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#include<stdio.h> __global__ void parallel_vector_add(int *d_a, int *d_b, int *d_c, int *d_n){ int i = (blockIdx.x*blockDim.x)+threadIdx.x ; printf("I am thread #%d\n", i) ; if(i < *d_n){ printf("T am about to compute c[%d].\n", i) ; d_c[i] = d_a[i] + d_b[i] ; } else{ printf("I am doing nothing.\n") ; } } ...
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/* Non-separable 2D, 3D and 4D Filtering with CUDA Copyright (C) <2013> Anders Eklund, andek034@gmail.com 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 3 of the Licens...
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#include <cuda.h> #include <cuda_runtime.h> #include <thrust/device_vector.h> #include <thrust/generate.h> #include <thrust/host_vector.h> #include <algorithm> #include <cstdio> #include "a.cuh" void test(int offset) { printf("start\n"); thrust::device_vector<int> X(2 << offset); std::generate(X.begin(),...
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/* #include "KernelDependencies.h" // TODO: teste collecting cells first and intersecting later. reduces registers, // but without mem coalescing it is actually 1/3 original performance (300fps for 1 triangle) // Kernel dependencies #include "KernelDependencies.h" // Global constants static __device__ const float...
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#include <stdio.h> #include <assert.h> #include <iostream> #include <cuda.h> #include <cuda_runtime.h> #include <limits> #ifndef MAX #define MAX(a,b) (a > b ? a : b) #endif __global__ void vectorAddGPU(float *a, float *b, float *c, int N, int offset) { int idx = blockIdx.x*blockDim.x + threadIdx.x; if (...
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#include <iostream> #include <stdio.h> #include <cuda_runtime.h> #include <chrono> __global__ void warmingup(float *c) { int tid = blockIdx.x*blockDim.x + threadIdx.x; float a, b; a=b=0.0f; if (tid%2==0){ a=100.0f; } else { b=200.0f; } c[tid] = a+b; } __global__ void mathKernel1(float *c) { in...
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#include <stdio.h> #include <stdlib.h> #include <cuda_runtime.h> #include <iostream> #include <fstream> #include <sstream> #include <vector> #include "assert.h" using namespace std; std::vector<int> readFile(string filename) { ifstream infile (filename); vector<int> vnum; string line; int index = 0; ...
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#include "cuda_runtime.h" #include <iostream> __global__ void empty() {} int main() { int device_id = 0; cudaSetDevice(device_id); cudaStream_t stream; cudaStreamCreate(&stream); cudaEvent_t start, end; cudaEventCreate(&start); cudaEventCreate(&end); int repeat = 1000; cudaEventRecord(start, str...
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__device__ float fracf(float x) { return x - floorf(x); } __device__ float random (float s, float t, float *rSeed) { return fracf(sinf(s*12.98123198*rSeed[0] + t*78.231233*rSeed[1])*43758.5453123); } __device__ float fitness( float p1x, float p1y, float p2x, float p2y, float p3x, float p3y, float *obs,...
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// Matrix addition, CPU version // gcc matrix_cpu.c -o matrix_cpu -std=c99 #include <stdio.h> #include <math.h> void printDeviceProperties(){ cudaDeviceProp prop; cudaGetDeviceProperties(&prop, 0); printf(" Device name: %s\n", prop.name); printf(" Memory Clock Rate (KHz): %d\n", prop.memoryClockRate); pri...
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/* * Module : Twine * Copyright : [2016..2017] Trevor L. McDonell * License : BSD3 * * Maintainer : Trevor L. McDonell <tmcdonell@cse.unsw.edu.au> * Stability : experimental * Portability : non-portable (GHC extensions) * * Convert between Accelerate's Struct-of-Array representation of complex *...
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#include <iostream> #include "../include/gdeque.h" #include <thrust/device_vector.h> #define def_dvec(t) thrust::device_vector<t> #define to_ptr(x) thrust::raw_pointer_cast(&x[0]) using namespace std; __global__ void test(float *output){ gpu_stl::deque<float> deque; int idx = 0; output[idx++] = deque.empt...
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#include "includes.h" __global__ void doNothing() {}
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#include <stdio.h> #include <cuda.h> // size of array #define N 4096 //vector addition kernel __global__ void vectorAddKernel(int *a, int *b, int *c) { int tdx = blockIdx.x * blockDim.x + threadIdx.x; if(tdx < N) { c[tdx] = a[tdx] + b[tdx]; } } int main(void) { cudaSetDevice(3); // grid and block sizes dim...
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#include "includes.h" __global__ void kernel ( void ) { }
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#include<iostream> #define SECTION_SIZE 32 using namespace std; __global__ void Prefix_sum_oneblock_kernel(float *X, float *Y, int InputSize, float *S) { __shared__ float XY[SECTION_SIZE]; int i = blockIdx.x*blockDim.x+ threadIdx.x; XY[threadIdx.x] = X[i]; /*if (i < InputSize && threadIdx.x != 0) { ...
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#include <stdio.h> #include <cuda.h> const int MAX_THREAD_NUMBER = 1000000; __device__ long long counterArray[MAX_THREAD_NUMBER] = {0}; extern "C" __device__ void bambooProfile(long bambooIndex) { int blockId = blockIdx.x + blockIdx.y * gridDim.x + gridDim.x * gridDim.y * blockIdx.z; long long index = blockI...
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/* Implementing parallell plus reduce in CUDA. */ #include <stdio.h> #define NUM_THREADS 16 #define NUM_BLOCKS 8 unsigned int serial_reduce(unsigned int* array, const unsigned int size){ unsigned int sum = 0; for(int i = 0; i < size; i++){ sum += array[i]; } return sum; } __global__ void re...
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// Corresponding header file: /include/mirror_ops.h #include <cuda_runtime.h> #include <stdio.h> /* Mirror operations */ __global__ void mirror(const uchar4* const inputChannel, uchar4* outputChannel, int numRows, int numCols, bool vertical) { int col = blockIdx.x * blockDim.x + threadIdx.x; int row = blockI...
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__global__ void vecAdd(float *in1, float *in2, float *out, int len) { int i = threadIdx.x + blockDim.x * blockIdx.x; if (i < len) out[i] = in1[i] + in2[i]; } int main(int argc, char **argv) { int inputLength = 1<<28; float *hostInput1; float *hostInput2; float *hostOutput; /*hostInput1 = (float*...
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// // Created by heidies on 7/8/18. // #include <cuda_runtime.h> #include <iostream> #include <sys/time.h> using namespace std; #define CHECK(call) \ { \ const cudaError...
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#include <stdio.h> #define CUCHK(call) { \ cudaError_t err = call; \ if( cudaSuccess != err) { \ fprintf(stderr, "Cuda error in file '%s' in line %i : %s.\n", \ ...
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#include "includes.h" __global__ void Dx_Forward_Kernel(float* output, const float* input, const int width, const int height, const int nChannels) { int x = threadIdx.x + blockIdx.x * blockDim.x; int y = threadIdx.y + blockIdx.y * blockDim.y; if (x >= width || y >= height) return; int offset = y*width + x; if (x == w...
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#include <cuda.h> __global__ void deviceburst(float *x, float *initsums, int n, int k, float *bigmaxs, int *startend) { int partition = (n - k + 1) / (blockDim.x * gridDim.x) + 1; int me = blockIdx.x * blockDim.x + threadIdx.x; int left = me * partition; int left_limit = left + partition; int length = k; ...
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#include <cuda_runtime.h> #include <cstdio> __global__ void my_kernel() { int tid = threadIdx.x; printf("Hello CUDA %d.\n", tid); } int main() { my_kernel<<<1, 8>>>(); cudaDeviceSynchronize(); }
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#include <stdio.h> #include <cuda_runtime.h> #include <cufft.h> #include <device_launch_parameters.h> #include <cstdio> #include <cstdlib> #include <iostream> #include <ctime> #include <string> #include <fstream> #include <math.h> using namespace std; #define rawR 7 #define rawC 840 #define rawL (rawR*rawC) #define L...
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#include <stdio.h> #include <stdlib.h> #include <math.h> #include <cuda_runtime.h> #include <cuda.h> #define TW 16 __global__ void matrix_sum(int *C, int *A, int *B, int rows, int cols, int dim) { // Get col int col = blockDim.x * blockIdx.x + threadIdx.x; // Get row int row = blockDim.y * blockIdx.y ...
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// /*// Created by sergio on 13/02/19. // #include <iostream> #include <stdint.h> // Para medir el clock #include <cstdlib> // std #include <iomanip> // Formateo de datos #include <string> #define CWIDTHLEFT 40 #define CWIDTHRIGHT 30 #include <cuda.h> #include <cuda_runtime.h> #include <device_l...
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// RUN: %clangxx -ccc-print-phases --sysroot=%S/Inputs/SYCL -target x86_64-unknown-linux-gnu -fsycl -fsycl-targets=nvptx64-nvidia-cuda -Xsycl-target-backend --cuda-gpu-arch=sm_80 --cuda-gpu-arch=sm_80 -c %s 2>&1 | FileCheck %s --check-prefix=DEFAULT-PHASES // Test the correct placement of the offloading actions for...
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// // // Tomás Oliveira e Silva, November 2017 // // ACA 2017/2018 // // modify_sector CUDA kernel (each thread deals with one sector) // extern "C" __global__ void modify_sector_cuda_kern...
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#include <stdio.h> #include <stdlib.h> #include <math.h> #include <time.h> __global__ void imageblur( int* inputImage, int* outputImage, int filterSize, double* filter, int imageRow, int imageCol){ int pixelx = blockIdx.x * blockDim.x + threadIdx.x; int pixely = blockIdx.y * blockDim.y + threadIdx.y; double...
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#include <stdio.h> #include <stdlib.h> #include <math.h> #include <assert.h> #include <cuda.h> #include <cuda_runtime.h> #include <sys/time.h> #include <algorithm> #include <unistd.h> #define max(a, b) (a > b ? a : b) #define min(a, b) (a < b ? a : b) // Max threadsize is 1024 32*32 typedef unsigned char ubyte; void...
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#include <cuda_runtime.h> #include <stdio.h> #include <stdlib.h> #ifndef PRINT_SUFFIX #define PRINT_SUFFIX "<find_cudadevices>" #endif #define MY_CUDA_VER (__CUDACC_VER_MAJOR__ * 100 + __CUDACC_VER_MINOR__) inline void check(cudaError_t result) { if (result) { fprintf(stderr, PRINT_SUFFIX "%s (%s)", ...
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#include <vector> #include <stdint.h> #include <stddef.h> __device__ bool NV12ToRGB(uint8_t * pData, int Height, int Width, int bitdepth, void * pOut) { }
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#include <stdio.h> #include <stdlib.h> #include <math.h> #define I(ix,iz) (ix)+nx*(iz) # define PI 3.141592653589793 __global__ void propagator_U(float *Ux, float *Uz, float *Txx, float *Txz, float *Tzz, float *P, int nx, int nz, float dt, float dh) { int ix = threadIdx.x + blockDim.x * blockIdx.x; int iz = threadI...
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#include <iostream> #include <numeric> #include <stdio.h> #include <stdlib.h> #include <time.h> #include <cuda.h> #include <curand.h> #include <math.h> #include <fstream> #include <sstream> #include <cstdio> #include <ctime> static void CheckCudaErrorAux (const char *, unsigned, const char *, cudaError_t); void sequen...
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#include<stdio.h> #include<stdlib.h> __global__ void mykernel(int* a,int* b,int* c){ //no code is here *c=*a+*b; } int main(){ int a=1; int b=9; int c; int* d_a; int* d_b; int* d_c; cudaMalloc((void**)&d_a,sizeof(int)); cudaMalloc((void**)&d_b,sizeof(int)); cudaMalloc((void*...
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__global__ void JacobiSVD(int* S, int* V, int m, int n) { const int iterations = 30; int tid_x = threadIdx.x; int bsz_x = blockDim.x; int tid_y = threadIdx.y; int gid_y = blockIdx.y * blockDim.y + tid_y; __shared__ int acc[512]; int* acc1 = acc; int* acc2 = acc + 256; __shared__ i...
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#include "cuda_runtime.h" #include "device_launch_parameters.h" #include <stdio.h> #include <stdlib.h> #include <iostream> #include <ctime> #include <algorithm> #define Color uchar4 float4 Sum(float4 a, Color b, float coef) { return { a.x + (float)b.x * coef, a.y + (float)b.y * coef, a.z + (float)b.z * coef, ...
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#include <thrust/sort.h> struct t { int j,k,l; }; int main() { const int N = 6; int i; int keys[N] = { 1, 4, 2, 8, 5, 7}; struct t values[N]= { {3,4,5},{5,6,7},{8,9,10},{11,12,13},{14,15,16},{17,18,19}}; //int *values2[N]= { {13,14,15},{15,16,17},{18,19,110},{111,112,113},{114,15,16},{17,18,19...
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#include "cuda_runtime.h" #include "device_launch_parameters.h" #include <iostream> #include <cstring> #include <string> using namespace std; #define NUM_DATA 512 __global__ void vecAdd(int *a,int *b,int *c) { int tid = threadIdx.x; c[tid] = a[tid] + b[tid]; } int main() { int *a,*b,*c; int *d_a,*d_b...
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#include <stdio.h> #include <time.h> #include <sys/time.h> #include <cuda_runtime.h> #define CHECK(cmnd) { \ cudaError_t ierr = cmnd; \ if (ierr != cudaSuccess) { \ printf("Error: %s:%d: ", __FILE__, __LINE__, cudaGetErrorString(ierr)); \ exit(ierr); ...
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#include "includes.h" __global__ void cube(float * d_out, float * d_in){ // Todo: Fill in this function int index = threadIdx.x; float f = d_in[index]; d_out[index] = f*f*f; }
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#include <stdio.h> #define T 16 // As Threads #define array_size 64 __global__ void vecMultiplyReverse(int *A, int *B, int *C) { int i = blockIdx.x * blockDim.x + threadIdx.x; if(i%2 == 0) { C[i] = A[i] + B[i]; } else if(i%2 != 0) { C[i] = A[i] - B[i]; } } int main (int ar...
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#include <cuda.h> #include <cuda_runtime.h> #include <math.h> #include <math_constants.h> #include <stdlib.h> #include <vector> #include <algorithm> #include <thrust/host_vector.h> #include <thrust/device_vector.h> #include <thrust/generate.h> #include <thrust/sort.h> #include <thrust/copy.h> #include <cstdlib> #def...
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#include "includes.h" __global__ void sga_up_forward (const int n, const float *filters, const int height, const int width, const int depth, const int wsize, float *top_data){ int index = blockIdx.x * blockDim.x + threadIdx.x; if (index >= n) { return; } int step = height * width; // int wsize=radius+1; int base =...
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#include <stdio.h> void create_diagonal_matrix(float *Dmatrix, float matrix[3], int array_length) { for(int i=0;i<array_length;i++) { for(int j=0;j<array_length;j++) { if(i==j) Dmatrix[j*array_length+i]=matrix[i]; else Dmatrix[j*array_leng...
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#include "includes.h" __global__ void init_one_vec(float* d_one_vec, size_t length) { int i = blockIdx.x * blockDim.x + threadIdx.x; if (i >= length) return; d_one_vec[i] = 1.f; }
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#include "includes.h" //Macros #define min(a, b) ( (a)<(b)? (a): (b) ) #define max(a, b) ( (a)>(b)? (a): (b) ) //Constants #define MAX_VECTOR_COUNT 5 //Vector structure typedef struct { float e[3]; }Vec3f; //Global array Vec3f vecArray[MAX_VECTOR_COUNT]; Vec3f newvecArray[MAX_VECTOR_COUNT]; //forward declarations ...
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#include "cuda_runtime.h" #include "device_launch_parameters.h" #include <stdio.h> #include <string.h> #define NUM_ELEMENTS 7 #define MAX_ELEMENTS_BLOCK 2048 struct Point { unsigned int X; unsigned int Y; unsigned int leftID; // counter-clockwise neighbor unsigned int rightID; // clockwise neighbor }; extern _...
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/* This is a automatically generated test. Do not modify */ #include <stdio.h> #include <stdlib.h> #include <math.h> __global__ void compute(float comp, int var_1,int var_2,float var_3,float var_4,float var_5,float var_6,float var_7,float var_8,float var_9,float var_10,float var_11,float var_12,float var_13,float va...
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#include <thrust/host_vector.h> #include <thrust/device_vector.h> #include <thrust/transform.h> struct saxpy_functor { const float a; saxpy_functor(float _a) : a(_a) {} __host__ __device__ float operator()(float x, float y) { return a*x+y; } }; void saxpy(float a, thrust::device_vector<float>& x, thrust::devi...
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__global__ void convolution(int filterWidth,float *filter,int imageHeight,int imageWidth,float *inputImage,float *outputImage) { int i= blockIdx.x * blockDim.x + threadIdx.x; int j= blockIdx.y * blockDim.y + threadIdx.y; // Iterate over the rows of the source image int halffilterSize = filterWidth >> 1 ; float su...
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#include "includes.h" //Udacity HW 4 //Radix Sorting __global__ void histogram(unsigned int* in, unsigned int* hist, int n,unsigned int nBins, unsigned int mask, unsigned int current_bits) { extern __shared__ unsigned int s_local_hist[]; for(int j = threadIdx.x; j < nBins; j += blockDim.x) s_local_hist[j] = 0; _...
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#include <stdio.h> #include <stdlib.h> #include <cuda.h> #include <cuda_runtime.h> __global__ void simpleKernel(float *dst, float *src1, float *src2) { const int idx = blockIdx.x * blockDim.x + threadIdx.x; //float temp = src[idx]; dst[idx] = src1[idx] + src2[idx]; } int execute_uva(bool copy=false, bool prin...
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// to use CUDA, uncomment the following line #define USE_CUDA #include <stdio.h> #include <time.h> #include <cuda.h> #include <cuda_runtime.h> #include <cuComplex.h> #define COLOR_DEPTH 256 #define DEFAULT_WIDTH 3840 #define DEFAULT_HEIGHT 2160 #define MAX_THREAD 65536 #ifndef USE_CUDA void computePixelNoGPU(cuDoub...
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#define uint unsigned int #define HX(i,j,n) Hx[i+IHx*(j)+IHx*JHx*n] #define BX(i,j,n) Bx[i+IHx*(j)+IHx*JHx*n] #define HY(i,j,n) Hy[i+IHy*(j)+IHy*JHy*n] #define BY(i,j,n) By[i+IHy*(j)+IHy*JHy*n] #define EZ(i,j,n) Ez[i+IEz*(j)+IEz*JEz*n] #define DZ(i,j,n) Dz[i+IEz*(j)+IEz*JEz*n] #define DZX(i,j,n) Dzx[i+IEz*(j)+IEz*JEz*n...
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#include "includes.h" using namespace std; int threads; __global__ void gcd_vector(int * d_out, int integer_m){ int idx = threadIdx.x; for(int i = idx; i<integer_m; i+=blockDim.x){ int u = i, v = integer_m; while ( v != 0) { int r = u % v; u = v; v = r; } if(u == 1){ d_out[idx]++; } } }
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#include "includes.h" __global__ void FilmGradeKernelA( float* p_Input, int p_Width, int p_Height, float p_Exp) { 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; p_Input[index] = p_Input[...
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//pass //--blockDim=512 --gridDim=1 --warp-sync=32 --no-inline #include <cuda.h> #include <stdio.h> #define N 32 __global__ void scan (int* A) { int tid = threadIdx.x; unsigned int lane = tid & 31; if (lane >= 1) A[tid] = A[tid - 1] + A[tid]; if (lane >= 2) A[tid] = A[tid - 2] + A[tid]; if (lane >= 4) A[tid]...
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#include "includes.h" __global__ void VecAdd(int n, const float *A, const float *B, float* C) { //DEVICE(GPU)CODE /******************************************************************** * * Compute C = A + B * where A is a (1 * n) vector * where B is a (1 * n) vector * where C is a (1 * n) vector * ****************...
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//#include <stdlib.h> //#include <stdio.h> //#include <cuda_runtime.h> //#include <helper_functions.h> //#include <curand_kernel.h> //#include "device_launch_parameters.h" //#include "../../common/book.h" //#include "../../common/cpu_anim.h" //#include "../../common/Utils.h" //#include "../../common/BlockUtils.h" //#in...
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#include <iostream> #include <cmath> #include <cstdlib> #include <climits> #include <cuda.h> #include <cuda_runtime.h> using namespace std; #define SIZE 14*14 #define X_SIZE 14 #define NUM_EXAMPLES 3 #define BLOCK_SIZE 3 //Function prototype //int SAT(int, int, int, int, int); //Global variable //Create big ass ar...
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#include <stdio.h> #include <stdlib.h> #include <cuda.h> #include <math.h> #include <limits.h> #include <float.h> #include <iostream> #include <sys/time.h> #include <stack> #define G 6.67408E-11 //Gravitational constant #define lvl 9 //depth of quad tree till which we'll divide plane using namespace std; struct ve...
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#include <stdio.h> #include <ctime> #include <cassert> #include <cmath> #include <utility> #include <vector> #include <algorithm> #include <cstdlib> #include <memory> #include <iostream> #include "cuda_runtime.h" #include "device_launch_parameters.h" float __device__ rad2deg(float radians) { return radians * 180....
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#include<iostream> #include<time.h> #include<climits> #include<stdlib.h> using namespace std; __global__ void minimum(int *a, int *b, int n) { int tid = threadIdx.x; int min_limit = INT_MAX; for(int i=tid; i<min(tid+256, n); i++) { if(min_limit > a[i]) min_limit = a[i]; } b[tid]...
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#include <iostream> #include <time.h> #define N 50000 #define BLK_SIZE 256 using namespace std; struct Atom { int x; int y; int z; int a, b, c, d, e, f; }; __global__ void AtomKernel(Atom *atoms, int *sum); __global__ void CoalescedKernel(int *x, int *y, int *z, int *sum); int main() { int i; //host Atom ...
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#include "cuda_runtime.h" #include "device_launch_parameters.h" #include <stdio.h> #include <iostream> #include <vector> #include <string> #include <array> #include <iomanip> #include <chrono> #include <fstream> typedef std::chrono::high_resolution_clock Clock; #define pi 3.14159265358979323846264338327950288419716...
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/* * makeProjection() * Forms E and E^T matrices from eigenvectors * float** eT: E^T, populated by function * float** e: E, populated by function * float** eigenvec: matrix of eigenvectors, unsorted * int* indices: indices to accept from eigenvectors * int N: degrees of freedom */ __global__ void makeProjection(...
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#include <stdio.h> #include <cuda.h> #include <cuda_runtime.h> struct Target { int2 min; int2 max; __device__ bool contains(int2 pos) const { return pos.x >= min.x && pos.x <= max.x && pos.y >= min.y && pos.y <= max.y; } }; __device__ bool simulate(Target target, int2 init_vel) { int2 vel = init_vel; in...
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#include <stdio.h> __device__ int x; __global__ void unaligned_kernel(void) { *(int*) ((char*)&x + 1) = 42; } __device__ void out_of_bounds_function(void) { *(int*) 0x87654320 = 42; } __global__ void out_of_bounds_kernel(void) { out_of_bounds_function(); } void run_unaligned(void) { printf("Running...
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#include "includes.h" __global__ void HydroUpdatePrim_CUDA3_kernel(float *Rho, float *Vx, float *Vy, float *Vz, float *Etot, float *dUD, float *dUS1, float *dUS2, float *dUS3, float *dUTau, float dt, int size) { // get thread and block index const long tx = threadIdx.x; const long bx = blockIdx.x; const long by = block...
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//Based on the work of Andrew Krepps #include <stdio.h> #include <math.h> #include <chrono> /* * Used for multiplying two square matrices of the same size. * Uses shared memory to store matrix c until it is time to copy * the final array out to the CPU. */ __host__ cudaEvent_t get_time(void) { cudaEvent_t time; cuda...
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#include "includes.h" __global__ void NmDistanceKernel(int b,int n,const float * xyz,int m,const float * xyz2,float * result,int * result_i){ const int batch=2048; __shared__ float buf[batch*5]; for (int i=blockIdx.x;i<b;i+=gridDim.x){ for (int k2=0;k2<m;k2+=batch){ int end_k=min(m,k2+batch)-k2; for (int j=threadIdx.x;...
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#include <assert.h> #include <math.h> #include <stdio.h> #include <time.h> #include <vector> #include <cuda.h> const int A = 1920; const int B = 132; const int C = 396; std::vector<float> TakeNaive(const std::vector<float>& x, const std::vector<int>& indices) { std::vector<float> y(...
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/***************************************************************************** Example : cuda-matrix-matrix-multiplication.cu Objective : Write a CUDA Program to perform Matrix Matrix multiplication. Input : None Output : Execution time in seconds , Gflops achieved ...
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#include "user_device.cuh" __device__ float global_cache[GLOBAL_CACHE_SIZE]; /** * function name: atomicMax_float * Return Type: float * Description: * "atomicMax" for float. * Compare old value (*maxVal) and new value (value). * If new value is larger than old value, than new value will overwri...
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#include "includes.h" __global__ void CudaPermuteWeightsPVToCudnn( float *dest, float *src, int numArbors, int outFeatures, int ny, int nx, int inFeatures) { // Parameter dimensions are PV source dimensions int kSrc = (blockIdx.x * blockDim.x) + threadIdx.x; if (kSrc < outFeatures * ny * nx * inFeatures) { int kA = kS...
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#include "Utils.cuh" #include <curand.h> #include <algorithm> #include <cuda_profiler_api.h> size_t Shape3d::size()const { return depth * height * width; } Shape3d::Shape3d() : Shape3d(1) {} Shape3d::Shape3d(size_t width) : Shape3d(1, width) {} Shape3d::Shape3d(size_t height, size_t width) : Shape3d(1, height, width) ...
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#include <iostream> #include <cuda_runtime.h> using namespace std; #define N 20 #define BLOCK_DIM 10 void random_inits(int a[N][N]){ for (int i = 0; i < N; i++){ for (int j = 0; j < N; j++){ a[i][j] = rand() % 10; } } } __global__ void add(int a[N][N], int b[N][N], int c[N][N]){ int i = threadIdx.x; int j...
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#include <iostream> #include <cuda_runtime.h> using namespace std; // Derived class class Rectangle { public: //don't use constructor Rectangle() { // width = (int *)malloc(sizeof(int)); // height = (int *)malloc(sizeof(int)); // *width = 10; ...
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#include<iostream> __constant__ float M[10]; int main(){ float h_M[]={1,2,3,4,5,7,8,9,0}; cudaMemcpyToSymbol(M,h_M,10*sizeof(float)); std::cout<< "yo"<<std::endl; }
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__device__ int evalDirt() { return 4; }
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#include "includes.h" __global__ void conv2genericrev(float *input, float *kernel, float *output, int input_n, int input_h, int input_w, int kernel_n, int kernel_h, int kernel_w, float alpha, int stride_h, int stride_w) { // output dimensions int output_h = input_h - (kernel_h - 1) * stride_h; int output_w = input_w - ...
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#include "includes.h" __global__ void _bcnn_vadd_kernel(int n, float *a, float *b, float *y) { int i = (blockIdx.x + blockIdx.y * gridDim.x) * blockDim.x + threadIdx.x; if (i < n) y[i] = a[i] + b[i]; }
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//This is simple naive programme(brute force) //which runs in O(N^2) #include <stdio.h> #include <stdlib.h> #include <cuda.h> #include <math.h> #include <sys/time.h> #define G 6.67408E-11 struct vector { float x, y; }; //This function calculate the gravitational force //between two bodies or particals vector gravit...
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#include <math.h> #include <stdio.h> #include <stdlib.h> __global__ void Babis_Kernel(double const *A, double *B, double const *G, int n, int m, int patchSize_x, int patchSize_y, double filtSigma) { int x,y,area_x,area_y; double norm,w_temp,diff=0,W=0,Products=0; // Set pixel coordinates int i = blockIdx...
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#include <stdio.h> #define N 512 __global__ void add(int *a, int *b, int *c){ c[blockIdx.x] = a[blockIdx.x]+b[blockIdx.x]; } void random_ints(int *a, int n){ for(int i=0; i<n; i++){ a[i] = rand()%10+1; } } int main(void){ int *a,*b,*c; int *d_a,*d_b,*d_c; int size = N*sizeof(int); cudaMalloc((void**)&d_a,...
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#include <stdio.h> #include <stdlib.h> #include <time.h> #include <sys/time.h> #include <cuda.h> void Algorithm2(int m, int n, int l); // Block size used in algorithm 2 of GEMM #define BLOCK_SIZE_x 32 #define BLOCK_SIZE_y 16 __device__ unsigned long long totThr = 0; __global__ void device_Matrix_multi(const double* co...
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#include <stdlib.h> #include <stdio.h> extern int HI; // the total number of point patterns extern int HN; // the total number of points extern int HK_star; // the total number of covariates extern int Hd; // the dimensionality of the problem extern int HV; // the total number of elements in the gr...
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#include <string.h> #include <stdio.h> #include <stdlib.h> #include <sys/time.h> __global__ void vectAdd(int *a, int *b, int *c, int len) { int i; i = blockIdx.x * blockDim.x + threadIdx.x; if (i < len) { c[i] = a[i] + b[i]; } } /* Function computing the final string to print */ void vector_add(int *c...
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#include <stdio.h> #include <time.h> #define MIN(a,b) (a < b ? a : b) #define PRINT 0 static const int N = 50000; __global__ void bubble_sort(int *array, int iteracio) { int id = threadIdx.x + blockIdx.x * blockDim.x; if(iteracio%2 == 0 ){ if(array[2*id] > array[2*id+1]) { int aux = array[2*id]; array[2*i...
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#define MAX_THREADS 1024 #define MULT_TILE_WIDTH 16 __global__ void matrixMultiplyShared(float *A, float *B, float *C, int numARows, int numAColumns, int numBRows, int numBColumns, int numCRows, int numCColum...
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#include <stdio.h> #include <stdlib.h> #define CSC(call) \ do { \ cudaError_t res = call; \ if (res != cudaSuccess) { \ fprintf(stderr, "ERROR in %s:%d. Message: %s\n", \ __FILE__, __LINE__, cudaGetErrorStr...
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#include "cuda_runtime.h" #include "device_launch_parameters.h" #include<stdio.h> __global__ void star(char *a, int *n) { int i, j, t; int k = *n; int tid=threadIdx.x; j = k - tid - 1; t = (tid + 1) * 2 - 1; for(i = 0; i < t; i++){ a[tid * (k * 2 - 1) + j + i] = '*'; } } int main(void) { int i, N, j; s...
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__global__ void set_one(float *array, int i) { int id = threadIdx.x + blockIdx.x * blockDim.x; if (id == 0) { array[i] = 1.0f; } } __device__ float gpu_logistic(float x) { return 1 / (1 + expf(-x)); } __global__ void activation_function(float x[], int n) { int id = threadIdx.x + blockIdx.x...
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__global__ void apply_blue(unsigned char *red_channel,unsigned char *green_channel, const unsigned int width, const unsigned int height) { const unsigned int row = threadIdx.y + blockIdx.y * blockDim.y; const unsigned int col = threadIdx.x + blockIdx.x * blockDim.x; if(row < height && col < width) { ...
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/* * Copyright 2015 NVIDIA Corporation * * 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 ...
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#include "includes.h" __global__ void var(float * M1, float * M2, float * X, int b, size_t nele) { int idx = blockIdx.x*blockDim.x + threadIdx.x; if (idx<nele) { float delta = X[idx] - M1[idx]; M1[idx] += delta / (b + 1); M2[idx] += delta*(X[idx] - M1[idx]); } }
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#include "file_reader.cuh" #include "reader.cuh" template<class T> FileReader<T>::FileReader(std::string &filename, Probe &probe) : Reader<T>(probe), filename_(filename), file_size_(0) { set_filename(filename); } /** * @brief Acquire samples_ from the file, so many frames at a time. * @tparam T The type of sa...