.x ) {
const float invMass = velm[atom].w, sqrtInvMass = sqrt( invMass ), factor = invMass * invMaxEigen;
float3 f = make_float3( 0.0f, 0.0f, 0.0f );
for( int mode = 0; mode < numModes; mode++ ) {
float4 m = modes[mode * numAtoms + atom];
float weight = weightBuffer[mode];
f.x += m.x * weight;
f.y += m.y * weight;
f.z += m.z * weight;
}
f.x *= sqrtInvMass;
f.y *= sqrtInvMass;
f.z *= sqrtInvMass;
posqP[atom] = make_float4( ( float )force[atom] / ( float )0x100000000 - f.x, ( float )force[atom + paddedNumAtoms] / ( float ) 0x100000000 - f.y, ( float ) force[atom + 2 * paddedNumAtoms] / ( float ) 0x100000000 - f.z, 0.0f );
float4 pos = posq[atom];
pos.x += factor * posqP[atom].x;
pos.y += factor * posqP[atom].y;
pos.z += factor * posqP[atom].z;
posq[atom] = pos;
}
}
|
9,768 | #include <iostream>
#include <fstream>
#include <stdlib.h>
#include <cstring>
#include <limits> // radi definiranja beskonačnosti
#include <ctime> // radi mjerenja vremena izvršavanja
#include <cmath> // radi "strop" funkcije
using namespace std;
/* Definiramo beskonačnost kao najveći mogući integer broj. */
#define infty std::numeric_limits<int>::max()
void printMatrix (int* G, unsigned int dim) {
cout << "\r\n";
for (int i = 0; i < dim*dim; i++) {
if (G[i] < infty) {
cout << G[i] << "\t";
}
else {
cout << "∞" << "\t";
}
/* Ako je ispisao sve za jedan vrh, prijeđi na sljedeći u novi redak. */
if ((i+1)%dim == 0) {
cout << "\r\n";
}
}
}
/* Kernel za device koji implementira prvu fazu blocked Floyd-Warshall algoritma. */
__global__ void FW_Cuda_Phase1(int B, int* D, int* PI, int dim, int primaryBlockDim) {
extern __shared__ int shrd[];
int* sh_D = &shrd[0];
int* sh_PI = &shrd[primaryBlockDim*primaryBlockDim];
int i = B*primaryBlockDim + threadIdx.y;
int j = B*primaryBlockDim + threadIdx.x;
int sub_dim = primaryBlockDim;
int sub_i = threadIdx.y;
int sub_j = threadIdx.x;
__syncthreads();
if (sub_i < sub_dim && sub_j < sub_dim && sub_i*sub_dim+sub_j < sub_dim*sub_dim && i < max(sub_dim, dim) && j < max(sub_dim, dim)) {
sh_D[sub_i*sub_dim+sub_j] = D[i*dim+j];
sh_PI[sub_i*sub_dim+sub_j] = PI[i*dim+j];
}
else {
sh_D[sub_i*sub_dim+sub_j] = INT_MAX;
sh_PI[sub_i*sub_dim+sub_j] = -1;
}
__syncthreads();
for (int sub_k = 0; sub_k < min(sub_dim, dim); sub_k++) {
__syncthreads();
if (i < max(sub_dim, dim) && j < max(sub_dim, dim) && sh_D[sub_i*sub_dim+sub_k] < INT_MAX && sh_D[sub_k*sub_dim+sub_j] < INT_MAX) {
if (sh_D[sub_i*sub_dim+sub_j] > sh_D[sub_i*sub_dim+sub_k] + sh_D[sub_k*sub_dim+sub_j]) {
sh_D[sub_i*sub_dim+sub_j] = sh_D[sub_i*sub_dim+sub_k] + sh_D[sub_k*sub_dim+sub_j];
sh_PI[sub_i*sub_dim+sub_j] = sh_PI[sub_k*sub_dim+sub_j];
}
}
}
__syncthreads();
if (sub_i < min(sub_dim, dim) && sub_j < min(sub_dim, dim) && sub_i*sub_dim+sub_j < sub_dim*sub_dim && i < max(sub_dim, dim) && j < max(sub_dim, dim)) {
D[i*dim+j] = sh_D[sub_i*sub_dim+sub_j];
PI[i*dim+j] = sh_PI[sub_i*sub_dim+sub_j];
}
}
/* Kernel za device koji implementira drugu fazu blocked Floyd-Warshall algoritma. */
__global__ void FW_Cuda_Phase2(int B, int* D, int* PI, int dim, int primaryBlockDim) {
extern __shared__ int shrd[];
/* Sve varijable koje imaju prefiks "p_" pripadaju primarnom podbloku, sve koje imaju "c_" pripadaju trenutnom bloku. */
int* p_sh_D = &shrd[0];
int* p_sh_PI = &shrd[primaryBlockDim*primaryBlockDim];
int* c_sh_D = &shrd[2*primaryBlockDim*primaryBlockDim];
int* c_sh_PI = &shrd[3*primaryBlockDim*primaryBlockDim];
int p_i = B*primaryBlockDim + threadIdx.y;
int p_j = B*primaryBlockDim + threadIdx.x;
/* Ako je trenutni blok prije primarnog, skipCenterBlock biti će 0.
Inače, ako je primarni ili neki nakon njega, biti će 1. */
int skipCenterBlock = min((blockIdx.x+1)/(B+1), 1);
int c_i, c_j;
/* Ako je y koordinata bloka u gridu jednaka 0, onda on pripada istom retku kao i primarni blok.
Ako je y koordinata bloka u gridu jednaka 1, pripada istom stupcu kao i primarni blok. */
if (blockIdx.y == 0) {
c_i = p_i;
c_j = (blockIdx.x+skipCenterBlock)*primaryBlockDim + threadIdx.x;
}
else {
c_i = (blockIdx.x+skipCenterBlock)*primaryBlockDim + threadIdx.y;
c_j = p_j;
}
int sub_dim = primaryBlockDim;
int sub_i = threadIdx.y;
int sub_j = threadIdx.x;
__syncthreads();
p_sh_D[sub_i*sub_dim+sub_j] = D[p_i*dim+p_j];
p_sh_PI[sub_i*sub_dim+sub_j] = PI[p_i*dim+p_j];
if (sub_i < sub_dim && sub_j < sub_dim && sub_i*sub_dim+sub_j < sub_dim*sub_dim && c_i < max(sub_dim, dim) && c_j < max(sub_dim, dim)) {
c_sh_D[sub_i*sub_dim+sub_j] = D[c_i*dim+c_j];
c_sh_PI[sub_i*sub_dim+sub_j] = PI[c_i*dim+c_j];
}
else {
c_sh_D[sub_i*sub_dim+sub_j] = INT_MAX;
c_sh_PI[sub_i*sub_dim+sub_j] = -1;
}
__syncthreads();
for (int sub_k = 0; sub_k < min(sub_dim, dim); sub_k++) {
__syncthreads();
/* Pripada istom stupcu kao i primarni blok. */
if (blockIdx.y == 1) {
if (c_i < max(sub_dim, dim) && c_j < max(sub_dim, dim) && c_sh_D[sub_i*sub_dim+sub_k] < INT_MAX && p_sh_D[sub_k*sub_dim+sub_j] < INT_MAX) {
if (c_sh_D[sub_i*sub_dim+sub_j] > c_sh_D[sub_i*sub_dim+sub_k] + p_sh_D[sub_k*sub_dim+sub_j]) {
c_sh_D[sub_i*sub_dim+sub_j] = c_sh_D[sub_i*sub_dim+sub_k] + p_sh_D[sub_k*sub_dim+sub_j];
c_sh_PI[sub_i*sub_dim+sub_j] = p_sh_PI[sub_k*sub_dim+sub_j];
}
}
}
/* Pripada istom retku kao i primarni blok. */
if (blockIdx.y == 0) {
if (c_i < max(sub_dim, dim) && c_j < max(sub_dim, dim) && p_sh_D[sub_i*sub_dim+sub_k] < INT_MAX && c_sh_D[sub_k*sub_dim+sub_j] < INT_MAX) {
if (c_sh_D[sub_i*sub_dim+sub_j] > p_sh_D[sub_i*sub_dim+sub_k] + c_sh_D[sub_k*sub_dim+sub_j]) {
c_sh_D[sub_i*sub_dim+sub_j] = p_sh_D[sub_i*sub_dim+sub_k] + c_sh_D[sub_k*sub_dim+sub_j];
c_sh_PI[sub_i*sub_dim+sub_j] = c_sh_PI[sub_k*sub_dim+sub_j];
}
}
}
__syncthreads();
}
__syncthreads();
if (sub_i < min(sub_dim, dim) && sub_j < min(sub_dim, dim) && sub_i*sub_dim+sub_j < sub_dim*sub_dim && c_i < max(sub_dim, dim) && c_j < max(sub_dim, dim)) {
D[c_i*dim+c_j] = c_sh_D[sub_i*sub_dim+sub_j];
PI[c_i*dim+c_j] = c_sh_PI[sub_i*sub_dim+sub_j];
}
}
/* Kernel za device koji implementira treću fazu blocked Floyd-Warshall algoritma. */
__global__ void FW_Cuda_Phase3(int B, int* D, int* PI, int dim, int primaryBlockDim) {
extern __shared__ int shrd[];
/* Sve varijable koje imaju prefiks "p1_" pripadaju primarnom podbloku 1 izračunatom u fazi 2,
sve koje imaju prefiks "p2_" pripadaju primarnom podbloku 2 izračunatom u fazi 2,
a sve koje imaju "c_" pripadaju trenutnom bloku. */
int* p1_sh_D = &shrd[0];
int* p1_sh_PI = &shrd[primaryBlockDim*primaryBlockDim];
int* p2_sh_D = &shrd[2*primaryBlockDim*primaryBlockDim];
int* p2_sh_PI = &shrd[3*primaryBlockDim*primaryBlockDim];
int* c_sh_D = &shrd[4*primaryBlockDim*primaryBlockDim];
int* c_sh_PI = &shrd[5*primaryBlockDim*primaryBlockDim];
/* Ako je trenutni blok prije primarnog, skipCenterBlock biti će 0.
Inače, ako je primarni ili neki nakon njega, biti će 1. U ovoj fazi to radimo po obje osi. */
int skipCenterBlockX = min((blockIdx.x+1)/(B+1), 1);
int skipCenterBlockY = min((blockIdx.y+1)/(B+1), 1);
int c_i = (blockIdx.y+skipCenterBlockY)*primaryBlockDim + threadIdx.y;
int c_j = (blockIdx.x+skipCenterBlockX)*primaryBlockDim + threadIdx.x;
int p1_i = c_i;
int p1_j = B*primaryBlockDim + threadIdx.x;
int p2_i = B*primaryBlockDim + threadIdx.y;
int p2_j = c_j;
int sub_dim = primaryBlockDim;
int sub_i = threadIdx.y;
int sub_j = threadIdx.x;
__syncthreads();
p1_sh_D[sub_i*sub_dim+sub_j] = D[p1_i*dim+p1_j];
p1_sh_PI[sub_i*sub_dim+sub_j] = PI[p1_i*dim+p1_j];
p2_sh_D[sub_i*sub_dim+sub_j] = D[p2_i*dim+p2_j];
p2_sh_PI[sub_i*sub_dim+sub_j] = PI[p2_i*dim+p2_j];
if (sub_i < sub_dim && sub_j < sub_dim && sub_i*sub_dim+sub_j < sub_dim*sub_dim && c_i < dim && c_j < dim) {
c_sh_D[sub_i*sub_dim+sub_j] = D[c_i*dim+c_j];
c_sh_PI[sub_i*sub_dim+sub_j] = PI[c_i*dim+c_j];
}
else {
c_sh_D[sub_i*sub_dim+sub_j] = INT_MAX;
c_sh_PI[sub_i*sub_dim+sub_j] = -1;
}
__syncthreads();
for (int sub_k = 0; sub_k < min(sub_dim, dim); sub_k++) {
__syncthreads();
if (c_i < max(sub_dim, dim) && c_j < max(sub_dim, dim) && p1_sh_D[sub_i*sub_dim+sub_k] < INT_MAX && p2_sh_D[sub_k*sub_dim+sub_j] < INT_MAX) {
if (c_sh_D[sub_i*sub_dim+sub_j] > p1_sh_D[sub_i*sub_dim+sub_k] + p2_sh_D[sub_k*sub_dim+sub_j]) {
c_sh_D[sub_i*sub_dim+sub_j] = p1_sh_D[sub_i*sub_dim+sub_k] + p2_sh_D[sub_k*sub_dim+sub_j];
c_sh_PI[sub_i*sub_dim+sub_j] = p2_sh_PI[sub_k*sub_dim+sub_j];
}
}
__syncthreads();
}
__syncthreads();
if (sub_i < min(sub_dim, dim) && sub_j < min(sub_dim, dim) && sub_i*sub_dim+sub_j < sub_dim*sub_dim && c_i < max(sub_dim, dim) && c_j < max(sub_dim, dim)) {
D[c_i*dim+c_j] = c_sh_D[sub_i*sub_dim+sub_j];
PI[c_i*dim+c_j] = c_sh_PI[sub_i*sub_dim+sub_j];
}
}
void Blocked_Floyd_Warshall_Cuda (int* W, int* D, int* PI, unsigned int dim) {
unsigned int n = dim*dim;
/* Error varijabla za handleanje CUDA errora. */
cudaError_t err = cudaSuccess;
/* Alociranje device varijabli matrica D i PI. */
int* d_D = NULL;
err = cudaMalloc((void**) &d_D, n*sizeof(int));
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno alociranje matrice D (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
int* d_PI = NULL;
err = cudaMalloc((void**) &d_PI, n*sizeof(int));
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno alociranje matrice PI (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
/* Kopiranje podataka iz host matrica u device. */
err = cudaMemcpy(d_D, D, n*sizeof(int), cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno kopiranje matrice D iz hosta u device (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaMemcpy(d_PI, PI, n*sizeof(int), cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno kopiranje matrice PI iz hosta u device (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
/* Pozivanje CUDA kernela. */
int blockDim = 25; /* Ukoliko je dimenzija bloka 32, imamo 1024 threadova po bloku.
U blocked verziji Floyd-Warshall algoritma ovaj broj ovisi o tome koliko
threadova se može pokrenuti u jednom bloku na nekoj grafičkoj kartici,
ali i o tome koliko shared memorije po multiprocesoru ima dotična grafička kartica.
Konkretno, za Teslu C2050/C2070 na kakvoj je rađen ovaj rad, maksimalno je
1024 threada po bloku, te je maksimalna shareana memorija multiprocesora 48kb,
što bi značilo da možemo spremiti 4096 int elementa (jer u fazi 3 nam trebaju 3 bloka
pa zapravo imamo 16kb po bloku za spremanje integera). Kako moramo gledati broj koji je
manji (između 1024 zbog threadova/bloku i 4096 zbog shareane memorije), algoritam ćemo
pokretati tako da je jedan blok veličine najviše 32*32, pri čemu se za veličinu bloka
uzima prvi broj manji ili jednak broju 32 s kojim je dijeljiv broj vrhova grafa. */
int numberOfBlocks = ceil((float)dim/(float)blockDim); /* Broj (primarnih) blokova u blocked Floyd-Warshall algoritmu. */
cout << "Blocked Floyd-Warshall algoritam se pokreće sa " << numberOfBlocks << " primarna bloka po dijagonali.\r\n";
cout << "CUDA kerneli se pokreću kako slijedi: \r\n \t Faza 1: grid dimenzije 1x1 \r\n";
cout << "\t Faza 2: grid dimenzije " << numberOfBlocks-1 << "x2";
if (numberOfBlocks-1 == 0) cout << " (Faza 2 se neće izvršiti zbog dimenzija grida)";
cout << "\r\n";
cout << "\t Faza 3: grid dimenzije " << numberOfBlocks-1 << "x" << numberOfBlocks-1;
if (numberOfBlocks-1 == 0) cout << " (Faza 3 se neće izvršiti zbog dimenzija grida)";
cout << "\r\n";
cout << "Svi blokovi se pokreću s " << blockDim*blockDim << " threada po bloku.\r\n";
/* Iteriranje po blokovima radimo na CPU, ostalo paraleliziramo. */
for (int B = 0; B < numberOfBlocks; B++) {
/* Veličina shared memorije je blockDim*blockDim za matricu D i za matricu PI. */
FW_Cuda_Phase1<<<dim3(1, 1, 1), dim3(blockDim, blockDim, 1), 2*blockDim*blockDim*sizeof(int)>>> (B, d_D, d_PI, dim, blockDim);
err = cudaGetLastError();
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno pokrenuta kernel metoda FW_Cuda_Phase1 (error code %s)!\n", cudaGetErrorString(err));
cout << "\r\n B = " << B << "\r\n";
exit(EXIT_FAILURE);
}
cudaThreadSynchronize();
/* Veličina shared memorije je blockDim*blockDim za primarnu matricu D, trenutnu matricu D, primarnu i trenutnu za matricu PI. */
if (numberOfBlocks-1 > 0) {
FW_Cuda_Phase2<<<dim3(numberOfBlocks-1, 2, 1), dim3(blockDim, blockDim, 1), 4*blockDim*blockDim*sizeof(int)>>> (B, d_D, d_PI, dim, blockDim);
err = cudaGetLastError();
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno pokrenuta kernel metoda FW_Cuda_Phase2 (error code %s)!\n", cudaGetErrorString(err));
cout << "\r\n B = " << B << "\r\n";
exit(EXIT_FAILURE);
}
}
cudaThreadSynchronize();
/* Veličina shared memorije je blockDim*blockDim za trenutnu matricu D, dvije primarne matrice D izračunate u fazi 2,
te za pripadne matrice PI. */
if (numberOfBlocks-1 > 0) {
FW_Cuda_Phase3<<<dim3(numberOfBlocks-1, numberOfBlocks-1, 1), dim3(blockDim, blockDim, 1), 6*blockDim*blockDim*sizeof(int)>>> (B, d_D, d_PI, dim, blockDim);
err = cudaGetLastError();
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno pokrenuta kernel metoda FW_Cuda_Phase3 (error code %s)!\n", cudaGetErrorString(err));
cout << "\r\n B = " << B << "\r\n";
exit(EXIT_FAILURE);
}
}
/* Sinkronizacija threadova kako bi se završila B-ta iteracija, te kako bi se prešlo na (B+1). iteraciju. */
cudaThreadSynchronize();
}
/* Kopiranje podataka iz device matrica u host. */
err = cudaMemcpy(D, d_D, n*sizeof(int), cudaMemcpyDeviceToHost);
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno kopiranje matrice D iz devicea u host (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaMemcpy(PI, d_PI, n*sizeof(int), cudaMemcpyDeviceToHost);
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno kopiranje matrice PI iz devicea u host (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
/* Dealociranje device varijabli matrica D i PI. */
err = cudaFree(d_D);
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno dealociranje matrice D (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
err = cudaFree(d_PI);
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno dealociranje matrice PI (error code %s)!\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
/* Reset CUDA devicea i završavanje CUDA Floyd-Warshalla. */
err = cudaDeviceReset();
if (err != cudaSuccess) {
fprintf(stderr, "Neuspješno resetiranje devicea (završavanje sa CUDA FW, priprema za sljedeće pokretanje)! error=%s\n", cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
}
/* Metoda koja rekonstruira težinu najkraćeg puta za dani par vrhova koristeći matricu
prethodnika PI i matricu inicijalnih težina W. */
int getPath (int* W, int* PI, int i, int j, unsigned int dim) {
if (i == j) {
return 0;
}
else if (PI[i*dim+j] == -1) {
return infty;
}
else {
int recursivePath = getPath(W, PI, i, PI[i*dim+j], dim);
if (recursivePath < infty) {
return recursivePath + W[PI[i*dim+j]*dim+j];
}
else {
return infty;
}
}
}
/* Za svaki par vrhova pokreće getPath metodu koja rekonstruira težinu najkraćeg puta
između njih koristeći matricu prethodnika PI. Tu težinu onda uspoređuje sa dobivenom težinom
za isti par vrhova u matrici najkraćih putova D. */
bool checkSolutionCorrectness (int* W, int* D, int* PI, unsigned int dim) {
for (int i = 0; i < dim; i++) {
for (int j = 0; j < dim; j++) {
if (getPath(W, PI, i, j, dim) != D[i*dim+j]) {
return false;
}
}
}
return true;
}
int main() {
/*
V - broj vrhova
E - broj bridova
u - prvi vrh pri učitavanju grafa iz datoteke
v - drugi vrh pri učitavanju grafa iz datoteke
w - težina između v1 i v2 pri učitavanju grafa iz datoteke
*/
unsigned int V, E;
int u, v, w;
ifstream inputGraphFile; inputGraphFile.open("graphFile.txt");
ofstream outputFile; outputFile.open("output_cuda_blocked.txt");
inputGraphFile >> V >> E;
cout << "V = " << V << ", E = " << E << "\r\n";
unsigned int n = V*V;
/* Inicijalizacija grafova u memoriji. */
int* W = (int*)malloc(n*sizeof(int));
int* D = (int*)malloc(n*sizeof(int));
int* PI = (int*)malloc(n*sizeof(int));
/* Postavljanje inicijalnih vrijednosti za matricu prethodnika PI(0),
matricu težina W i matricu najkraćih putova D(0). */
fill_n(W, n, infty);
fill_n(PI, n, -1);
for (int i = 0; i < E; i++) {
inputGraphFile >> u >> v >> w;
//cout << u << " <-- " << w << " --> " << v << "\r\n";
W[u*V+v] = w;
if (u != v) {
PI[u*V+v] = u;
}
}
for (int i = 0; i < V; i++) {
W[i*V+i] = 0;
}
/* D(0) = W na početku. */
memcpy (D, W, n*sizeof(int));
// printMatrix(W, V); printMatrix(D, V); printMatrix(PI, V);
/* Početak mjerenja izvršavanja Floyd-Warshall algoritma. */
clock_t begin = clock();
/* Pozivamo Floyd-Warshall CPU algoritam nad učitanim grafom. */
Blocked_Floyd_Warshall_Cuda(W, D, PI, V);
/* Kraj mjerenja izvršavanja Floyd-Warshall algoritma. */
clock_t end = clock();
double elapsedTime = double(end - begin) / CLOCKS_PER_SEC;
//printMatrix(W, V); printMatrix(D, V); printMatrix(PI, V);
/* Ispis rezultata u datoteku. */
outputFile << "|V| = " << V << ", |E| = " << E << "\r\n\r\n";
for (int i = 0; i < n; i++) {
if (i%V==0) outputFile << "\r\n";
if (D[i] < infty)
outputFile << D[i] << "\t";
else
outputFile << "∞" << "\t";
}
outputFile << "\r\n\r\n";
for (int i = 0; i < n; i++) {
if (i%V==0) outputFile << "\r\n";
outputFile << PI[i] << "\t";
}
cout << "Vrijeme izvršavanja Blocked Floyd-Warshall algoritma: " << elapsedTime << "s.\r\n";
if (checkSolutionCorrectness(W, D, PI, V) == true)
cout << "Svi najkraći putevi su točno izračunati!\r\n";
else
cout << "Najkraći putevi nisu točno izračunati.\r\n";
inputGraphFile.close();
outputFile.close();
free(W); free(D); free(PI);
return 0;
} |
9,769 | #include "includes.h"
__global__ void shared4R20ops(float *A, float *B, float *C, const int N)
{
__shared__ float Smem[512];
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < N)
Smem[threadIdx.x] = A[i];
__syncthreads();
float x;
if (i < N) {
x = A[i]/3 + 17*B[i] - A[i]*A[i] + 3*B[i] - 4*A[i]*B[i] + B[i]*B[i]*7;
C[i] = x- 8 +Smem[(threadIdx.x+1)%512]*A[i] + 4*Smem[(threadIdx.x+2)%512]+3*B[i]*Smem[(threadIdx.x+3)%512]+A[i]*Smem[(threadIdx.x+4)%512];
}
} |
9,770 | #define d_wavefield(z,x) d_wavefield[(x)*(nz)+(z)]
// #define d_data(it,iRec) d_data[(iRec)*(nSteps)+(it)]
__global__ void recording(float *d_wavefield, int nz, float *d_data, \
int iShot, int it, int nSteps, int nrec, int *d_z_rec, int *d_x_rec) {
int iRec = threadIdx.x + blockDim.x*blockIdx.x;
if(iRec >= nrec){
return;
}
d_data[(iRec)*(nSteps)+(it)] = d_wavefield(d_z_rec[iRec], d_x_rec[iRec]);
} |
9,771 | #include "device_launch_parameters.h"
#include <cuda_runtime.h>
#include <curand_kernel.h>
#include <cuda.h>
#include <stdlib.h>
#include <stdio.h>
#define SIZE 33*1024
#define min(a, b) a > b ? b : a
const int threadperBlock = 256;
const int blocksperGrid = min(32, (SIZE + threadperBlock - 1) / threadperBlock);
__global__ void dot(float *a, float *b, float *c)
{
__shared__ float cache[threadperBlock];
int tid = threadIdx.x + blockIdx.x * blockDim.x;
int cacheIndex = threadIdx.x;
float temp = 0;
while (tid < SIZE)
{
temp += a[tid] * b[tid];
tid += blockDim.x * gridDim.x;
}
cache[cacheIndex] = temp;
__syncthreads();
int i = blockDim.x / 2;
while (i != 0)
{
if (cacheIndex < i)
cache[cacheIndex] += cache[cacheIndex + i];
__syncthreads();
i /= 2;
}
if (cacheIndex == 0)
c[blockIdx.x] = cache[0];
}
int main()
{
float *a, *b, *c_, c;
float *d_a, *d_b, *d_c_;
a = (float *)malloc(SIZE*sizeof(float));
b = (float *)malloc(SIZE*sizeof(float));
c_ = (float *)malloc(blocksperGrid*sizeof(float));
cudaMalloc(&d_a, SIZE*sizeof(float));
cudaMalloc(&d_b, SIZE*sizeof(float));
cudaMalloc(&d_c_, blocksperGrid*sizeof(float));
for (int i = 0; i < SIZE; ++i)
{
a[i] = i;
b[i] = i;
}
cudaMemcpy(d_a, a, SIZE*sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, SIZE*sizeof(float), cudaMemcpyHostToDevice);
dot<<<blocksperGrid, threadperBlock>>>(d_a, d_b, d_c_);
cudaMemcpy(c_, d_c_, blocksperGrid*sizeof(float), cudaMemcpyDeviceToHost);
c = 0;
for (int i = 0; i < blocksperGrid; i++)
{
c += c_[i];
}
printf("%.6g\n", c);
float K = 0.;
for (int i = 0; i < SIZE; i++)
{
K += i*i;
}
printf("%.6g\n", K);
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c_);
free(a);
free(b);
free(c_);
return 0;
}
|
9,772 |
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <iostream>
#include <stdio.h>
void checkCUDAError(const char *msg)
{
cudaError_t err = cudaGetLastError();
if (cudaSuccess != err)
{
fprintf(stderr, "CUDA error: %s: %s. \n", msg, cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
}
__global__ void render(uchar4 *pos, int width, int height) {
int i = threadIdx.x + blockIdx.x * blockDim.x;
int j = threadIdx.y + blockIdx.y * blockDim.y;
if ((i >= width) || (j >= height))
return;
int index = j * width + i;
unsigned char r = int(float(i) / width * 255.99) & 0xff;
unsigned char g = int(float(j) / height * 255.99) & 0xff;
unsigned char b = (70) & 0xff;
pos[index].w = 0;
pos[index].x = r;
pos[index].y = g;
pos[index].z = b;
}
extern "C" void launch_kernel(uchar4* pos, unsigned int w, unsigned int h) {
int tx = 8;
int ty = 8;
dim3 blocks(w / tx + 1, h / ty + 1);
dim3 threads(tx, ty);
render <<<blocks, threads >>> (pos, w, h);
cudaThreadSynchronize();
checkCUDAError("kernel failed!");
}
|
9,773 | #include<iostream>
using namespace std;
int main(){
cout<<"Mayank"<<endl;
return 0;
}
|
9,774 | #ifndef FLUID_DYNAMICS_GPU_CU
#define FLUID_DYNAMICS_GPU_CU
#endif |
9,775 |
__constant__ int heightWidth[4]; // height, width, height*width of puzzle, population size
__device__ void overwrite( int * gridPopulation, int * gridChildren, int parent, int child);
__device__ int difference(int * population, int * children, int p, int c);
// replaces parents by children according to their fitness
extern "C"
__global__ void updatePopulation(int * gridPopulation, int * gridChildren, int * fitness, int * fitnessChildren, int * randomSelection)
{
__shared__ int differenceArray[320];
int ind = blockDim.x * blockIdx.x + threadIdx.x ; // number of individual in population
int ind2 = randomSelection[ind]; // the other individual
int p,pp,c,cc;
// each children computes difference of two pairs of child and parents
if(ind < ind2 ){ // p1+c2, p2+c1
p = ind;
c = ind2;
pp = ind2;
cc = ind;
}else{ // p1+c1, c2+p2
p = ind;
c = ind;
pp = ind2;
cc = ind2;
}
differenceArray[ind] = difference(gridPopulation, gridChildren, p, c);
differenceArray[ind] += difference(gridPopulation, gridChildren, pp, cc);
__syncthreads();
if(differenceArray[ind] > differenceArray[ind2]){ // should I compare with direct or other parent?
if (fitness[p] <= fitnessChildren[c]) {
fitness[p] = fitnessChildren[c];
p = p * heightWidth[2]; // index in population -> index in array
c = c * heightWidth[2];
cc = cc * heightWidth[2];
overwrite(gridPopulation, gridChildren, p, c);
}
} else {
if (fitness[p] <= fitnessChildren[cc]) {
fitness[p] = fitnessChildren[cc];
p = p * heightWidth[2]; // index in population -> index in array
c = c * heightWidth[2];
cc = cc * heightWidth[2];
overwrite(gridPopulation, gridChildren, p, cc);
}
}
}
// overwrites
__device__ void overwrite( int * gridPopulation, int* gridChildren, int p, int c){
for (int i = 0; i < heightWidth[2]; i++) {
gridPopulation[p + i] = gridChildren[c + i];
}
}
// counts how simmillar is parent to child
__device__ int difference(int * population, int* children, int p, int c){
int diff = 0;
p = p*heightWidth[2];
c = c*heightWidth[2];
for (int i = 0; i < heightWidth[2]; i++) {
if (children[c + i] != population[p + i]) {
diff++;
}
}
return diff;
} |
9,776 | #include <cuda.h>
#include <stdio.h>
#include <time.h>
#include <stdlib.h>
// kernel
__global__ void multiplyMatricesKernel(float* d_x, float* d_y, float* d_z, int m, int n, int p)
{
// indexing variables
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
// thread boundary check
if(i < p && j < m)
{
for(int k = 0; k < n; ++k)
{
d_z[j * p + i] += d_x[j * n + k] * d_y[k * p + i];
}
}
}
// CUDA error checking
void errorCheck(unsigned int line)
{
cudaError_t cudaError = cudaGetLastError();
if(cudaError != cudaSuccess)
{
printf("CUDA error in line %u in file %s: %s\n", line - 1, __FILE__, cudaGetErrorString(cudaError));
exit(EXIT_FAILURE);
}
}
// host function containing kernel call
void multiplyMatrices(float* x, float* y, float* z, int m, int n, int p)
{
dim3 numOfBlocks(ceil(p / 32.0), ceil(m / 32.0), 1);
dim3 numOfThreads(32, 32, 1);
size_t bytes_x = m * n * sizeof(float);
size_t bytes_y = n * p * sizeof(float);
size_t bytes_z = m * p * sizeof(float);
float* d_x;
float* d_y;
float* d_z;
cudaMalloc((void**) &d_x, bytes_x);
errorCheck(__LINE__);
cudaMalloc((void**) &d_y, bytes_y);
errorCheck(__LINE__);
cudaMalloc((void**) &d_z, bytes_z);
errorCheck(__LINE__);
cudaMemcpy(d_x, x, bytes_x, cudaMemcpyHostToDevice);
errorCheck(__LINE__);
cudaMemcpy(d_y, y, bytes_y, cudaMemcpyHostToDevice);
errorCheck(__LINE__);
multiplyMatricesKernel<<<numOfBlocks, numOfThreads>>>(d_x, d_y, d_z, m, n, p);
errorCheck(__LINE__);
cudaMemcpy(z, d_z, bytes_z, cudaMemcpyDeviceToHost);
errorCheck(__LINE__);
cudaFree(d_x);
errorCheck(__LINE__);
cudaFree(d_y);
errorCheck(__LINE__);
cudaFree(d_z);
errorCheck(__LINE__);
}
int main()
{
struct timespec start, end;
srand(time(NULL));
size_t m = rand() % 257 + 3840;
size_t n = rand() % 257 + 3840;
size_t p = rand() % 257 + 3840;
float* x = (float*) malloc(m * n * sizeof(float));
float* y = (float*) malloc(n * p * sizeof(float));
float* z = (float*) malloc(m * p * sizeof(float));
for(int i = 0; i < m * n; ++i)
{
x[i] = rand() % 129 - 64;
}
for(int i = 0; i < n * p; ++i)
{
y[i] = rand() % 129 - 64;
}
clock_gettime(CLOCK_REALTIME, &start);
// do matrix multiplication
multiplyMatrices(x, y, z, m, n, p);
clock_gettime(CLOCK_REALTIME, &end);
time_t execTime = (end.tv_sec - start.tv_sec) * 1000000 + (end.tv_nsec - start.tv_nsec) / 1000;
printf("Execution time: %d microseconds.", execTime);
return 0;
}
|
9,777 |
struct cell_id
{
unsigned int i, j, k;
};
#define SOURCE_INDEX(m,g,i,j,k,cmom,ng,nx,ny) ((m)+((cmom)*(g))+((cmom)*(ng)*(i))+((cmom)*(ng)*(nx)*(j))+((cmom)*(ng)*(nx)*(ny)*(k)))
#define SCAT_COEFF_INDEX(a,l,o,nang,cmom) ((a)+((nang)*(l))+((nang)*(cmom)*o))
#define FLUX_I_INDEX(a,g,j,k,nang,ng,ny) ((a)+((nang)*(g))+((nang)*(ng)*(j))+((nang)*(ng)*(ny)*(k)))
#define FLUX_J_INDEX(a,g,i,k,nang,ng,nx) ((a)+((nang)*(g))+((nang)*(ng)*(i))+((nang)*(ng)*(nx)*(k)))
#define FLUX_K_INDEX(a,g,i,j,nang,ng,nx) ((a)+((nang)*(g))+((nang)*(ng)*(i))+((nang)*(ng)*(nx)*(j)))
#define ANGULAR_FLUX_INDEX(a,g,i,j,k,nang,ng,nx,ny) ((a)+((nang)*(g))+((nang)*(ng)*(i))+((nang)*(ng)*(nx)*(j))+((nang)*(ng)*(nx)*(ny)*(k)))
#define source(m,g,i,j,k) source[SOURCE_INDEX((m),(g),(i),(j),(k),cmom,ng,nx,ny)]
#define scat_coeff(a,l,o) scat_coeff[SCAT_COEFF_INDEX((a),(l),(o),nang,cmom)]
#define flux_i(a,g,j,k) flux_i[FLUX_I_INDEX((a),(g),(j),(k),nang,ng,ny)]
#define flux_j(a,g,i,k) flux_j[FLUX_J_INDEX((a),(g),(i),(k),nang,ng,nx)]
#define flux_k(a,g,i,j) flux_k[FLUX_K_INDEX((a),(g),(i),(j),nang,ng,nx)]
#define angular_flux_in(a,g,i,j,k) angular_flux_in[ANGULAR_FLUX_INDEX((a),(g),(i),(j),(k),nang,ng,nx,ny)]
#define angular_flux_out(a,g,i,j,k) angular_flux_out[ANGULAR_FLUX_INDEX((a),(g),(i),(j),(k),nang,ng,nx,ny)]
__global__ void sweep_plane_kernel(
const unsigned int nx,
const unsigned int ny,
const unsigned int nz,
const unsigned int nang,
const unsigned int ng,
const unsigned int cmom,
const int istep,
const int jstep,
const int kstep,
const unsigned int oct,
const unsigned int z_pos,
const unsigned int num_cells,
const struct cell_id * plane,
const double * __restrict__ source,
const double * __restrict__ scat_coeff,
const double * __restrict__ dd_i,
const double * __restrict__ dd_j,
const double * __restrict__ dd_k,
const double * __restrict__ mu,
const double * __restrict__ velocity_delta,
const double * __restrict__ mat_cross_section,
const double * __restrict__ angular_flux_in,
double * __restrict__ flux_i,
double * __restrict__ flux_j,
double * __restrict__ flux_k,
double * __restrict__ angular_flux_out
)
{
// Recover indexes for angle and group
const size_t global_id_x = blockIdx.x * blockDim.x + threadIdx.x;
const size_t global_id_y = blockIdx.y * blockDim.y + threadIdx.y;
if (global_id_x >= nang*ng) return;
if (global_id_y >= num_cells) return;
const size_t a = global_id_x % nang;
const size_t g = global_id_x / nang;
// Read cell index from plane buffer
const size_t i = (istep > 0) ? plane[global_id_y].i : nx - plane[global_id_y].i - 1;
const size_t j = (jstep > 0) ? plane[global_id_y].j : ny - plane[global_id_y].j - 1;
const size_t k = (kstep > 0) ? plane[global_id_y].k + z_pos : nz - plane[global_id_y].k - z_pos - 1;
//
// Compute the angular flux (psi)
//
// Begin with the first scattering moment
const unsigned int s_stride = (cmom*g)+(cmom*ng*i)+(cmom*ng*nx*j)+(cmom*ng*nx*ny*k);
double source_term = source[0 + s_stride];
// Add in the anisotropic scattering source moments
for (unsigned int l = 1; l < cmom; l++)
{
source_term += scat_coeff[a+(nang*l)+(nang*cmom*oct)]
* source[l + s_stride];
}
const unsigned int i_index = a + (nang*g) + (nang*ng*j) + (nang*ng*ny*k);
const unsigned int j_index = a + (nang*g) + (nang*ng*i) + (nang*ng*nx*k);
const unsigned int k_index = a + (nang*g) + (nang*ng*i) + + (nang*ng*nx*j);
const unsigned int flux_index = k_index + (nang*ng*nx*ny*k);
double psi =
source_term
+ flux_i[i_index]*mu[a]*dd_i[0]
+ flux_j[j_index]*dd_j[a]
+ flux_k[k_index]*dd_k[a];
// Add contribution from last timestep flux if time-dependant
if (velocity_delta[g] != 0.0)
{
psi += velocity_delta[g] * angular_flux_in[flux_index];
}
// Divide by denominator
psi /= (mat_cross_section[g] + velocity_delta[g] + mu[a]*dd_i[0] + dd_j[a] + dd_k[a]);
// Compute upwind fluxes
double tmp_flux_i = 2.0 * psi - flux_i[i_index];
double tmp_flux_j = 2.0 * psi - flux_j[j_index];
double tmp_flux_k = 2.0 * psi - flux_k[k_index];
// Time difference the final flux value
if (velocity_delta[g] != 0.0)
{
psi = 2.0 * psi - angular_flux_in[flux_index];
}
// Fixup
double zeros[4];
int num_ok = 4;
for (int fix = 0; fix < 4; fix++)
{
zeros[0] = (tmp_flux_i < 0.0) ? 0.0 : 1.0;
zeros[1] = (tmp_flux_j < 0.0) ? 0.0 : 1.0;
zeros[2] = (tmp_flux_k < 0.0) ? 0.0 : 1.0;
zeros[3] = (psi < 0.0) ? 0.0 : 1.0;
if (num_ok == zeros[0] + zeros[1] + zeros[2] + zeros[3])
continue;
num_ok = zeros[0] + zeros[1] + zeros[2] + zeros[3];
// Recalculate psi
psi =
flux_i[i_index]*mu[a]*dd_i[0]*(1.0 + zeros[0]) +
flux_j[j_index]*dd_j[a]*(1.0 + zeros[1]) +
flux_k[k_index]*dd_k[a]*(1.0 + zeros[2]);
if (velocity_delta[g] != 0.0)
{
psi += velocity_delta[g] * angular_flux_in[flux_index] * (1.0 + zeros[3]);
}
psi = 0.5 * psi + source_term;
double new_denominator =
mat_cross_section[g] +
mu[a] * dd_i[0] * zeros[0] +
dd_j[a] * zeros[1] +
dd_k[a] * zeros[2] +
velocity_delta[g] * zeros[3];
if (new_denominator > 1.0E-12)
{
psi /= new_denominator;
}
else
{
psi = 0.0;
}
tmp_flux_i = 2.0 * psi - flux_i[i_index];
tmp_flux_j = 2.0 * psi - flux_j[j_index];
tmp_flux_k = 2.0 * psi - flux_k[k_index];
if (velocity_delta[g] != 0.0)
{
psi = 2.0 * psi - angular_flux_in[flux_index];
}
}
// Write values to global memory
flux_i[i_index] = tmp_flux_i * zeros[0];
flux_j[j_index] = tmp_flux_j * zeros[1];
flux_k[k_index] = tmp_flux_k * zeros[2];
angular_flux_out[flux_index] = psi * zeros[3];
}
|
9,778 | #include "WeightedCellularAutomata.cuh"
/**
* Creates a queue entry of x and y values
* Parameter x: the x value
* Parameter y: the y value
* Returns: an entry to insert into the queue
*/
int* createQueueEntry(int x, int y){
int* entry=(int*)calloc(2, sizeof(int));
entry[0]=x;
entry[1]=y;
return entry;
}
void addSurroundingsToQueue(Queue** queue, float** empireMap, int width, int height, int x, int y){
for(int surroundingY=max(0, y-1); surroundingY<min(height, y+2); surroundingY++){
for(int surroundingX=max(0, x-1); surroundingX<min(width, x+2); surroundingX++){
if(empireMap[surroundingY][surroundingX]==0 && (x!=surroundingX || y!=surroundingY)){
insertToQueue(queue, createQueueEntry(surroundingX, surroundingY));
}
}
}
}
/**
* Generates the capitals (starting points) for each civilization
* Each civilization will expand outwards from there
* Parameter queue: the queue to add the surrounding pixels to
* Parameter empireMap: the map of empires
* Parameter map: the map of land and water
* Parameter width: the width of the maps
* Parameter height: the height of the maps
* Parameter empires: the list of empires to draw
* Parameter numEmpires: the number of empires in the list
* Returns: nothing
*/
void generateCapitals(Queue** queue, float** empireMap, float** map, int width, int height, empire* empires, int numEmpires){
for(int empire=0; empire<numEmpires; empire++){
int capitalX;
int capitalY;
do{
capitalX=(int)((((double)rand())/RAND_MAX)*width);
capitalY=(int)((((double)rand())/RAND_MAX)*height);
}while(map[capitalY][capitalX]<0);
empires[empire].capitalX=capitalX;
empires[empire].capitalY=capitalY;
empireMap[capitalY][capitalX]=empires[empire].number;
addSurroundingsToQueue(queue, empireMap, width, height, capitalX, capitalY);
}
}
/**
* Checks a single entry from the queue for possible expansions
* Parameter queue: the queue to get the tile from
* Parameter empireMap: the map of empires to possibly add the tile to
* Parameter map: the map of land/sea height values
* Parameter width: the width of the maps
* Parameter height: the height of the maps
* Parameter empires: the list of empires
* Parameter numEmpires: the number of empires in the list
*/
void checkTile(Queue** queue, float** empireMap, float** map, int width, int height, empire* empires, int numEmpires){
int* entry=popRandomEntryFromQueue(queue);
if(empireMap[entry[1]][entry[0]]!=0){
free(entry);
return;
}
int* surroundingTilesForEmpire=(int*)calloc(numEmpires, sizeof(int));
// Counts the number of surrounding tiles for each empire
for(int y=max(0, entry[1]-1); y<min(height, entry[1]+2); y++){
for(int x=max(0, entry[0]-1); x<min(width, entry[0]+2); x++){
if(empireMap[y][x]>0){
surroundingTilesForEmpire[((int)empireMap[y][x])-1]++;
}
}
}
float randomProbability=((float)rand())/(RAND_MAX+1);
int isLand=map[entry[1]][entry[0]]>0;
// Gets the empire assoicated with the random probability
for(int empire=0; empire<numEmpires; empire++){
if(isLand){
randomProbability-=surroundingTilesForEmpire[empire]*LANDEXPANSIONPROBABILITY;
}
else{
randomProbability-=surroundingTilesForEmpire[empire]*WATEREXPANSIONPROBABILITY;
}
if(randomProbability<0){
empireMap[entry[1]][entry[0]]=empire+1;
break;
}
}
if(randomProbability>=0){
insertToQueue(queue, entry);
}
else{
addSurroundingsToQueue(queue, empireMap, width, height, entry[0], entry[1]);
}
free(surroundingTilesForEmpire);
}
/**
* Creates a map for empires based on a series of probabalistic expansions
* Parameter map: the map of height values for water/land
* Parameter width: the width of the map
* Parameter height: the height of the map
* Parameter empires: the list of empires
* Parameter numEmpires: the number of empires in the list
* Returns: the map of empires with their corresponding numbers
*/
float** weightedCellularAutomata(float** map, int width, int height, empire* empires, int numEmpires){
// Creates a 10x2 queue
Queue** queue=createQueue(2, 10);
// Creats the empire map
float** empireMap=(float**)calloc(height, sizeof(float*));
for(int y=0; y<height; y++){
empireMap[y]=(float*)calloc(width, sizeof(float));
}
// Creates the capitals and adds the surrounding tiles to the queue
generateCapitals(queue, empireMap, map, width, height, empires, numEmpires);
printf("Capitals made %d for %d empires\n", (*queue)->entries, numEmpires);
// Expands the empires
while(!isEmpty(queue)){
checkTile(queue, empireMap, map, width, height, empires, numEmpires);
}
freeQueue(queue);
for(int y=0; y<height; y++){
for(int x=0; x<width; x++){
if(empireMap[y][x]==0){
printf("Here\n");
}
}
}
return empireMap;
}
|
9,779 | #include <stdio.h>
#include <cuda_runtime.h>
int log2(int i)
{
int r = 0;
while (i >>= 1) r++;
return r;
}
int bit_reverse(int w, int bits)
{
int r = 0;
for (int i = 0; i < bits; i++)
{
int bit = (w & (1 << i)) >> i;
r |= bit << (bits - i - 1);
}
return r;
}
__global__ void simple_histo(int *d_bins, const int *d_in, const int BIN_COUNT)
{
int myId = threadIdx.x + blockDim.x * blockIdx.x;
int myItem = d_in[myId];
int myBin = myItem % BIN_COUNT;
atomicAdd(&(d_bins[myBin]), 1);
}
int main(int argc, char **argv)
{
int deviceCount;
cudaGetDeviceCount(&deviceCount);
if (deviceCount == 0) {
fprintf(stderr, "error: no devices supporting CUDA.\n");
exit(EXIT_FAILURE);
}
int dev = 0;
cudaSetDevice(dev);
cudaDeviceProp devProps;
if (cudaGetDeviceProperties(&devProps, dev) == 0)
{
printf("Using device %d:\n", dev);
printf("%s; global mem: %dB; compute v%d.%d; clock: %d kHz\n",
devProps.name, (int)devProps.totalGlobalMem,
(int)devProps.major, (int)devProps.minor,
(int)devProps.clockRate);
}
const int ARRAY_SIZE = 128;
const int ARRAY_BYTES = ARRAY_SIZE * sizeof(int);
const int BIN_COUNT = 3;
const int BIN_BYTES = BIN_COUNT * sizeof(int);
// generate the input array on the host
int h_in[ARRAY_SIZE];
for (int i = 0; i < ARRAY_SIZE; i++) {
h_in[i] = bit_reverse(i, log2(ARRAY_SIZE));
}
int h_bins[BIN_COUNT];
for (int i = 0; i < BIN_COUNT; i++) {
h_bins[i] = 0;
}
// declare GPU memory pointers
int * d_in;
int * d_bins;
// allocate GPU memory
cudaMalloc((void **)&d_in, ARRAY_BYTES);
cudaMalloc((void **)&d_bins, BIN_BYTES);
// transfer the arrays to the GPU
cudaMemcpy(d_in, h_in, ARRAY_BYTES, cudaMemcpyHostToDevice);
cudaMemcpy(d_bins, h_bins, BIN_BYTES, cudaMemcpyHostToDevice);
printf("Running simple histo\n");
simple_histo <<< ARRAY_SIZE / 64, 64 >>>(d_bins, d_in, BIN_COUNT);
// copy back the sum from GPU
cudaMemcpy(h_bins, d_bins, BIN_BYTES, cudaMemcpyDeviceToHost);
for (int i = 0; i < BIN_COUNT; i++) {
printf("bin %d: count %d\n", i, h_bins[i]);
}
// free GPU memory allocation
cudaFree(d_in);
cudaFree(d_bins);
system("pause");
return 0;
}
|
9,780 | #include <cuda.h>
#include <iomanip>
#include <iostream>
#include <stdio.h>
#include <random>
const int kSize = 5000;
const int kKernelSize = 13; // odd
#define InitRandom() \
std::random_device r; \
std::default_random_engine generator(r()); \
std::uniform_real_distribution<float> distribution(0, 1e3);
void Generate(float *const a, float *const w)
{
#pragma omp parallel for
for (int i = 0; i < kSize; ++i)
{
InitRandom();
const int j_upperbound = (i + 1) * kSize;
for (int j = i * kSize; j < j_upperbound; ++j)
a[j] = distribution(generator);
}
{
InitRandom();
for (int i = 0; i < kKernelSize * kKernelSize; ++i)
w[i] = distribution(generator);
}
}
void Conv(const float *const a, const float *const w, float *const b)
{
#pragma omp parallel for
for (int i = 0; i < kSize; ++i)
{
for (int j = 0; j < kSize; ++j)
{
float conv = 0;
int x = i - kKernelSize / 2, y = j - kKernelSize / 2;
for (int k = 0; k < kKernelSize; ++k)
{
for (int l = 0; l < kKernelSize; ++l)
{
if (!(x < 0 || x >= kSize || y < 0 || y >= kSize))
conv += a[x * kSize + y] * w[k * kKernelSize + l];
y++;
}
x++;
y -= kKernelSize;
}
b[i * kSize + j] = conv;
}
}
}
void Check(const float *const a, const float *const w, float *const b)
{
auto b_std = new float[kSize * kSize];
Conv(a, w, b_std);
for (int i = 0; i < kSize * kSize; ++i)
{
if (abs(b[i] / b_std[i] - 1) > 1e-3 || isnanf(b[i]) || isinff(b[i]))
{
std::cout << "\x1b[31m"
"Wrong Answer"
"\x1b[0m"
" at "
<< i << std::endl;
std::cout << "expected " << b_std[i] << " but found " << b[i]
<< std::endl;
delete[] b_std;
return;
}
}
std::cout << "\x1b[32m"
"Correct"
"\x1b[0m"
<< std::endl;
delete[] b_std;
}
void Output(const float *const a, const float *const w, const float *const b)
{
for (int i = 0; i < kSize; ++i)
{
for (int j = 0; j < kSize; ++j)
std::cout << std::setw(2) << a[i * kSize + j] << ' ';
std::cout << std::endl;
}
for (int i = 0; i < kKernelSize; ++i)
{
for (int j = 0; j < kKernelSize; ++j)
std::cout << std::setw(2) << w[i * kKernelSize + j] << ' ';
std::cout << std::endl;
}
for (int i = 0; i < kSize; ++i)
{
for (int j = 0; j < kSize; ++j)
std::cout << std::setw(2) << b[i * kSize + j] << ' ';
std::cout << std::endl;
}
}
__global__ void ConvGPU(const float *const ad, const float *const wd, float *bd, int const roundX, int const roundY)
{
int RoundStartingIndex = 50 * roundY + 50 * roundX * 5000;
float conv = 0;
int x = blockIdx.x - 13 / 2 + threadIdx.x;
int y = blockIdx.y - 13 / 2 + threadIdx.y;
if (!((x + 50 * roundX < 0) || (x + 50 * roundX >= 5000) || (y + 50 * roundY < 0) || (y + 50 * roundY >= 5000)))
{
conv = ad[RoundStartingIndex + x * 5000 + y] * wd[threadIdx.x * 13 + threadIdx.y];
}
unsigned int tidInBlk = threadIdx.x * 13 + threadIdx.y;
if (tidInBlk >= 13 * 13)
{
return;
}
// float *idata = tmp + (blockIdx.x * 50 + blockIdx.y) * 13 * 13;
__shared__ float idata[13 * 13];
idata[tidInBlk] = conv;
__syncthreads();
if (tidInBlk % 28 == 0 && tidInBlk != 168)
{
for (int i = 1; i < 32; i++)
{
idata[tidInBlk] += idata[tidInBlk + i];
}
}
__syncthreads();
printf("reduced..1\n");
if (tidInBlk == 0)
{
for (int i = 1; i < 7; i++)
{
idata[0] += idata[i * 28];
}
}
printf("reduced..\n");
bd[RoundStartingIndex + blockIdx.x * 5000 + blockIdx.y] = idata[0];
}
int main()
{
auto a = new float[kSize * kSize];
auto w = new float[kKernelSize * kKernelSize];
auto b = new float[kSize * kSize];
Generate(a, w);
cudaEvent_t start_e, stop_e;
cudaEventCreate(&start_e);
cudaEventCreate(&stop_e);
cudaEventRecord(start_e);
int tmpKsize = 50;
// initialize data in device memory.
float *ad = NULL,
*wd = NULL, *bd = NULL;
cudaMalloc(&ad, kSize * kSize * sizeof(float));
cudaMalloc(&wd, kKernelSize * kKernelSize * sizeof(float));
cudaMalloc(&bd, kSize * kSize * sizeof(float));
cudaDeviceSynchronize();
cudaMemcpy(ad, a, kSize * kSize * sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(wd, w, kKernelSize * kKernelSize * sizeof(float), cudaMemcpyHostToDevice);
cudaDeviceSynchronize();
// the promoted GPU version.
dim3 grid(tmpKsize, tmpKsize, 1);
dim3 block(kKernelSize, kKernelSize, 1);
printf("Starting..\n");
for (int i = 0; i < kSize / tmpKsize; i++)
{
for (int j = 0; j < kSize / tmpKsize; j++)
{
ConvGPU<<<grid, block>>>(ad, wd, bd, i, j); // for efficiency concern, tmpKsize is hard-coded.
}
}
cudaDeviceSynchronize();
printf("Ended..\n");
cudaMemcpy(b, bd, kSize * kSize * sizeof(float), cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
cudaEventRecord(stop_e);
cudaEventSynchronize(stop_e);
Check(a, w, b);
float milliseconds = 0;
cudaEventElapsedTime(&milliseconds, start_e, stop_e);
std::cout << milliseconds << " milliseconds" << std::endl;
cudaEventDestroy(start_e);
cudaEventDestroy(stop_e);
// Output(a, w, b);
delete[] a;
delete[] w;
delete[] b;
return 0;
}
|
9,781 | /*
* =====================================================================================
*
* Filename: cuda_transforms.cu
*
* Description: Useful transforms needed before sorting can be carried out.
*
* Version: 1.0
* Created: 2016-06-30 11:14
* Revision: none
* Compiler: nvcc
*
* Author: Michael Tierney (MT), tiernemi@tcd.ie
*
* =====================================================================================
*/
#include "../../inc/cu_inc/cuda_transforms.cuh"
#include <stdio.h>
/*
* === FUNCTION ======================================================================
* Name: cudaCalcDistanceSq
* Arguments: float * gpuTriCo - Pointer to gpu triangle co-ordinates.
* float * gpuCamCo - Pointer to camera co-ordinates.
* float * gpuDistances - Pointer to distances vector which will be
* int numCentroids - Number of centroids in data set
* Description: Calculates the distance squared of each point relative to the camera.
* Reads are clustered in such a way to promote coalesced reading.
* =====================================================================================
*/
__global__ void cudaCalcDistanceSq(const float * __restrict__ gpuCenCo, const float * __restrict__ gpuCamCo, float * gpuDistancesSq, int numCentroids) {
// Grid stride loop. //
for (int i = threadIdx.x + blockDim.x * blockIdx.x ; i < numCentroids ;
i += blockDim.x*gridDim.x) {
// Coalesced reading of centroids. //
float xt = gpuCenCo[i] ;
float yt = gpuCenCo[i+numCentroids] ;
float zt = gpuCenCo[i+(numCentroids*2)] ;
// Coalesced reading of cameras. //
float xc = gpuCamCo[0] ;
float yc = gpuCamCo[1] ;
float zc = gpuCamCo[2] ;
float diffx = xt - xc ;
float diffy = yt - yc ;
float diffz = zt - zc ;
gpuDistancesSq[i] = diffx*diffx + diffy*diffy + diffz*diffz ;
}
}
|
9,782 | #include "stdio.h"
#include <iostream>
#include <cuda.h>
#include <cuda_runtime.h>
__constant__ int dim;
__global__ void test(int *gpu_Num){
*gpu_Num = dim;
}
int main(int argc, char* argv[])
{
int num = 25;
cudaMemcpyToSymbol(dim,&num,sizeof(int),0,cudaMemcpyHostToDevice);
int *gpu_Num;
cudaMalloc(&gpu_Num,sizeof(int));
test<<<1,1>>>(gpu_Num);
int hostResult;
cudaMemcpy(&hostResult,gpu_Num,sizeof(int),cudaMemcpyDefault);
printf("Result: %i\n",hostResult);
}
|
9,783 | #include "includes.h"
__global__ void sum_arrays_gpu(unsigned int * a, unsigned int * b, int size)
{
int index = blockDim.x * blockIdx.x + threadIdx.x;
if (index < size) {
a[0] = a[0] + b[index];
//printf("%u ", a[0]);
}
} |
9,784 | #include <iostream>
#include "stdio.h"
#include <vector>
#include <cuda.h>
// #include "cuPrintf.cu"
const int TILEWIDTH = 2;
__global__ void simpleMatrixStuff (double** firstMatrix, double** resultMatrix) {
for (int i = 0; i < 4; i++) {
for (int j = 0; j < 4; j++) {
resultMatrix[i][j] = 2*firstMatrix[i][j];
}
}
}
__global__ void matrixMultTiled (double** firstMatrix, double** secondMatrix, double** resultMatrix, int width = 4) {
__shared__ double localFirstMatrix[TILEWIDTH][TILEWIDTH];
__shared__ double localSecondMatrix[TILEWIDTH][TILEWIDTH];
double result = 0;
// Define short values for index variables
int tx = threadIdx.x;
int ty = threadIdx.y;
int basecol = blockIdx.x * blockDim.x;
int baserow = blockIdx.y * blockDim.y;
// Tile Loop
for (int i = 0; i < width / TILEWIDTH; i++) {
// Fill local matrices
localFirstMatrix[tx][ty] = firstMatrix[i*TILEWIDTH+tx][baserow+ty];
localSecondMatrix[tx][ty] = secondMatrix[basecol+tx][i*TILEWIDTH+ty];
// localSecondMatrix[ty][tx] = secondMatrix[basecol+tx][i*TILEWIDTH+ty]; // transposing matrix
__syncthreads(); // (Globally) Wait for all local matrizes to be filled
// Loop for calculating result matrix's element
for (int j = 0; j < TILEWIDTH; j++) {
result += localFirstMatrix[j][tx] * localSecondMatrix[ty][j];
// result += localFirstMatrix[j][ty] * localSecondMatrix[j][tx]; // transposed matrix
}
__syncthreads(); // (Globally) Wait for every res_matrix element to be calculated
}
resultMatrix[basecol+tx][baserow+ty] = result; // Fill calculated res_matrix element in actual final res_matrix
}
// Output stuff
void mOut_singleLine (double* matrixLine, int sizeOfMatrix) {
for (unsigned int i = 0; i < sizeOfMatrix; i++) {
if (matrixLine[i] < 10) std::cout << " ";
std::cout << matrixLine[i] << " ";
}
}
void mOut_singleMatrix (double ** singleMatrix, int sizeOfMatrix) {
for (unsigned int i = 0; i < sizeOfMatrix; i++) {
std::cout << "( ";
mOut_singleLine(singleMatrix[i], sizeOfMatrix);
std::cout << ")" << std::endl;
}
}
void mOut_product (double** matrixOne, double** matrixTwo, int sizeOfMatrix) {
for (int i = 0; i < sizeOfMatrix; i++) {
std::cout << "( ";
mOut_singleLine(matrixOne[i], sizeOfMatrix);
std::cout << ")";
if (i == 1 || i == 2) {
std::cout << " * ";
} else {
std::cout << " ";
}
std::cout << "( ";
mOut_singleLine(matrixTwo[i], sizeOfMatrix);
std::cout << ")" << std::endl;
}
}
int main (int argc, char** argv) {
// cudaPrintfInit();
int sizeOfMatrix = 4;
double** matrixOne = new double *[sizeOfMatrix];
double** matrixTwo = new double *[sizeOfMatrix];
double** matrixRes = new double *[sizeOfMatrix];
srand(23);
for (int i = 0; i < sizeOfMatrix; i++) {
matrixOne[i] = new double[sizeOfMatrix];
matrixTwo[i] = new double[sizeOfMatrix];
matrixRes[i] = new double[sizeOfMatrix];
for (int j = 0; j < sizeOfMatrix; j++) {
matrixOne[i][j] = rand() % 100;
matrixTwo[i][j] = rand() % 100;
matrixRes[i][j] = -1;
}
}
std::cout << "Original matrices:" << std::endl;
// mOut_singleMatrix(matrixOne, sizeOfMatrix);
mOut_product(matrixOne, matrixTwo, sizeOfMatrix);
double** dev_matrixOne;
double** dev_matrixTwo;
double** dev_matrixRes;
cudaMalloc((void**)&dev_matrixOne, sizeOfMatrix*sizeof(double*));
cudaMalloc((void**)&dev_matrixTwo, sizeOfMatrix*sizeof(double*));
cudaMalloc((void**)&dev_matrixRes, sizeOfMatrix*sizeof(double*));
for (int i = 0; i < sizeOfMatrix; i++) {
double* dev_tempOne = 0;
cudaMalloc((void**) &dev_tempOne, sizeOfMatrix*sizeof(double));
cudaMemcpy(dev_matrixOne + i, &dev_tempOne, sizeof(double*), cudaMemcpyHostToDevice);
cudaMemcpy(dev_tempOne, matrixOne[i], sizeOfMatrix*sizeof(double), cudaMemcpyHostToDevice);
double* dev_tempTwo = 0;
cudaMalloc((void**) &dev_tempTwo, sizeOfMatrix*sizeof(double));
cudaMemcpy(dev_matrixTwo + i, & dev_tempTwo, sizeof(double*), cudaMemcpyHostToDevice);
cudaMemcpy(dev_tempTwo, matrixTwo[i], sizeOfMatrix*sizeof(double), cudaMemcpyHostToDevice);
double* dev_tempRes = 0;
cudaMalloc((void**) &dev_tempRes, sizeOfMatrix*sizeof(double));
cudaMemcpy(dev_matrixRes + i, &dev_tempRes, sizeof(double*), cudaMemcpyHostToDevice);
}
simpleMatrixStuff<<<1,1>>>(dev_matrixOne, dev_matrixRes);
for (int i = 0; i < sizeOfMatrix; i++) {
double* tempDouble = 0;
cudaMemcpy(&tempDouble, dev_matrixRes+i, sizeof(double*), cudaMemcpyDeviceToHost);
cudaMemcpy(matrixRes[i], tempDouble, sizeOfMatrix*sizeof(double), cudaMemcpyDeviceToHost);
}
std::cout << "Check for matrix1:" << std::endl;
mOut_singleMatrix(matrixRes, sizeOfMatrix);
simpleMatrixStuff<<<1,1>>>(dev_matrixTwo, dev_matrixRes);
for (int i = 0; i < sizeOfMatrix; i++) {
double* tempDouble = 0;
cudaMemcpy(&tempDouble, dev_matrixRes+i, sizeof(double*), cudaMemcpyDeviceToHost);
cudaMemcpy(matrixRes[i], tempDouble, sizeOfMatrix*sizeof(double), cudaMemcpyDeviceToHost);
}
std::cout << "Check for matrix2:" << std::endl;
mOut_singleMatrix(matrixRes, sizeOfMatrix);
matrixMultTiled<<<dim3(2,2), dim3(2,2)>>>(dev_matrixOne, dev_matrixTwo, dev_matrixRes);
for (int i = 0; i < sizeOfMatrix; i++) {
double* tempDouble = 0;
cudaMemcpy(&tempDouble, dev_matrixRes+i, sizeof(double*), cudaMemcpyDeviceToHost);
cudaMemcpy(matrixRes[i], tempDouble, sizeOfMatrix*sizeof(double), cudaMemcpyDeviceToHost);
}
std::cout << "Multiplied Matrix: " << std::endl;
mOut_singleMatrix(matrixRes, sizeOfMatrix);
std::cout << "Which is, sadly, wrong -- if you use B*A instead of A*B you get the right result: " << std::endl;
matrixMultTiled<<<dim3(2,2), dim3(2,2)>>>(dev_matrixTwo, dev_matrixOne, dev_matrixRes);
for (int i = 0; i < sizeOfMatrix; i++) {
double* tempDouble = 0;
cudaMemcpy(&tempDouble, dev_matrixRes+i, sizeof(double*), cudaMemcpyDeviceToHost);
cudaMemcpy(matrixRes[i], tempDouble, sizeOfMatrix*sizeof(double), cudaMemcpyDeviceToHost);
}
mOut_singleMatrix(matrixRes, sizeOfMatrix);
// cudaPrintfDisplay(stdout, true);
// cudaPrintfEnd();
}
|
9,785 | //George Lees Jr.
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>
#define N 1000
#include <iostream>
#include <ctime>
extern "C"
__global__ void NearestNeighborKernel(float* A_x_d, float* A_y_d ,float* B_x_d, float* B_y_d, float* A_agentstrength_d, float* B_agentstrength_d)
{
int j_min_d;
int idx = threadIdx.x + blockIdx.x * blockDim.x;
if(idx < N)//so threads don't go past the bounds
{
float dist_min = 3.40282e38f;
for(int j = 0; j < N; j++)
{
if(j == idx) continue;
float dist_vec_d = sqrt(pow((A_x_d[idx]-B_x_d[j]),2)+pow((A_y_d[idx]-B_y_d[j]),2));
//syncthreads
if(dist_vec_d < dist_min)
{
dist_min = dist_vec_d;
j_min_d= j;
}
//syncthreads
if(dist_min<0.02 && B_agentstrength_d[j_min_d]>0.001)
{
/* Simple fight model - weakest agent killed */
if(A_agentstrength_d[j]<B_agentstrength_d[j_min_d])
{
A_agentstrength_d[j]=0;
}
else
{
B_agentstrength_d[j_min_d]=0;
}
}
}
}
}
int main(void)
{
// Declare variables and pointers on host to send to gpu
float *A_x, *A_y, *B_x, *B_y;
float *A_agentstrength;
float *B_agentstrength;
int vector_size;
vector_size = N*sizeof(float);
A_x = (float *)malloc(vector_size);
A_y = (float *)malloc(vector_size);
B_x = (float *)malloc(vector_size);
B_y = (float *)malloc(vector_size);
A_agentstrength = (float *)malloc(vector_size);
B_agentstrength = (float *)malloc(vector_size);
int i, time;
float delx, dely;
int total_dead_A[N];
int total_dead_B[N];
FILE *myfile;
FILE *myfile2;
// Declare variables on device
float *A_x_d;
float *A_y_d;
float *B_x_d;
float *B_y_d;
float *A_agentstrength_d;
float *B_agentstrength_d;
cudaMalloc(&A_x_d, vector_size);
cudaMalloc(&A_y_d, vector_size);
cudaMalloc(&B_x_d, vector_size);
cudaMalloc(&B_y_d, vector_size);
cudaMalloc(&A_agentstrength_d, vector_size);
cudaMalloc(&B_agentstrength_d, vector_size);
/* open files to write results */
myfile = fopen("agentresults.dat","w");
myfile2 = fopen("agentsummary.dat","w");
/* A loop to set the initial positions and strengths of 200 agents
* (100 in team A and 100 in team B) which are random distributed
* in a region with corners (-4,-4),(-4,4), (4,-4) and (4,4).
* Strengths are assigned as random numbers between 0.5 and 1.0.
* If agentstrength is less than 0.001 it is considered dead. */
for (i=1;i<=N;++i)
{
A_x[i] = -4.0 + 8.0*((float) rand() / (float) (RAND_MAX-1));
A_y[i] = -4.0 + 8.0*((float) rand() / (float) (RAND_MAX-1));
B_x[i] = -4.0 + 8.0*((float) rand() / (float) (RAND_MAX-1));
B_y[i] = -4.0 + 8.0*((float) rand() / (float) (RAND_MAX-1));
A_agentstrength[i]=0.5 + 0.5* ((float) rand() / (float) (RAND_MAX-1));
B_agentstrength[i]=0.5 + 0.5* ((float) rand() / (float) (RAND_MAX-1));
}
// Start the time loop
for(time=1;time<=100;++time)
{
/* Loop through all agents on both teams (A and B)
* and update their positions by adding random numbers to their
* position (x,y). Note that if they move outside a region bounded
* by the corners (-5,-5), (-5,5), (5,-5) and (5,5) they are put
* back in the region.
*/
for (i=1;i<=N;++i)
{
if(A_agentstrength[i]>0.001)
{
delx = (float) rand() / (float) (RAND_MAX-1) - 0.5 ;
dely = (float) rand() / (float) (RAND_MAX-1) - 0.5;
A_x[i] = A_x[i] + delx;
A_y[i] = A_y[i] + dely;
/* If, by adding the movement we move the agent out of the confining region
* then move the agent back to stay in region */
if(A_x[i]>5) {A_x[i]=A_x[i]-delx;}
if(A_x[i]<-5) {A_x[i]=A_x[i]+delx;}
if(A_y[i]>5) {A_y[i]=A_y[i]-dely;}
if(A_y[i]<-5) {A_y[i]=A_y[i]+dely;}
}
if(B_agentstrength[i]>0.001)
{
delx = (float) rand() / (float) (RAND_MAX-1) - 0.5;
dely = (float) rand() / (float) (RAND_MAX-1) - 0.5;
B_x[i] = B_x[i] + delx;
B_y[i] = B_y[i] + dely;
/* If, by adding the movement we move the agent out of the confining region
* then move the agent back to stay in region */
if(B_x[i]>5) {B_x[i]=B_x[i]-delx;}
if(B_x[i]<-5) {B_x[i]=B_x[i]+delx;}
if(B_y[i]>5) {B_y[i]=B_y[i]-dely;}
if(B_y[i]<-5) {B_y[i]=B_y[i]+dely;}
}
}
/* Loop through all agents on both teams A and for each agent
* find the nearest individual on team B. Then fight with it.
* Loser dies.*/
//&&
/* If the nearest agent on team B is close enough to the agent i on team A
* and not already dead then fight */
// transfer vectors A_x, A_y, B_x, B_y to gpu
cudaMemcpy(A_x_d, A_x, vector_size, cudaMemcpyHostToDevice);
cudaMemcpy(A_y_d, A_y, vector_size, cudaMemcpyHostToDevice);
cudaMemcpy(B_x_d, B_x, vector_size, cudaMemcpyHostToDevice);
cudaMemcpy(B_y_d, B_y, vector_size, cudaMemcpyHostToDevice);
cudaMemcpy(A_agentstrength_d, A_agentstrength, vector_size, cudaMemcpyHostToDevice);
cudaMemcpy(B_agentstrength_d, B_agentstrength, vector_size, cudaMemcpyHostToDevice);
NearestNeighborKernel<<< 4, 512>>> (A_x_d, A_y_d, B_x_d,
B_y_d, A_agentstrength_d, B_agentstrength_d);
cudaMemcpy(A_x, A_x_d, vector_size, cudaMemcpyDeviceToHost);
cudaMemcpy(A_y, A_y_d, vector_size, cudaMemcpyDeviceToHost);
cudaMemcpy(B_x, B_x_d, vector_size, cudaMemcpyDeviceToHost);
cudaMemcpy(B_y, B_y_d, vector_size, cudaMemcpyDeviceToHost);
cudaMemcpy(A_agentstrength,A_agentstrength_d, vector_size, cudaMemcpyDeviceToHost);
cudaMemcpy(B_agentstrength,B_agentstrength_d, vector_size, cudaMemcpyDeviceToHost);
/* Print out all agent positions and strengths for both teams */
for(i=1;i<=N;++i)
{
fprintf(myfile, "%f %f %f %f %f %f \n",A_x[i],A_y[i],A_agentstrength[i],B_x[i],B_y[i],B_agentstrength[i]);
}
/* Compute number dead for both teams */
total_dead_A[time]=0;
total_dead_B[time]=0;
for(i=1;i<=N;++i)
{
if(A_agentstrength[i]<0.001){total_dead_A[time]=total_dead_A[time]+1;}
if(B_agentstrength[i]<0.001){total_dead_B[time]=total_dead_B[time]+1;}
}
fprintf(myfile2, "%d %d \n",total_dead_A[time],total_dead_B[time]);
/* Go back for another time step */
}
free(A_x);free(A_y);free(B_x);free(B_y);
cudaFree(A_x_d);
cudaFree(A_y_d);
cudaFree(B_x_d);
cudaFree(B_y_d);
/* Close files */
if(myfile!=NULL)
{
fclose(myfile);
}
if(myfile2!=NULL)
{
fclose(myfile2);
}
return EXIT_SUCCESS;
}
|
9,786 | #include "includes.h"
#define tam 1.0
#define dx 0.00001
#define dt 0.000001
#define T 0.01
#define kappa 0.000045
__global__ void Inicializacao( double *uprev, const int n ) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
double x = idx * dx;
if( idx < n + 1 ) {
if( x <= 0.5 ) {
uprev[ idx ] = 200 * x;
}
else {
uprev[ idx ] = 200 * ( 1. - x );
}
}
} |
9,787 | /*CUDA 2-D Matrix Multiplication*/
#include <stdio.h>
#include <math.h>
#define TILE_WIDTH 2
#define WIDTH 100
__global__ void MatrixMul( float *A_d , float *B_d , float *C_d)
{
// calculate thread id
unsigned int col = TILE_WIDTH*blockIdx.x + threadIdx.x ;
unsigned int row = TILE_WIDTH*blockIdx.y + threadIdx.y ;
C_d[row*WIDTH+col] = 0;
for (int k = 0 ; k<WIDTH ; k++ )
{
C_d[row*WIDTH + col]+= A_d[row * WIDTH + k ] * B_d[ k * WIDTH + col] ;
}
}
// main routine
int main ()
{
float array1_h[WIDTH][WIDTH] ,array2_h[WIDTH][WIDTH];
float non_array_h[WIDTH][WIDTH] ,M_result_array_h[WIDTH][WIDTH] ;
float *array1_d , *array2_d ,*M_result_array_d ; // device array
int i , j ;
//input in host array
for ( i = 0 ; i<WIDTH ; i++ )
{
for (j = 0 ; j<WIDTH ; j++ )
{
array1_h[i][j] =(float)rand()/(float)RAND_MAX;
array2_h[i][j] = (float)rand()/(float)RAND_MAX;
}
}
//Non-threaded routine
for(i=0; i<WIDTH; ++i)
{
for(j=0; j<WIDTH; ++j)
{
non_array_h[i][j]=0;
for(int k=0; k<WIDTH; ++k)
{
non_array_h[i][j] += array1_h[i][k] * array2_h[k][j] ;
}
}
}
//create device array cudaMalloc ( (void **)&array_name, sizeofmatrixinbytes) ;
cudaMalloc((void **) &array1_d , WIDTH*WIDTH*sizeof (float) ) ;
cudaMalloc((void **) &array2_d , WIDTH*WIDTH*sizeof (float) ) ;
//copy host array to device array; cudaMemcpy ( dest , source , WIDTH , direction )
cudaMemcpy ( array1_d , array1_h , WIDTH*WIDTH*sizeof (float) , cudaMemcpyHostToDevice ) ;
cudaMemcpy ( array2_d , array2_h , WIDTH*WIDTH*sizeof (float) , cudaMemcpyHostToDevice ) ;
//allocating memory for resultant device array
cudaMalloc((void **) &M_result_array_d , WIDTH*WIDTH*sizeof (float) ) ;
//calling kernel
dim3 dimGrid ( WIDTH/TILE_WIDTH , WIDTH/TILE_WIDTH ,1 ) ;
dim3 dimBlock( TILE_WIDTH, TILE_WIDTH, 1 ) ;
MatrixMul <<<dimGrid,dimBlock>>> ( array1_d , array2_d ,M_result_array_d) ;
//copy back result_array_d to result_array_h
cudaMemcpy(M_result_array_h , M_result_array_d , WIDTH*WIDTH*sizeof(float) ,
cudaMemcpyDeviceToHost) ;
float error = 0;
//print the result array
printf("*****************************************\n");
printf("Vector Multiplication of %d*%d matrix\n", WIDTH, WIDTH);
printf("*****************************************\n");
for ( i = 0 ; i<WIDTH ; i++ )
{
for ( j = 0 ; j < WIDTH ; j++ )
{
// printf ("%f %f\t",non_array_h[i][j], M_result_array_h[i][j] ) ;
//Root mean square of the differences
error += pow(M_result_array_h[i][j]-non_array_h[i][j], 2);
}
//printf ("\n") ;
}
error = error/(WIDTH*WIDTH);
error = sqrt(error);
printf("*****************************************\n");
printf("Error:%f\n", error);
printf("*****************************************\n");
cudaFree(array1_d);
cudaFree(array2_d);
cudaFree(M_result_array_d);
return 0;
} |
9,788 | //ECGR 6090 Heterogeneous Computing Homework 0
// Problem 2 a - 1D Stencil on GPU
//Written by Aneri Sheth - 801085402
// Reference taken from Lecture Slides by Dr. Tabkhi
//Other reference taken from https://github.com/szymonm/pwir-cuda-labs/tree/master/lab1 and https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html#using-cuda-gpu-timers
#include <stdio.h>
#include <time.h>
#define RADIUS 2 //radius = 2,4,8,16
#define BLOCK_SIZE 128 //fixed number of threads per block
#define NUM_ELEMENTS 10000 //job size = 1K, 10K, 100K, 1M and 10M
// CUDA API error checking macro
static void handleError(cudaError_t err,
const char *file,
int line ) {
if (err != cudaSuccess) {
printf("%s in %s at line %d\n", cudaGetErrorString(err),
file, line );
exit(EXIT_FAILURE);
}
}
#define cudaCheck( err ) (handleError(err, __FILE__, __LINE__ ))
__global__ void stencil_1d(int *in, int *out)
{
// index of a thread across all threads + RADIUS
int gindex = threadIdx.x + (blockIdx.x * blockDim.x) + RADIUS;
int result = 0;
for (int offset = -RADIUS ; offset <= RADIUS ; offset++)
result += in[gindex + offset];
// Store the result
out[gindex - RADIUS] = result;
}
int main()
{
unsigned int i;
cudaEvent_t start, stop; //time start and stop
float time;
cudaEventCreate(&start);
cudaEventCreate(&stop);
//CPU array copies
int h_in[NUM_ELEMENTS + 2 * RADIUS], h_out[NUM_ELEMENTS];
// GPU array copies
int *d_in, *d_out;
for( i = 0; i < (NUM_ELEMENTS + 2*RADIUS); ++i )
h_in[i] = 1;
// Allocate device memory
cudaCheck( cudaMalloc( &d_in, (NUM_ELEMENTS + 2*RADIUS) * sizeof(int)) );
cudaCheck( cudaMalloc( &d_out, NUM_ELEMENTS * sizeof(int)) );
//copy fro CPU to GPU memory
cudaCheck( cudaMemcpy( d_in, h_in, (NUM_ELEMENTS + 2*RADIUS) * sizeof(int),
cudaMemcpyHostToDevice) );
cudaEventRecord( start, 0 );
// Call stencil kernel
stencil_1d<<< (NUM_ELEMENTS + BLOCK_SIZE - 1)/BLOCK_SIZE, BLOCK_SIZE >>> (d_in, d_out);
cudaEventRecord( stop, 0 );
cudaEventSynchronize(stop);
cudaEventElapsedTime( &time, start, stop );
cudaEventDestroy( start );
cudaEventDestroy( stop );
printf(" GPU Execution Time = %f\n",time);
// Copy results from device memory to host
cudaCheck( cudaMemcpy( h_out, d_out, NUM_ELEMENTS * sizeof(int),
cudaMemcpyDeviceToHost) );
// Free out memory
cudaFree(d_in);
cudaFree(d_out);
return 0;
}
|
9,789 | #include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <cuda_runtime.h>
#define THREAD_NUM 512
#define MATRIX_SIZE 1000
const int blocks_num = (MATRIX_SIZE + THREAD_NUM - 1) / THREAD_NUM;
void printDeviceProp(const cudaDeviceProp &prop)
{
printf("Device Name : %s.\n", prop.name);
printf("totalFlbalMem : %d.\n", prop.totalGlobalMem);
printf("sharedMemPerBlock : %d.\n", prop.regsPerBlock);
printf("regsPerBlock : %d.\n", prop.regsPerBlock);
printf("warpSize : %d.\n", prop.warpSize);
printf("memPitch : %d.\n", prop.memPitch);
printf("maxThreadsPerBlock : %d.\n", prop.maxThreadsPerBlock);
printf("maxThreadsDim[0 - 2] : %d %d %d.\n", prop.maxThreadsDim[0], prop.maxThreadsDim[1], prop.maxThreadsDim[2]);
printf("maxGridSize[0 - 2] : %d %d %d.\n", prop.maxGridSize[0], prop.maxGridSize[1], prop.maxGridSize[2]);
printf("totalConstMem : %d.\n", prop.totalConstMem);
printf("major.minor : %d.%d.\n", prop.major, prop.minor);
printf("clockRate : %d.\n", prop.clockRate);
printf("textureAlignment : %d.\n", prop.textureAlignment);
printf("deviceOverlap : %d.\n", prop.deviceOverlap);
printf("multiProcessorCount : %d.\n", prop.multiProcessorCount);
}
bool InitCUDA()
{
int count;
cudaGetDeviceCount(&count);
if(count == 0){
fprintf(stderr, "There is no device.\n");
return false;
}
int i;
for(i = 0; i < count; i++)
{
cudaDeviceProp prop;
int status;
status = cudaGetDeviceProperties(&prop, i);
//printDeviceProp(prop);
if(status == cudaSuccess){
if(prop.major >= 1){
break;
}
}
}
printf("Total %d GPU\n", count);
if(i == count){
fprintf(stderr, "There is no device supporting cuda 1.x.\n");
return false;
}
cudaSetDevice(i+1);
return true;
}
void matgen(float* a, int n)
{
int i, j;
for(i = 0; i < n; i++){
for(j = 0; j < n; j++){
a[i * n + j] = (float)rand() / RAND_MAX + (float)rand() / (RAND_MAX * RAND_MAX);
}
}
}
__global__ static void matMultCUDA(const float* a, const float* b, float* c, int n, clock_t* time, int *e)
{
extern __shared__ float data[];
const int tid = threadIdx.x;
const int row = blockIdx.x;
int i, j;
//for(i = tid; i < n; i += THREAD_NUM){
for(i = tid; i < n; i += blockDim.x){
data[i] = a[row * n + i];
}
__syncthreads();
clock_t start;
if(tid == 0)
*e = blockDim.x;
time[row] = clock();
//for(j = tid; j < n; j += THREAD_NUM){
for(j = tid; j < n; j += blockDim.x){
float t = 0;
float y = 0;
for(i = 0; i < n; i++){
float r ;
y -= data[i] * b[i * n + j];
r = t - y;
y = (r - t) + y;
t = r;
}
c[row * n + j] = t;
}
if(tid == 0){
time[row + blocks_num] = clock();
}
}
int main()
{
if(!InitCUDA())
return 0;
float *a, *b, *c, *d;
int *e;
int n = MATRIX_SIZE;
a = (float*)malloc(sizeof(float) * n * n);
b = (float*)malloc(sizeof(float) *n * n);
c = (float*)malloc(sizeof(float) * n * n);
d = (float*)malloc(sizeof(float) * n * n);
e = (int*)malloc(sizeof(int) * n * n);
srand(0);
matgen(a, n);
matgen(b, n);
float *cuda_a, *cuda_b, *cuda_c;
int *cuda_e;
clock_t* time;
size_t pitch_a, pitch_b, pitch_c;
cudaMallocPitch((void**) &cuda_a, &pitch_a, sizeof(float) * n, n);
cudaMallocPitch((void**)&cuda_b, &pitch_b, sizeof(float) * n, n);
cudaMallocPitch((void**)&cuda_c, &pitch_c, sizeof(float) * n, n);
/*
cudaMalloc((void**)&cuda_a, sizeof(float) * n * n);
cudaMalloc((void**)&cuda_b, sizeof(float) * n * n);
cudaMalloc((void**)&cuda_c, sizeof(float) * n * n);
*/
cudaMalloc((void**)&cuda_e, sizeof(int));
cudaMalloc((void**)&time, sizeof(clock_t) * n * 2);
cudaMemcpy(cuda_a, a, sizeof(float) * n * n, cudaMemcpyHostToDevice);
cudaMemcpy(cuda_b, b, sizeof(float) * n * n, cudaMemcpyHostToDevice);
//matMultCUDA<<<blocks_num, THREAD_NUM, 0>>>(cuda_a, cuda_b, cuda_c, n, time);
matMultCUDA<<<n, THREAD_NUM, sizeof(float) * n >>> (cuda_a, cuda_b, cuda_c, n, time, cuda_e);
clock_t time_use[blocks_num * 2];
cudaMemcpy(c, cuda_c, sizeof(float) * n * n, cudaMemcpyDeviceToHost);
cudaMemcpy(e, cuda_e, sizeof(int), cudaMemcpyDeviceToHost);
cudaMemcpy(&time_use, time, sizeof(clock_t) * 2 * blocks_num, cudaMemcpyDeviceToHost);
cudaFree(cuda_a);
cudaFree(cuda_b);
cudaFree(cuda_c);
cudaFree(time);
printf("sizeof(c)= %d\n",sizeof(c));
printf("blockDim.x = %d\n", *e);
for(int i = 0; i < 10; i++)
printf("%f ", c[i]);
clock_t min_start, max_end;
min_start = time_use[0];
max_end = time_use[blocks_num];
for(int i = 1; i < blocks_num; i++){
if(min_start > time_use[i])
min_start = time_use[i];
if(max_end < time_use[i + blocks_num])
max_end = time_use[i + blocks_num];
}
clock_t final_time = max_end - min_start;
for(int i = 0; i < n; i++){
for(int j = 0; j < n; j++){
double t = 0;
for(int k = 0; k < n; k++){
t += a[i * n + k] * b[k * n + j];
}
d[i * n + j] = t;
}
}
float max_err = 0;
float average_err = 0;
for(int i = 0; i < n; i++){
for(int j = 0; j < n; j++){
if(d[i * n + j] != 0){
float err = fabs((c[i * n + j] - d[i * n + j]) / d[i * n + j]);
if(max_err < err)
max_err = err;
average_err += err;
}
}
}
printf("Max error: %g Average error: %g\n", max_err, average_err / (n*n));
printf("gputime: %d\n", final_time);
return 0;
}
|
9,790 | #include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define Uw 1.0
#define ERMAX 0.0000005
#define xp(i) (float)i*delta
#define yp(j) (float)j*delta
#define position(i,j) j*Nx+i
void Caller(void);
void CavityCompute(void);
int GetComputeCondition(void);
void ComputeMain(int check);
void ApplyIC(float *U, float *V, int Nx, int Ny);
void ApplyBCCPU(float *W, float *Wnew, float *Psi, int Nx, int Ny, float delta);
void VorticityCPU(float *U, float *V, float *W, float *Wnew, float *Psi, float dt, float delta, int ReN, int Nx, int Ny);
void StreamCPU(float *Wnew, float *Psi, float *Psinew, int Nx, int Ny, float delta );
void VeloCalcCPU(float *U, float *V, float *Psi, int Nx, int Ny, float delta);
float ErckCPU(float *W, float *Wnew, int Nx, int Ny);
void CavityCPU(float *U, float *V, float *W, float *Psi, int Nx, int Ny, float delta, int ReN, float dt);
void CavityCUDA(float *U, float *V, float *W, float *Psi, int Nx, int Ny, float delta, int ReN, float dt);
void ParaWriter(float *U, float *V, float *W, float *Psi, int ReN, float Lx, float Ly, float delta, float dt, int Nx, int Ny);
int main(int argc, char* argv[])
{
Caller();
return 0;
}
void Caller(void)
{
CavityCompute();
return;
}
int GetComputeCondition(void)
{
int check;
printf("1: CPU, 2: CUDA\n");
printf("Compute What? ");
scanf("%d", &check);
return check;
}
void CavityCompute(void)
{
int check = GetComputeCondition();
if((check != 1 )&& (check != 2))
{
printf("Wrong Input, Compute CPU\n");
check = 1;
}
ComputeMain(check);
return;
}
void ComputeMain(int check)
{
int ReN, Nx, Ny, N, SIZE;
float Lx, Ly, delta, dt;
printf("Input ReN: ");
scanf("%d", &ReN);
printf("Input Lx: ");
scanf("%f", &Lx);
printf("Input Ly: ");
scanf("%f", &Ly);
printf("Input Nx (X-Grid Counter): ");
scanf("%d", &Nx);
printf("Input dt: ");
scanf("%f", &dt);
delta = Lx / ((float)(Nx-1));
Ny = (int)(Ly/delta+1.0);
N = Nx*Ny;
SIZE = sizeof(float)*N;
printf("Reynolds Number: %d, X-Grid: %d, Y=Grid: %d, GridSize=%f, dt=%f\n", ReN, Nx, Ny, delta, dt);
float *U, *V, *W, *Psi;
U = (float *)malloc(SIZE);
V = (float *)malloc(SIZE);
W = (float *)malloc(SIZE);
Psi=(float *)malloc(SIZE);
if(check == 1)
CavityCPU(U, V, W, Psi, Nx, Ny, delta, ReN, dt);
else if(check ==2)
CavityCUDA(U, V, W, Psi, Nx, Ny, delta, ReN, dt);
ParaWriter(U, V, W, Psi, ReN, Lx, Ly, delta, dt, Nx, Ny);
free(U);
free(V);
free(W);
free(Psi);
}
void ApplyIC(float *U, float *V, int Nx, int Ny)
{
int i,j;
j = Ny-1;
for( i = 0 ; i < Nx ; i++)
{
int pos = position(i,j);
U[pos]=Uw;
}
return;
}
void ApplyBCCPU(float *W, float *Wnew, float *Psi, int Nx, int Ny, float delta)
{
int i, j, pos, SIZE=sizeof(float)*Nx*Ny;
for (i=0;i<Nx;i++)
{
j=0;
pos = position(i,j);
W[pos]=2.0*(Psi[pos]-Psi[pos+Nx])/(delta*delta);
j=Ny-1;
pos = position(i,j);
W[pos] = 2.0*(Psi[pos] - Psi[pos-Nx]) / (delta*delta) - 2.0*Uw/delta;
}
for(j=0;j<Ny;j++)
{
i=0;
pos=position(i,j);
W[pos]=2.0*(Psi[pos]-Psi[pos+1])/(delta*delta);
i=Nx-1;
pos=position(i,j);
W[pos]=2.0*(Psi[pos]-Psi[pos-1])/(delta*delta);
}
memcpy(Wnew, W, SIZE);
return;
}
void VorticityCPU(float *U, float *V, float *W, float *Wnew, float *Psi, float dt, float delta, int ReN, int Nx, int Ny)
{
int i, j, pos;
float c = 0.5*dt/delta;
float d = dt/((float)ReN*delta*delta);
for(j=1;j<Ny-1;j++)
{
for(i=1;i<Nx-1;i++)
{
pos=position(i,j);
Wnew[pos] = (1.0 - 4.0 * d);
}
}
return;
}
void CavityCPU(float *U, float *V, float *W, float *Psi, int Nx, int Ny, float delta, int ReN, float dt)
{
float *Wnew,*Psinew;
int N=Nx*Ny;
int SIZE=sizeof(float)*N;
Wnew = (float *)malloc(SIZE);
Psinew = (float *)malloc(SIZE);
memset(U, 0.0, SIZE);
memset(V, 0.0, SIZE);
memset(W, 0.0, SIZE);
memset(Wnew, 0.0, SIZE);
memset(Psi, 0.0, SIZE);
memset(Psinew, 0.0, SIZE);
float timer = 0.0, error = 0.0;
int iter = 0;
ApplyIC(U, V, Nx, Ny);
do{
ApplyBCCPU(W, Wnew, Psi, Nx, Ny, delta);
VorticityCPU(U, V, W, Wnew, Psi, dt, delta, ReN, Nx, Ny);
StreamCPU(Wnew, Psi, Psinew, Nx, Ny, delta);
VeloCalcCPU(U, V, Psi, Nx, Ny, delta);
iter++;
timer += dt;
error = ErckCPU(W, Wnew, Nx, Ny);
printf("Time: %.6f, Iter: %d, Error: %.9f\r", timer, iter, error);
memcpy(W, Wnew, SIZE);
} while(error >= ERMAX);
printf("\n");
free(Wnew);
free(Psinew);
return;
}
void CavityCUDA(float *U, float *V, float *W, float *Psi, int Nx, int Ny, float delta, int ReN, float dt)
{
return;
}
void ParaWriter(float *U, float *V, float *W, float *Psi, int ReN, float Lx, float Ly, float delta, float dt, int Nx, int Ny)
{
FILE *PR;
char name[150] = "Error";
sprintf(name, "Cavity, Re=%d, delta=%f, Lx=%.1f, Ly=%.1f, dt=%f.csv", ReN, delta, Lx, Ly, dt);
PR = fopen(name, "w");
int i,j;
fprintf(PR,"X,Y,U,V,Vorticity,StreamFunction\n");
for( j = 0 ; j < Ny ; j++ )
{
for( i = 0 ; i < Nx ; i++ )
{
float x = xp(i);
float y = yp(j);
int pos = position(i, j);
fprintf(PR, "%f,%f,%f,%f,%f,%f\n", x,y,U[pos],V[pos],W[pos],Psi[pos]);
}
}
fclose(PR);
return;
}
|
9,791 | //
// include files
//
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
// #define BLOCK_NUM 16
// #define THREAD_NUM 64
#define N 1024*1024
static void cuda_checker(cudaError_t err, const char *file, int line ) {
if (err != cudaSuccess) {
printf("%s in %s at line %d\n", cudaGetErrorString(err), file, line);
exit(EXIT_FAILURE);
}
}
#define CUDA_CHECK(err) (cuda_checker(err, __FILE__, __LINE__ ))
//
// kernel code
//
__global__ void add(int *a, int *b, int *c, int *d, int *e, int *f, int *g) {
int tid = blockIdx.x; // handle the data at this index
int local[6];
local[0] = a[tid];
local[1] = b[tid];
local[2] = c[tid];
local[3] = d[tid];
local[4] = e[tid];
local[5] = f[tid];
__syncthreads();
if(tid < N) {
int sum = 0;
for (int i = 0; i < 6; ++i) {
sum += local[i];
}
g[tid] = sum;
}
}
//
// host code
//
int main(int argc, const char **argv) {
int *a, *b, *c, *d, *e, *f, *g;
int *dev_a, *dev_b, *dev_c, *dev_d, *dev_e, *dev_f, *dev_g;
a = (int*) malloc(sizeof(int) * N);
b = (int*) malloc(sizeof(int) * N);
c = (int*) malloc(sizeof(int) * N);
d = (int*) malloc(sizeof(int) * N);
e = (int*) malloc(sizeof(int) * N);
f = (int*) malloc(sizeof(int) * N);
g = (int*) malloc(sizeof(int) * N);
for(int i = 0; i < N; i++) {
a[i] = -i;
b[i] = -i;
c[i] = -i;
d[i] = i * i;
e[i] = i * i;
f[i] = i * i;
}
CUDA_CHECK( cudaMalloc((void**)&dev_a, N * sizeof(int)) );
CUDA_CHECK( cudaMalloc((void**)&dev_b, N * sizeof(int)) );
CUDA_CHECK( cudaMalloc((void**)&dev_c, N * sizeof(int)) );
CUDA_CHECK( cudaMalloc((void**)&dev_d, N * sizeof(int)) );
CUDA_CHECK( cudaMalloc((void**)&dev_e, N * sizeof(int)) );
CUDA_CHECK( cudaMalloc((void**)&dev_f, N * sizeof(int)) );
CUDA_CHECK( cudaMalloc((void**)&dev_g, N * sizeof(int)) );
CUDA_CHECK( cudaMemcpy(dev_a, a, N * sizeof(int), cudaMemcpyHostToDevice) );
CUDA_CHECK( cudaMemcpy(dev_b, b, N * sizeof(int), cudaMemcpyHostToDevice) );
CUDA_CHECK( cudaMemcpy(dev_c, c, N * sizeof(int), cudaMemcpyHostToDevice) );
CUDA_CHECK( cudaMemcpy(dev_d, d, N * sizeof(int), cudaMemcpyHostToDevice) );
CUDA_CHECK( cudaMemcpy(dev_e, e, N * sizeof(int), cudaMemcpyHostToDevice) );
CUDA_CHECK( cudaMemcpy(dev_f, f, N * sizeof(int), cudaMemcpyHostToDevice) );
float time;
cudaEvent_t start, stop;
CUDA_CHECK(cudaEventCreate(&start));
CUDA_CHECK(cudaEventCreate(&stop));
CUDA_CHECK(cudaEventRecord(start, 0));
add<<<1024,N/1024>>>(dev_a, dev_b, dev_c, dev_d, dev_e, dev_f, dev_g);
CUDA_CHECK( cudaMemcpy(g, dev_g, N * sizeof(int), cudaMemcpyDeviceToHost) );
CUDA_CHECK(cudaEventRecord(stop, 0));
CUDA_CHECK(cudaEventSynchronize(stop));
CUDA_CHECK(cudaEventElapsedTime(&time, start, stop));
printf("Time to generate: %3.1f ms \n", time);
// for( int i = 0; i < N; i++ ){
// printf( "cpu: %d, gpu: %d\n", a[i]+b[i], c[i]);
// }
CUDA_CHECK( cudaFree(dev_a) );
CUDA_CHECK( cudaFree(dev_b) );
CUDA_CHECK( cudaFree(dev_c) );
CUDA_CHECK( cudaFree(dev_d) );
CUDA_CHECK( cudaFree(dev_e) );
CUDA_CHECK( cudaFree(dev_f) );
CUDA_CHECK( cudaFree(dev_g) );
cudaDeviceReset();
return 0;
}
|
9,792 | //
// Created by DJtheRedstoner on 5/4/2021.
//
class SimpleRandom {
private:
const static long long multiplier = 0x5DEECE66D;
const static long long mask = (1LL << 48) - 1;
long long seed = 0LL;
public:
__device__
void setSeed(long long newSeed) {
seed = (newSeed ^ multiplier) & mask;
}
__device__
int nextInt(int bound) {
int r = next();
int m = bound - 1;
if ((bound & m) == 0)
r = (int)((bound * (long long)r) >> 31);
else {
int u = r;
while (u - (r = u % bound) + m < 0) u = next();
}
return r;
}
private:
__device__
int next() {
seed = (seed * multiplier + 0xBLL) & mask;
return (int)(seed >> 17);
}
};
|
9,793 | #include "includes.h"
__global__ void square(float *d_in, float *d_out)
{
int index = threadIdx.x;
float f = d_in[index];
d_out[index] = f * f;
} |
9,794 | /*
* HzUpdaterTE.cpp
*
* Created on: 29 янв. 2016 г.
* Author: aleksandr
*/
#include "HzUpdaterTE.h"
#include "SmartIndex.h"
// o o o o x
// o o o o x
// o o o o x
// o o o o x
// x x x x x
__host__ __device__
void HzUpdaterTE::operator() (const int indx) {
// m и n - индексы в полноценных массивах
// sizeY - размер полноценнго массива
int m = indx/(sizeY);
int n = indx%(sizeY);
float Chze = S / 377.0;
if ( (m<sizeX-1) && (n<sizeY-1) ) {
Hz(m, n) = Hz(m, n) + Chze*((Ex(m, n + 1) - Ex(m, n)) - (Ey(m + 1, n) - Ey(m, n)));
}
}
|
9,795 | #include "includes.h"
#define NTHREADS 512
// Updates the column norms by subtracting the Hadamard-square of the
// Householder vector.
//
// N.B.: Overflow incurred in computing the square should already have
// been detected in the original norm construction.
__global__ void UpdateHHNorms(int cols, float *dV, float *dNorms) {
// Copyright 2009, Mark Seligman at Rapid Biologics, LLC. All rights
// reserved.
int colIndex = threadIdx.x + blockIdx.x * blockDim.x;
if (colIndex < cols) {
float val = dV[colIndex];
dNorms[colIndex] -= val * val;
}
} |
9,796 | // Author: Ayush Kumar
// Roll No: 170195
// Compile: nvcc -g -G -arch=sm_61 -std=c++11 assignment5-p4.cu -o assignment5-p4
#include <cmath>
#include <cuda.h>
#include <iostream>
#include <sys/time.h>
typedef unsigned long long int uint64_cu;
const uint64_cu N = (1 << 12);
#define BLOCK_SIZE 32
#define THRESHOLD (0.000001)
using std::cerr;
using std::cout;
using std::endl;
__global__ void kernel1(uint64_cu* d_A, uint64_cu* d_B, uint64_cu* d_C) {
// TODO: Fill in
int i = blockIdx.y * blockDim.y + threadIdx.y;
int j = blockIdx.x * blockDim.x + threadIdx.x;
for (int k = 0; k < N; k++) {
d_C[i*N + j] += d_A[i*N + k] * d_B[k*N + j];
}
}
__global__ void kernel2(uint64_cu* d_A, uint64_cu* d_B, uint64_cu* d_C) {
// TODO: Fill in
// Block row and column
int block_i = blockIdx.y;
int block_j = blockIdx.x;
// Each thread block computes one sub-matrix B_sub of B
uint64_cu* C_sub = &d_C[block_i * blockDim.y * N + block_j * blockDim.x];
// Each thread computes one element of B_sub
// by accumulating results into B_value
uint64_cu C_value = 0;
// Thread row and column within B_sub
int thread_i = threadIdx.y;
int thread_j = threadIdx.x;
// Loop over all the sub-matrices of A^T and A that are
// required to compute B_sub
// Multiply each pair of sub-matrices together
// and accumulate the results
for (int m = 0; m < N/blockDim.x; m++) {
// Get sub-matrix AT_sub of AT
uint64_cu* A_sub = &d_A[block_i * blockDim.y * N + m * blockDim.x];
// Get sub-matrix A_sub of A
uint64_cu* B_sub = &d_B[m * blockDim.y * N + block_j * blockDim.x];
// Shared memory used to store AT_sub and A_sub respectively
__shared__ uint64_cu As[BLOCK_SIZE][BLOCK_SIZE];
__shared__ uint64_cu Bs[BLOCK_SIZE][BLOCK_SIZE];
// Load AT_sub and A_sub from device memory to shared memory
// Each thread loads one element of each sub-matrix
As[thread_i][thread_j] = A_sub[thread_i * N + thread_j];
Bs[thread_i][thread_j] = B_sub[thread_i * N + thread_j];
// Synchronize to make sure the sub-matrices are loaded
// before starting the computation
__syncthreads();
// Multiply AT_sub and A_sub together
for (int k = 0; k < BLOCK_SIZE; k += 16) {
C_value += As[thread_i][k] * Bs[k][thread_j];
C_value += As[thread_i][k+1] * Bs[k+1][thread_j];
C_value += As[thread_i][k+2] * Bs[k+2][thread_j];
C_value += As[thread_i][k+3] * Bs[k+3][thread_j];
C_value += As[thread_i][k+4] * Bs[k+4][thread_j];
C_value += As[thread_i][k+5] * Bs[k+5][thread_j];
C_value += As[thread_i][k+6] * Bs[k+6][thread_j];
C_value += As[thread_i][k+7] * Bs[k+7][thread_j];
C_value += As[thread_i][k+8] * Bs[k+8][thread_j];
C_value += As[thread_i][k+9] * Bs[k+9][thread_j];
C_value += As[thread_i][k+10] * Bs[k+10][thread_j];
C_value += As[thread_i][k+11] * Bs[k+11][thread_j];
C_value += As[thread_i][k+12] * Bs[k+12][thread_j];
C_value += As[thread_i][k+13] * Bs[k+13][thread_j];
C_value += As[thread_i][k+14] * Bs[k+14][thread_j];
C_value += As[thread_i][k+15] * Bs[k+15][thread_j];
}
// Synchronize to make sure that the preceding
// computation is done before loading two new
// sub-matrices of AT and A in the next iteration
__syncthreads();
}
// Write B_sub to device memory
// Each thread writes one element
C_sub[thread_i * N + thread_j] = C_value;
}
__host__ void cpumatMul(uint64_cu* h_A, uint64_cu* h_B, uint64_cu* h_C) {
for (uint64_cu i = 0; i < N; i++) {
for (uint64_cu j = 0; j < N; j++) {
float sum = 0.0;
for (uint64_cu k = 0; k < N; k++) {
sum += h_A[i * N + k] * h_B[k * N + j];
}
h_C[i * N + j] = sum;
}
}
}
__host__ void check_result(uint64_cu* w_ref, uint64_cu* w_opt) {
bool wrong = false;
for (uint64_cu i = 0; i < N; i++) {
for (uint64_cu j = 0; j < N; j++) {
if (w_ref[i * N + j] != w_opt[i * N + j]) {
wrong = true;
goto out;
}
}
}
out:
if (wrong) {
cout << " Diffs found!" << endl;
} else {
cout << "No differences found between base and test versions\n";
}
}
double rtclock() { // Seconds
struct timezone Tzp;
struct timeval Tp;
int stat;
stat = gettimeofday(&Tp, &Tzp);
if (stat != 0) {
cout << "Error return from gettimeofday: " << stat << "\n";
}
return (Tp.tv_sec + Tp.tv_usec * 1.0e-6);
}
int main() {
uint64_cu SIZE = N * N;
uint64_cu *h_A, *h_B, *h_cpu_C, *h_gpu1_C, *h_gpu2_C;
h_A = (uint64_cu*)malloc(SIZE * sizeof(uint64_cu));
h_B = (uint64_cu*)malloc(SIZE * sizeof(uint64_cu));
h_cpu_C = (uint64_cu*)malloc(SIZE * sizeof(uint64_cu));
h_gpu1_C = (uint64_cu*)malloc(SIZE * sizeof(uint64_cu));
h_gpu2_C = (uint64_cu*)malloc(SIZE * sizeof(uint64_cu));
for (uint64_cu i = 0; i < N; i++) {
for (uint64_cu j = 0; j < N; j++) {
h_A[i * N + j] = rand() % 64;
h_B[i * N + j] = 2;
h_cpu_C[i * N + j] = 0;
h_gpu1_C[i * N + j] = 0;
h_gpu2_C[i * N + j] = 0;
}
}
double clkbegin = rtclock();
cpumatMul(h_A, h_B, h_cpu_C);
double clkend = rtclock();
double cpu_time = clkend - clkbegin;
cout << "Matmul time on CPU: " << cpu_time * 1000 << " msec" << endl;
cudaError_t status;
cudaEvent_t start, end;
float kernel_time;
uint64_cu *d_A, *d_B, *d_C1;
// // if (status != cudaSuccess) {
// // cerr << cudaGetErrorString(status) << endl;
// // }
status = cudaMalloc(&d_A, SIZE * sizeof(uint64_cu));
status = cudaMalloc(&d_B, SIZE * sizeof(uint64_cu));
status = cudaMalloc(&d_C1, SIZE * sizeof(uint64_cu));
dim3 threads_in_block1(32, 32);
dim3 blocks_in_grid1(N/threads_in_block1.x, N/threads_in_block1.y);
cudaEventCreate(&start);
cudaEventCreate(&end);
cudaEventRecord(start, 0);
/************** CUDA **************/
status = cudaMemcpy(d_A, h_A, SIZE * sizeof(uint64_cu), cudaMemcpyHostToDevice);
status = cudaMemcpy(d_B, h_B, SIZE * sizeof(uint64_cu), cudaMemcpyHostToDevice);
status = cudaMemset(d_C1, 0, SIZE * sizeof(uint64_cu));
// TODO: Fill in
kernel1<<<blocks_in_grid1, threads_in_block1>>>(d_A, d_B, d_C1);
cudaMemcpy(h_gpu1_C, d_C1, SIZE * sizeof(uint64_cu), cudaMemcpyDeviceToHost);
/************** CUDA **************/
cudaEventRecord(end, 0);
cudaEventSynchronize(end);
cudaEventElapsedTime(&kernel_time, start, end);
cudaEventDestroy(start);
cudaEventDestroy(end);
check_result(h_cpu_C, h_gpu1_C);
std::cout << "Kernel 1 time (ms): " << kernel_time << "\n";
status = cudaGetLastError();
if (status != cudaSuccess) {
cerr << cudaGetErrorString(status) << endl;
}
uint64_cu* d_C2;
status = cudaMalloc(&d_C2, SIZE * sizeof(uint64_cu));
dim3 threads_in_block2(BLOCK_SIZE, BLOCK_SIZE);
dim3 blocks_in_grid2(N/threads_in_block2.x, N/threads_in_block2.y);
cudaEventCreate(&start);
cudaEventCreate(&end);
cudaEventRecord(start, 0);
/************** CUDA **************/
status = cudaMemcpy(d_A, h_A, SIZE * sizeof(uint64_cu), cudaMemcpyHostToDevice);
status = cudaMemcpy(d_B, h_B, SIZE * sizeof(uint64_cu), cudaMemcpyHostToDevice);
status = cudaMemset(d_C2, 0, SIZE * sizeof(uint64_cu));
// TODO: Fill in
kernel2<<<blocks_in_grid2, threads_in_block2>>>(d_A, d_B, d_C2);
cudaMemcpy(h_gpu2_C, d_C2, SIZE * sizeof(uint64_cu), cudaMemcpyDeviceToHost);
/************** CUDA **************/
cudaEventRecord(end, 0);
cudaEventSynchronize(end);
cudaEventElapsedTime(&kernel_time, start, end);
cudaEventDestroy(start);
cudaEventDestroy(end);
check_result(h_cpu_C, h_gpu2_C);
std::cout << "Kernel 2 time (ms): " << kernel_time << "\n";
status = cudaGetLastError();
if (status != cudaSuccess) {
cerr << cudaGetErrorString(status) << endl;
}
cudaFree(d_A);
cudaFree(d_B);
// cudaFree(d_C1);
cudaFree(d_C2);
free(h_A);
free(h_B);
free(h_cpu_C);
free(h_gpu1_C);
free(h_gpu2_C);
return EXIT_SUCCESS;
}
|
9,797 | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
__global__ void ReducePI(
float* d_sum,
int num
);
__global__ void ReducePI2(
float* d_sum,
int num,
float* d_pi
);
int __main()
{
return 0;
}
__global__ void ReducePI(
float* d_sum,
int num
){
int id = blockIdx.x * blockDim.x + threadIdx.x;
int gid = id;
float temp;
extern float __shared__ s_pi[];
s_pi[threadIdx.x] = 0.f;
while(gid < num){
temp = (gid + 0.5) / num;
s_pi[threadIdx.x] += 4.0f / (1 + temp*temp);
gid = blockDim.x * gridDim.x;
}
for(int i=(blockIdx.x >> 1); i>0; i++){
if(threadIdx.x < i){
s_pi[threadIdx.x] += s_pi[threadIdx.x+i];
}
__syncthreads();
}
if(threadIdx.x == 0){
d_sum[blockIdx.x] = s_pi[0];
}
}
__global__ void ReducePI2(
float* d_sum,
int num,
float* d_pi
){
int id=threadIdx.x;
extern float __shared__ s_sum[];
s_sum[id]=d_sum[id];
__syncthreads();
for(int i=(blockDim.x>>1);i>0;i>>=1){
if(id<i)
s_sum[id]+=s_sum[id+i];
__syncthreads();
}
printf("%d,%f\n",id,s_sum[id]);
if(id==0){
*d_pi=s_sum[0]/num;
printf("%d,%f\n",id,*d_pi);
}
} |
9,798 | extern "C"
__global__ void add(int n, float *a, float *sum)
{
int i = threadIdx.x + blockDim.x * blockIdx.x;
if (i<n)
{
for (int j = 0; j < n; j++)
{
sum[i] = sum[i] + a[i*n + j];
}
}
} |
9,799 | /*****************************************************************************
Example : cuda-PI-computation.cu
Objective : Write a CUDA Program to calculate value of PI using numerical integration method..
Input : None
Output : Execution time in seconds
Created : Aug 2011
E-mail : RarchK
****************************************************************************/
// This is code for Pi calculation....
#include<stdio.h>
#include<cuda.h>
#define BLOCKSIZE 16
#define SIZE 1024
#define EPS 1.0e-15
cudaDeviceProp deviceProp;
double *host_Vect,*host_Result,cpu_Result;
double *device_Vect,*device_Result,totalsum;
int vlength ;
int device_Count;
int noOfIntervals = SIZE;
/*mem error*/
void mem_error(char *arrayname, char *benchmark, int len, char *type)
{
printf("\nMemory not sufficient to allocate for array %s\n\tBenchmark : %s \n\tMemory requested = %d number of %s elements\n",arrayname, benchmark, len, type);
exit(-1);
}
/*sequential function for Pi calculation*/
void CPU_PiCalculation()
{
double x;
double h = 1.0 / noOfIntervals;
int i;
for (i = 1; i < noOfIntervals +1; i = i+1)
{
x = h * (i + 0.5);
cpu_Result = cpu_Result + 4.0/(1.0 + x * x);
}
cpu_Result = cpu_Result * h;
}
/*Check for safe return of all calls to the device */
void CUDA_SAFE_CALL(cudaError_t call)
{
cudaError_t ret = call;
//printf("RETURN FROM THE CUDA CALL:%d\t:",ret);
switch(ret)
{
case cudaSuccess:
// printf("Success\n");
break;
/* case cudaErrorInvalidValue:
{
printf("ERROR: InvalidValue:%i.\n",__LINE__);
exit(-1);
break;
}
case cudaErrorInvalidDevicePointer:
{
printf("ERROR:Invalid Device pointeri:%i.\n",__LINE__);
exit(-1);
break;
}
case cudaErrorInvalidMemcpyDirection:
{
printf("ERROR:Invalid memcpy direction:%i.\n",__LINE__);
exit(-1);
break;
} */
default:
{
printf(" ERROR at line :%i.%d' ' %s\n",__LINE__,ret,cudaGetErrorString(ret));
exit(-1);
break;
}
}
}
/* function to calculate relative error*/
void relError(int noOfIntervals,double *host_Result)
{
int flag=0;
double errorNorm = 0.0;
double eps=EPS;
double relativeError=0.0;
relativeError = ((cpu_Result - ((*host_Result))) / cpu_Result);
if (relativeError > eps && relativeError != 0.0e+00 )
{
if(errorNorm < relativeError)
{
errorNorm = relativeError;
flag=1;
}
}
if( flag == 1) {
printf(" \nresult failed");
}
if(flag==0)
{
printf("\n\n\t\t Result Verification: success\n\n");
}
}
/*prints the result in screen*/
void print_on_screen(char * program_name,float tsec,double gflops,int noOfIntervals,int flag)//flag=1 if gflops has been calculated else flag =0
{
printf("\n---------------%s----------------\n",program_name);
printf("\tNoOfIntervals\t TIME_SEC\t Gflops\n");
if(flag==1)
printf("\t%d\t\t%f\t%lf\t",noOfIntervals,tsec,gflops);
else
printf("\t%d\t\t %lf\t %s\t",noOfIntervals,tsec,"---");
}
/*funtion to check blocks per grid and threads per block*/
void check_block_grid_dim(cudaDeviceProp devProp,dim3 blockDim,dim3 gridDim)
{
if( blockDim.x >= devProp.maxThreadsDim[0] || blockDim.y >= devProp.maxThreadsDim[1] || blockDim.z >= devProp.maxThreadsDim[2] )
{
printf("\nBlock Dimensions exceed the maximum limits:%d * %d * %d \n",devProp.maxThreadsDim[0],devProp.maxThreadsDim[1],devProp.maxThreadsDim[2]);
exit(-1);
}
if( gridDim.x >= devProp.maxGridSize[0] || gridDim.y >= devProp.maxGridSize[1] || gridDim.z >= devProp.maxGridSize[2] )
{
printf("\nGrid Dimensions exceed the maximum limits:%d * %d * %d \n",devProp.maxGridSize[0],devProp.maxGridSize[1],devProp.maxGridSize[2]);
exit(-1);
}
}
/*Get the number of GPU devices present on the host */
int get_DeviceCount()
{
int count;
cudaGetDeviceCount(&count);
return count;
}
/////////////////////////////////////////////////////////////////////////////////////////
//
// Pi calculation : this kernel will perform Pi calculation
//
/////////////////////////////////////////////////////////////////////////////////////////
__global__ void PiCalculation(double *dIntervalLocalValue,double numInterval, int threadDim)
{
int tidx = threadIdx.x;
int tidy = threadIdx.y;
int tindex = (threadDim * tidx) + tidy;
int maxNumThread = threadDim * threadDim;
int intervalCount ;
double tempResult = 0.0;
double h = 1.0 / numInterval;
double sum = 0.0;
double x = 0.0;
dIntervalLocalValue[tindex] = 0.0;
for( intervalCount = tindex + 1; intervalCount <= numInterval; intervalCount += maxNumThread )
{
x = h * ( (double)intervalCount - 0.5 );
sum += (4.0 /(1.0 + x*x));
}
dIntervalLocalValue[tindex] = h * sum;
__syncthreads();
if( tindex == 0 )
{
tempResult = 0.0f;
for( intervalCount = 0; intervalCount < maxNumThread; intervalCount++)
tempResult += dIntervalLocalValue[intervalCount];
dIntervalLocalValue[0] = tempResult;
}
}//end of Pi calculation function
/*function to launch kernel*/
void launch_Kernel_PiCalculation()
{
/* threads_per_block, blocks_per_grid */
dim3 dimBlock(BLOCKSIZE,BLOCKSIZE);
dim3 dimGrid(1,1);
check_block_grid_dim(deviceProp,dimBlock,dimGrid);
PiCalculation<<<dimGrid,dimBlock>>>(device_Result,noOfIntervals,BLOCKSIZE);
}
/*main function*/
int main()
{
double gflops=0.0;
vlength = SIZE;
float elapsedTime,Tsec;
cudaEvent_t start,stop;
host_Result = (double*) malloc( sizeof(double));
device_Count=get_DeviceCount();
printf("\n\nNUmber of Devices : %d\n\n", device_Count);
// Device Selection, Device 1: Tesla C1060
cudaSetDevice(0);
int device;
// Current Device Detection
cudaGetDevice(&device);
cudaGetDeviceProperties(&deviceProp,device);
printf("Using device %d: %s \n", device, deviceProp.name);
/* allocate memory for GPU events
start = (cudaEvent_t) malloc (noOfIntervalsof(cudaEvent_t));
stop = (cudaEvent_t) malloc (noOfIntervalsof(cudaEvent_t));
if(start==NULL)
mem_error("start","Pi calculation",1,"cudaEvent_t");
if(stop==NULL)
mem_error("stop","Pi calculation",1,"cudaEvent_t");*/
//event creation...
CUDA_SAFE_CALL(cudaEventCreate (&start));
CUDA_SAFE_CALL(cudaEventCreate (&stop));
//allocating memory on GPU
CUDA_SAFE_CALL(cudaMalloc( (void**)&device_Result, sizeof(double)));
// Launching kernell..........
CUDA_SAFE_CALL(cudaEventRecord (start, 0));
launch_Kernel_PiCalculation();
CUDA_SAFE_CALL(cudaEventRecord (stop, 0));
CUDA_SAFE_CALL(cudaEventSynchronize (stop));
CUDA_SAFE_CALL(cudaEventElapsedTime ( &elapsedTime, start, stop));
Tsec= 1.0e-3*elapsedTime;
//printing the result on screen
print_on_screen("PiCalculation",Tsec,gflops,noOfIntervals,0);
//retriving result from device
CUDA_SAFE_CALL(cudaMemcpy((void *)host_Result, (void *)device_Result,sizeof(double),cudaMemcpyDeviceToHost));
// CPU calculation..and checking error deviation....
CPU_PiCalculation();
relError(noOfIntervals,host_Result);
printf("\n ----------------------------------------------------------------------\n");
//free host memory----------
free(host_Result);
return 0;
}// end of main
|
9,800 | #include <memory>
#include <iostream>
#include <cuda_runtime.h>
#include <cstdio>
#include <cstring> // memset
int main(void)
{
int device;
cudaDeviceProp device_property;
cudaGetDevice(&device);
printf("ID of device: %d\n", device);
memset(&device_property, 0, sizeof(cudaDeviceProp));
device_property.major = 1;
device_property.minor = 3;
cudaChooseDevice(&device, &device_property);
printf("ID of device which supports double precision is: %d\n", device);
cudaSetDevice(device);
}
|
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