hip_filename stringlengths 5 84 | hip_content stringlengths 79 9.69M | cuda_filename stringlengths 4 83 | cuda_content stringlengths 19 9.69M |
|---|---|---|---|
2032e854599fe4c3e6166ae1ebf33b1a6015aabc.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include<stdio.h>
#include<stdlib.h>
#define N 20
#define M 3
__global__ void add(int *a, int *b, int *c, int n) {
int index = threadIdx.x + blockIdx.x * blockDim.x;
if(index < n )
c[index] = a[index] + b[index];
}
void r... | 2032e854599fe4c3e6166ae1ebf33b1a6015aabc.cu | #include<stdio.h>
#include<stdlib.h>
#define N 20
#define M 3
__global__ void add(int *a, int *b, int *c, int n) {
int index = threadIdx.x + blockIdx.x * blockDim.x;
if(index < n )
c[index] = a[index] + b[index];
}
void random_ints(int *x, int n){
int i;
for(i=0;i<n;i++){
x[i]=rand()%99;
}
}
void print... |
ff809bf2341a055cbca59194aa03c09f39225656.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*
Copyright Ramtin Shams (hereafter referred to as 'the author'). All rights
reserved. **Citation required in derived works or publications**
NOTICE TO USER:
Users and possessors of this source code are hereby granted ... | ff809bf2341a055cbca59194aa03c09f39225656.cu | /*
Copyright Ramtin Shams (hereafter referred to as 'the author'). All rights
reserved. **Citation required in derived works or publications**
NOTICE TO USER:
Users and possessors of this source code are hereby granted a nonexclusive,
royalty-free license to use this source code for non-commercial purpos... |
af5f8f677563e3e420ed5cea447cd9fa4b294599.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "hip/hip_runtime.h"
#include "device_launch_parameters.h"
#include "stdio.h"
using namespace std;
__global__ void mykernel() {
printf("Hello World!");
}
int main(){
hipLaunchKernelGGL(( mykernel) , dim3(1),dim3(1), 0, ... | af5f8f677563e3e420ed5cea447cd9fa4b294599.cu | #include "cuda_runtime.h"
#include "cuda.h"
#include "device_launch_parameters.h"
#include "stdio.h"
using namespace std;
__global__ void mykernel() {
printf("Hello World!");
}
int main(){
mykernel <<< 1,1>>> ();
return 0;
} |
e8afb8fbc5e63e020c3f611005afb568d0901ee0.hip | // !!! This is a file automatically generated by hipify!!!
#include <stdbool.h>
#include <stdio.h>
#include <string.h>
#include <getopt.h>
#include <hiprand/hiprand_kernel.h>
#include <stdlib.h>
#include <hip/hip_runtime.h>
#include <sys/time.h>
#include "matrixMulCUDA.cu"
#include<chrono>
#include<iostream>
using name... | e8afb8fbc5e63e020c3f611005afb568d0901ee0.cu | #include <stdbool.h>
#include <stdio.h>
#include <string.h>
#include <getopt.h>
#include <curand_kernel.h>
#include <stdlib.h>
#include <cuda.h>
#include <sys/time.h>
#include "matrixMulCUDA.cu"
#include<chrono>
#include<iostream>
using namespace std;
using namespace std::chrono;
int blocks_[20][2] = {{8,8},{16,16},{24... |
41fb6057f7415221f4ef5f8c997638e3d0690321.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <iostream>
__global__ void axpy(float a, float* x, float* y) {
y[threadIdx.x] = a * x[threadIdx.x];
}
int main(int argc, char* argv[]) {
const int kDataLen = 4;
float a = 2.0f;
float host_x[kDataLen] = {1.0f, 2.0... | 41fb6057f7415221f4ef5f8c997638e3d0690321.cu | #include <iostream>
__global__ void axpy(float a, float* x, float* y) {
y[threadIdx.x] = a * x[threadIdx.x];
}
int main(int argc, char* argv[]) {
const int kDataLen = 4;
float a = 2.0f;
float host_x[kDataLen] = {1.0f, 2.0f, 3.0f, 4.0f};
float host_y[kDataLen];
// Copy input data to device.
float* devi... |
pomdp_pbvi_gpu.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/**
* The MIT License (MIT)
*
* Copyright (c) 2015 Kyle Hollins Wray, University of Massachusetts
*
* Permission is hereby granted, free of charge, to any person obtaining a copy of
* this software and associated documenta... | pomdp_pbvi_gpu.cu | /**
* The MIT License (MIT)
*
* Copyright (c) 2015 Kyle Hollins Wray, University of Massachusetts
*
* Permission is hereby granted, free of charge, to any person obtaining a copy of
* this software and associated documentation files (the "Software"), to deal in
* the Software without restriction, including ... |
32bf91b9aca233f5d35ba9cac2e497286f71a7b4.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>
static hipStream_t *streams;
// CUDA kernel to pause for at least num_cycle cycles
__global__ void sleep(int64_t num_cycles)
{
int64_t cycles = 0;
... | 32bf91b9aca233f5d35ba9cac2e497286f71a7b4.cu | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>
static cudaStream_t *streams;
// CUDA kernel to pause for at least num_cycle cycles
__global__ void sleep(int64_t num_cycles)
{
int64_t cycles = 0;
int64_t start = clock64();
while(cycles < num_cycles) {
cycles = clock64()... |
f23758c41e80342b96655934a1547c9867e47bb1.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <stdlib.h>
__global__ void add1(int *A, int *B, int *C, int n){ //each thread computes the sum of elements row-wise
int row = threadIdx.x;
for(int i=0;i<n;i++){
... | f23758c41e80342b96655934a1547c9867e47bb1.cu | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <stdlib.h>
__global__ void add1(int *A, int *B, int *C, int n){ //each thread computes the sum of elements row-wise
int row = threadIdx.x;
for(int i=0;i<n;i++){
C[row*n+i] = A[row*n +i] + B[row*n+i];
}
}
__global__ void ... |
ee0b95d2f2e4ef9e0a3a230e8bd379f0b7051ee3.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <iostream>
#include "assert.h"
#define WORK_PER_THREAD 4
__global__ void saxpy_parallel(int n, float a, float *x, float *y)
{
int i = blockIdx.x*blockDim.x + threadIdx.x;
i *= WORK_PER_THREAD;
if (i < n)
{
#pragm... | ee0b95d2f2e4ef9e0a3a230e8bd379f0b7051ee3.cu | #include <iostream>
#include "assert.h"
#define WORK_PER_THREAD 4
__global__ void saxpy_parallel(int n, float a, float *x, float *y)
{
int i = blockIdx.x*blockDim.x + threadIdx.x;
i *= WORK_PER_THREAD;
if (i < n)
{
#pragma unroll
for(int j=0; j<WORK_PER_THREAD; j++)
y[i+j] = a * x[i+j] + y[i+j];
}
}
... |
d4f72ce4814b0dd1425a117599977d4439cfb4cd.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*******************************************************************************
* Copyright (c) 2019 Konduit K.K.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Versi... | d4f72ce4814b0dd1425a117599977d4439cfb4cd.cu | /*******************************************************************************
* Copyright (c) 2019 Konduit K.K.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unles... |
8c532ea8b81bcd1742cff5bc42dda0f6697f35f9.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
//************************************************************************************/
// Title : Parallel Processing of SAR Signal for Image generation on CUDA Platform
//**... | 8c532ea8b81bcd1742cff5bc42dda0f6697f35f9.cu | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
//************************************************************************************/
// Title : Parallel Processing of SAR Signal for Image generation on CUDA Platform
//****************************************************************... |
9b61e79732e3688149c551b8d3a7d6e2fe49032c.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "kernel_hip.cuh"
#define N 5
__global__ void gpuSquareKernel(float* d_in, float* d_out)
{
int tid = threadIdx.x;
float temp = d_in[tid];
d_out[tid] = temp * temp;
}
void gpuSquare(float* h_in, float* h_out)
{... | 9b61e79732e3688149c551b8d3a7d6e2fe49032c.cu | #include "kernel.cuh"
#define N 5
__global__ void gpuSquareKernel(float* d_in, float* d_out)
{
int tid = threadIdx.x;
float temp = d_in[tid];
d_out[tid] = temp * temp;
}
void gpuSquare(float* h_in, float* h_out)
{
float *d_in, *d_out;
cudaMalloc((void**)&d_in, N * sizeof(float));
cudaMalloc(... |
db5c99065a250506aa6a7c1a568898c324cdb69b.hip | // !!! This is a file automatically generated by hipify!!!
#include <torch/extension.h>
#include <hip/hip_runtime.h>
#include <hip/hip_runtime.h>
#include <c10/macros/Macros.h>
#include <THH/THH.h>
#include <ATen/AccumulateType.h>
#include <ATen/hip/HIPContext.h>
// Warp reduce kernels to reduce N groups of data into ... | db5c99065a250506aa6a7c1a568898c324cdb69b.cu | #include <torch/extension.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <c10/macros/Macros.h>
#include <THC/THC.h>
#include <ATen/AccumulateType.h>
#include <ATen/cuda/CUDAContext.h>
// Warp reduce kernels to reduce N groups of data into N numbers, where N = warpSize / width.
// width should be a power of 2 ... |
56269514c5ad7f741c2a8b9bfb3bf897ebe444a4.hip | // !!! This is a file automatically generated by hipify!!!
#include <cstdio>
#include <cstdlib>
#include <hip/hip_runtime.h>
#include <rocblas.h>
#include <time.h>
#define random(a, b) (rand() % (b - a) + a)
void FillMatrix(float *matrix, int row, int col);
void PrintMatrix(float *A, float *B, float *C, int m, int n, i... | 56269514c5ad7f741c2a8b9bfb3bf897ebe444a4.cu | #include <cstdio>
#include <cstdlib>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <time.h>
#define random(a, b) (rand() % (b - a) + a)
void FillMatrix(float *matrix, int row, int col);
void PrintMatrix(float *A, float *B, float *C, int m, int n, int k);
__global__ void MatrixMulCUDA(const float *A, const f... |
b69428d78d88f6d1defd6cb4c1505bcef170562e.hip | // !!! This is a file automatically generated by hipify!!!
#include <ATen/native/hip/Normalization.cuh>
inline bool batch_norm_use_channels_last_kernels(const at::Tensor& self) {
return self.is_contiguous(at::MemoryFormat::ChannelsLast) || self.ndimension() == 2;
}
namespace at { namespace native {
std::tuple<Tens... | b69428d78d88f6d1defd6cb4c1505bcef170562e.cu | #include <ATen/native/cuda/Normalization.cuh>
inline bool batch_norm_use_channels_last_kernels(const at::Tensor& self) {
return self.is_contiguous(at::MemoryFormat::ChannelsLast) || self.ndimension() == 2;
}
namespace at { namespace native {
std::tuple<Tensor&, Tensor&, Tensor&> batch_norm_cuda_out(const Tensor& s... |
gpu_pc_v2.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/********************************************************
*
* This experiment optimizes packet classification
* in the following aspects:
* 1. Thread assignment
* 2. Memory coalescing
*
* Experiment Assumptions:
* 1. 5... | gpu_pc_v2.cu | /********************************************************
*
* This experiment optimizes packet classification
* in the following aspects:
* 1. Thread assignment
* 2. Memory coalescing
*
* Experiment Assumptions:
* 1. 510 Non-overlapping intervals
* 2. 1024 Rules (510 * 1024 element BVs)
* 3. Number of p... |
ca0a679015b6dc1a237b42c5509e755444e7b319.hip | // !!! This is a file automatically generated by hipify!!!
#include <stdio.h>
#include <sys/time.h>
#include <time.h>
#include <opencv2/opencv.hpp>
#include <math.h>
//#include <device_launch_parameters.h>
//#include <hip/hip_runtime.h>
//#include <helper_cuda.h>
//#include <helper_timer.h>
//#include <hip/device_funct... | ca0a679015b6dc1a237b42c5509e755444e7b319.cu | #include <stdio.h>
#include <sys/time.h>
#include <time.h>
#include <opencv2/opencv.hpp>
#include <math.h>
//#include <device_launch_parameters.h>
//#include <cuda_runtime.h>
//#include <helper_cuda.h>
//#include <helper_timer.h>
//#include <device_functions.h>
#define IS_NOT_EDGE(a) (a < min_val)
#define IS_STRONG_ED... |
1896f0ce74593a54da8fea2d28f45b5de2ecb5fd.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/filler_op.h"
namespace caffe2 {
namespace {
__global__ void FillRangeKernel(const int n, float* data) {
CUDA_1D_KERNEL_LOOP(index, n) {
data[index] = index;
}... | 1896f0ce74593a54da8fea2d28f45b5de2ecb5fd.cu | #include "caffe2/core/context_gpu.h"
#include "caffe2/operators/filler_op.h"
namespace caffe2 {
namespace {
__global__ void FillRangeKernel(const int n, float* data) {
CUDA_1D_KERNEL_LOOP(index, n) {
data[index] = index;
}
}
}
template <>
bool RangeFillOp<float, CUDAContext>::Fill(
TensorCUDA* output) {
... |
f3ea23d2e836532fe75f1885a772aa1992bdb8d1.hip | // !!! This is a file automatically generated by hipify!!!
/*
* Copyright (c) 2018-2019, 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.o... | f3ea23d2e836532fe75f1885a772aa1992bdb8d1.cu | /*
* Copyright (c) 2018-2019, 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... |
890514075e66bf4c72a07820794522f4f6212ad7.hip | // !!! This is a file automatically generated by hipify!!!
#include "catch.hpp"
#include <thrust/device_vector.h>
//----------------------------------------------------------------------------------------
#define TEST_CUDA_CHECK_RETURN
//-------------------------------------------------------------------------------... | 890514075e66bf4c72a07820794522f4f6212ad7.cu | #include "catch.hpp"
#include <thrust/device_vector.h>
//----------------------------------------------------------------------------------------
#define TEST_CUDA_CHECK_RETURN
//----------------------------------------------------------------------------------------
#include "BaseCudaTestHandler.h"
#include "../GP... |
c2efadd2acad18b834bd18bbaf1961fa5aa5d367.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/* Udacity Homework 3
HDR Tone-mapping
Background HDR
==============
A High Definition Range (HDR) image contains a wider variation of intensity
and color than is allowed by the RGB format with 1 byte per channel that w... | c2efadd2acad18b834bd18bbaf1961fa5aa5d367.cu | /* Udacity Homework 3
HDR Tone-mapping
Background HDR
==============
A High Definition Range (HDR) image contains a wider variation of intensity
and color than is allowed by the RGB format with 1 byte per channel that we
have used in the previous assignment.
To store this extra information we use si... |
bb7674ecd4b6f0ab52fed40f1bd47fb928a05452.hip | // !!! This is a file automatically generated by hipify!!!
#include <stdio.h>
#include <stdlib.h>
#include <device_launch_parameters.h>
#include <hip/hip_runtime.h>
// function for checking the CUDA runtime API results.
inline
void checkCuda(hipError_t result)
{
#if defined(DEBUG) || defined(_DEBUG)
if (result != h... | bb7674ecd4b6f0ab52fed40f1bd47fb928a05452.cu | #include <stdio.h>
#include <stdlib.h>
#include <device_launch_parameters.h>
#include <cuda_runtime.h>
// function for checking the CUDA runtime API results.
inline
void checkCuda(cudaError_t result)
{
#if defined(DEBUG) || defined(_DEBUG)
if (result != cudaSuccess)
{
printf_s("Error: %s : %d", __FILE__, __LINE_... |
3afaf1bf27abaf77fdbd8287bf8c846e73c6a50e.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <string>
#include <iostream>
#include <fstream>
#include <sstream>
#include <float.h>
#include <math.h>
#ifndef OUT_OF_BOUNDS_LABEL
#define OUT_OF_BOUNDS_LABEL -1
#endif
#ifndef BAD_TOPOLOGY_LABEL
#define BAD_TOPOLOGY_... | 3afaf1bf27abaf77fdbd8287bf8c846e73c6a50e.cu |
#include <string>
#include <iostream>
#include <fstream>
#include <sstream>
#include <float.h>
#include <math.h>
#ifndef OUT_OF_BOUNDS_LABEL
#define OUT_OF_BOUNDS_LABEL -1
#endif
#ifndef BAD_TOPOLOGY_LABEL
#define BAD_TOPOLOGY_LABEL -2
#endif
#ifndef NUM_OF_CHANNELS
#define NUM_OF_CHANNELS 3
#endif
#ifndef USE... |
9d9c72e7975c25aa0642da638b2001146587ee41.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "cudakernel/memory/pad.h"
#include "cudakernel/common/divmod_fast.h"
#include "cudakernel/common/memory_utils.h"
#include "ppl/nn/common/tensor_shape.h"
#include "ppl/common/retcode.h"
#include <hip/hip_fp16.h>
template <t... | 9d9c72e7975c25aa0642da638b2001146587ee41.cu | #include "cudakernel/memory/pad.h"
#include "cudakernel/common/divmod_fast.h"
#include "cudakernel/common/memory_utils.h"
#include "ppl/nn/common/tensor_shape.h"
#include "ppl/common/retcode.h"
#include <cuda_fp16.h>
template <typename T>
__global__ void ppl_cukernel_pad(
int64_t num_elems,
int num_dims,
P... |
9038377c629036eeadba06211d70ac14482338d2.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#ifndef EVOLUTION_AUX_H
#define EVOLUTION_AUX_H
#include "evolutionUtils.h"
#include "cudaMath.h"
#include "coriolisUtils.h"
#ifdef printf
#undef printf
#endif
static __global__ void _print_constant_memory_()
{
printf(" %f %f ... | 9038377c629036eeadba06211d70ac14482338d2.cu |
#ifndef EVOLUTION_AUX_H
#define EVOLUTION_AUX_H
#include "evolutionUtils.h"
#include "cudaMath.h"
#include "coriolisUtils.h"
#ifdef printf
#undef printf
#endif
static __global__ void _print_constant_memory_()
{
printf(" %f %f %f %d\n", r1_dev.left, r1_dev.dr, r1_dev.mass, r1_dev.n);
printf(" %f %f %f %d\n", r2_... |
493b6fc5d8603637e68c69a9f12d91afa7ece82a.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
#include <stdlib.h>
#include <omp.h>
#include <assert.h>
#define threshold 5 //(50% probability)
#define block_size 256
__global__ void calculation( char* dev_a,
char* dev_b,
... | 493b6fc5d8603637e68c69a9f12d91afa7ece82a.cu | #include <stdio.h>
#include <stdlib.h>
#include <omp.h>
#include <assert.h>
#define threshold 5 //(50% probability)
#define block_size 256
__global__ void calculation( char* dev_a,
char* dev_b,
char* dev_c,
int num_mat... |
b0b92ede1d3dbd4569f1fbdf66ed72178f5ddaef.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <add_cuda.h>
namespace zjx{
__global__ void addwithcuda(int* x, int* y,int *z){
*z = *x + *y;
}
int add_ceshi(int m, int n){
int *x=0;
int *y=0;
int *z=0;
hipMalloc((void**)&x,sizeof(int));
hipMa... | b0b92ede1d3dbd4569f1fbdf66ed72178f5ddaef.cu | #include <add_cuda.h>
namespace zjx{
__global__ void addwithcuda(int* x, int* y,int *z){
*z = *x + *y;
}
int add_ceshi(int m, int n){
int *x=0;
int *y=0;
int *z=0;
cudaMalloc((void**)&x,sizeof(int));
cudaMalloc((void**)&y,sizeof(int));
cudaMalloc((void**)&z,sizeof(int));
cudaMemcpy(x... |
c4a88ba5108cb97facef58e08570a812424c23ee.hip | // !!! This is a file automatically generated by hipify!!!
/*
* Copyright (c) 2020, 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/li... | c4a88ba5108cb97facef58e08570a812424c23ee.cu | /*
* Copyright (c) 2020, 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 ... |
fc569f4d1f75fcbd8af63b41eb00d1f6833dfc08.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*
-- MAGMA (version 1.6.0) --
Univ. of Tennessee, Knoxville
Univ. of California, Berkeley
Univ. of Colorado, Denver
@date November 2014
@generated from zlaswp.cu normal z -> d, Sat Nov 15 19:... | fc569f4d1f75fcbd8af63b41eb00d1f6833dfc08.cu | /*
-- MAGMA (version 1.6.0) --
Univ. of Tennessee, Knoxville
Univ. of California, Berkeley
Univ. of Colorado, Denver
@date November 2014
@generated from zlaswp.cu normal z -> d, Sat Nov 15 19:53:59 2014
@author Stan Tomov
@author Mathieu Faverge
@auth... |
fe2fc01e16dc0050bc058546dd3832030c4edec1.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
//
// auto-generated by ops.py
//
__constant__ int xdim0_flux_calc_kernelz;
int xdim0_flux_calc_kernelz_h = -1;
__constant__ int ydim0_flux_calc_kernelz;
int ydim0_flux_calc_kernelz_h = -1;
__constant__ int xdim1_flux_calc_kernelz;
... | fe2fc01e16dc0050bc058546dd3832030c4edec1.cu | //
// auto-generated by ops.py
//
__constant__ int xdim0_flux_calc_kernelz;
int xdim0_flux_calc_kernelz_h = -1;
__constant__ int ydim0_flux_calc_kernelz;
int ydim0_flux_calc_kernelz_h = -1;
__constant__ int xdim1_flux_calc_kernelz;
int xdim1_flux_calc_kernelz_h = -1;
__constant__ int ydim1_flux_calc_kernelz;
int ydim1_... |
ff86553c188ee0651dd2f0556ed7ffd592ee2861.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
//
// auto-generated by ops.py
//
__constant__ int dims_advec_mom_kernel2_x [4][2];
static int dims_advec_mom_kernel2_x_h [4][2] = {0};
//user function
__device__
inline void advec_mom_kernel2_x_gpu(ACC<double> &vel1,
const ACC<... | ff86553c188ee0651dd2f0556ed7ffd592ee2861.cu | //
// auto-generated by ops.py
//
__constant__ int dims_advec_mom_kernel2_x [4][2];
static int dims_advec_mom_kernel2_x_h [4][2] = {0};
//user function
__device__
inline void advec_mom_kernel2_x_gpu(ACC<double> &vel1,
const ACC<double> &node_mass_post,
const ACC<double> &node_mass_pre,
const ACC<double> &mom_f... |
87b20766ba959aa97a5c935e778a86ee7d395f2c.hip | // !!! This is a file automatically generated by hipify!!!
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#ifdef _WIN32
# define WINDOWS_LEAN_AND_MEAN
# define NOMINMAX
# include <windows.h>
#endif
// OpenGL Graphics includes
#include <glew.h>
#include <freeglut.h>
#include <cudaDefs.... | 87b20766ba959aa97a5c935e778a86ee7d395f2c.cu | #include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#ifdef _WIN32
# define WINDOWS_LEAN_AND_MEAN
# define NOMINMAX
# include <windows.h>
#endif
// OpenGL Graphics includes
#include <glew.h>
#include <freeglut.h>
#include <cudaDefs.h>
#include <imageManager.h>
// includes, cuda
#include <c... |
998800abb121a5af7855e424faca16733198baf5.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
#include <stdlib.h>
__global__ void add(int a, int b, int *c) {
*c = a + b;
}
int main(int argc, char *argv[]) {
int c;
int *dev_c;
hipError_t error = hipMalloc((void **)&dev_c, sizeof(int));
if(error ... | 998800abb121a5af7855e424faca16733198baf5.cu | #include <stdio.h>
#include <stdlib.h>
__global__ void add(int a, int b, int *c) {
*c = a + b;
}
int main(int argc, char *argv[]) {
int c;
int *dev_c;
cudaError_t error = cudaMalloc((void **)&dev_c, sizeof(int));
if(error != cudaSuccess) {
printf("Memory could not be allocated on device\n");
exit(EX... |
36521f24734b7d61118e14683ce1847744163274.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*
-- MAGMA (version 1.7.0) --
Univ. of Tennessee, Knoxville
Univ. of California, Berkeley
Univ. of Colorado, Denver
@date September 2015
@generated from ztranspose.cu normal z -> d, Fri Sep 1... | 36521f24734b7d61118e14683ce1847744163274.cu | /*
-- MAGMA (version 1.7.0) --
Univ. of Tennessee, Knoxville
Univ. of California, Berkeley
Univ. of Colorado, Denver
@date September 2015
@generated from ztranspose.cu normal z -> d, Fri Sep 11 18:29:21 2015
@author Stan Tomov
@author Mark Gates
*/
#include "common... |
98380c70655b01015fa5f5293d1055671d36766c.hip | // !!! This is a file automatically generated by hipify!!!
/**
* Project TACO: Parallel ACO algorithm for TSP
* 15-418 Parallel Algorithms - Final Project
* Ivan Wang, Carl Lin
*/
#include <stdio.h>
#include <hip/hip_runtime.h>
#include <hip/hip_runtime.h>
#include <hiprand/hiprand_kernel.h>
#include <math.h>
... | 98380c70655b01015fa5f5293d1055671d36766c.cu | /**
* Project TACO: Parallel ACO algorithm for TSP
* 15-418 Parallel Algorithms - Final Project
* Ivan Wang, Carl Lin
*/
#include <stdio.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <curand_kernel.h>
#include <math.h>
#include <math_functions.h>
#include "CycleTimer.h"
#include "ants.h"
#define MA... |
4e38e620c4989978bd6179245bbad452224aeb2a.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <ATen/ATen.h>
#include <THH/THHAtomics.cuh>
using namespace at; // temporal fix for pytorch<=0.4.1 (see #9848)
#define THREADS_PER_BLOCK 1024
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i =... | 4e38e620c4989978bd6179245bbad452224aeb2a.cu | #include <ATen/ATen.h>
#include <THC/THCAtomics.cuh>
using namespace at; // temporal fix for pytorch<=0.4.1 (see #9848)
#define THREADS_PER_BLOCK 1024
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \
i += blockDim.x * gridDim.x)
in... |
784ba4c1ab8427d9399f03202b996b243d2d78ca.hip | // !!! This is a file automatically generated by hipify!!!
/**
* @file
*
* @author Lawrence Murray <lawrence.murray@csiro.au>
* $Rev$
* $Date$
*/
#include "device.hpp"
#include "cuda.hpp"
#include <vector>
#ifdef ENABLE_CUDA
hipDeviceProp_t bi::device_prop;
#endif
int bi::chooseDevice(const int rank) {
int ... | 784ba4c1ab8427d9399f03202b996b243d2d78ca.cu | /**
* @file
*
* @author Lawrence Murray <lawrence.murray@csiro.au>
* $Rev$
* $Date$
*/
#include "device.hpp"
#include "cuda.hpp"
#include <vector>
#ifdef ENABLE_CUDA
cudaDeviceProp bi::device_prop;
#endif
int bi::chooseDevice(const int rank) {
int dev, num;
std::vector<int> valid;
/* build list of vali... |
654e9b8bd99dc9bb0b348a63ad2010e54f9cd586.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "head.h"
#define tpb 256
extern float *d_t;
extern float *d_it;
extern float *d_V;
extern float *d_dV2;
extern float *d_Vnew;
extern float *d_m;
extern float *d_h;
extern float *d_jj;
extern float *d_d;
extern float *d_f;... | 654e9b8bd99dc9bb0b348a63ad2010e54f9cd586.cu | #include "head.h"
#define tpb 256
extern float *d_t;
extern float *d_it;
extern float *d_V;
extern float *d_dV2;
extern float *d_Vnew;
extern float *d_m;
extern float *d_h;
extern float *d_jj;
extern float *d_d;
extern float *d_f;
extern float *d_X;
extern float *d_cai;
extern float *d_m0;
extern float *d_h0;
extern... |
9c06140c24c05ff20b0ac0235c03eadc4368f981.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <reduce.h>
__device__ float update(float old,float opOutput,float *extraParams) {
float mean = extraParams[1];
float curr = (opOutput - mean);
return old + powf(curr,2);
}
__device__... | 9c06140c24c05ff20b0ac0235c03eadc4368f981.cu | #include <reduce.h>
__device__ float update(float old,float opOutput,float *extraParams) {
float mean = extraParams[1];
float curr = (opOutput - mean);
return old + powf(curr,2);
}
__device__ float op(float d1,float d2,float *extraParams) {
return d1 + d2;
}
__device__ ... |
b16c109493f6daddb5c0aa16e36e1a03e843e954.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <THHUNN/THHUNN.h>
#include <THHUNN/common.h>
#include <THH/THHTensor.hpp>
#include <THH/THHThrustAllocator.cuh>
#include <thrust/device_ptr.h>
#include <thrust/execution_policy.h>
#include <thrust/iterator/constant_iterato... | b16c109493f6daddb5c0aa16e36e1a03e843e954.cu | #include <THCUNN/THCUNN.h>
#include <THCUNN/common.h>
#include <THC/THCTensor.hpp>
#include <THC/THCThrustAllocator.cuh>
#include <thrust/device_ptr.h>
#include <thrust/execution_policy.h>
#include <thrust/iterator/constant_iterator.h>
#include <thrust/transform_reduce.h>
#if CUDA_VERSION >= 7000 || defined __HIP_PLAT... |
6d77934834f3b9ae0c3c84052c35d6089e06c3d0.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "includes.h"
__global__ void getAggregateStartIndicesKernel(int size, int *fineAggregateSort, int *aggregateRemapIndex)
{
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if(idx < size)
{
if(idx == 0 || fineAggregateSort[id... | 6d77934834f3b9ae0c3c84052c35d6089e06c3d0.cu | #include "includes.h"
__global__ void getAggregateStartIndicesKernel(int size, int *fineAggregateSort, int *aggregateRemapIndex)
{
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if(idx < size)
{
if(idx == 0 || fineAggregateSort[idx] != fineAggregateSort[idx - 1])
{
aggregateRemapIndex[fineAggregateSort[idx]] = idx;
}... |
1d975390723bc8b3dafff7cb041b6eedd55299f6.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <comm_quda.h>
#include <gauge_fix_ovr_extra.h>
#include <thrust_helper.cuh>
namespace quda {
#if defined(GPU_GAUGE_ALG) && defined(MULTI_GPU)
struct BorderIdArg {
int X[4]; // grid dimensions
int border[4];
... | 1d975390723bc8b3dafff7cb041b6eedd55299f6.cu | #include <comm_quda.h>
#include <gauge_fix_ovr_extra.h>
#include <thrust_helper.cuh>
namespace quda {
#if defined(GPU_GAUGE_ALG) && defined(MULTI_GPU)
struct BorderIdArg {
int X[4]; // grid dimensions
int border[4];
BorderIdArg(int X_[4], int border_[4]) {
for ( int dir = 0; dir < 4; ++dir ) bord... |
483dd6dc56b0e4a2ea1cee902ace3a8a90f6882f.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include<math.h>
#include<iostream>
using namespace std;
__global__ void sum(float* input)
{
int tid = threadIdx.x;
int step_size = 1;
int number_of_threads = blockDim.x;
fl... | 483dd6dc56b0e4a2ea1cee902ace3a8a90f6882f.cu | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include<math.h>
#include<iostream>
using namespace std;
__global__ void sum(float* input)
{
int tid = threadIdx.x;
int step_size = 1;
int number_of_threads = blockDim.x;
float aux_size = (float)number_of_threads;
while (number_of_thr... |
d56e6273302bd5473d5fbdaaf74d270176efb499.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*
-- MAGMA (version 1.4.1) --
Univ. of Tennessee, Knoxville
Univ. of California, Berkeley
Univ. of Colorado, Denver
December 2013
@precisions normal c -> d s
*/
#include "common_magma.h"
#de... | d56e6273302bd5473d5fbdaaf74d270176efb499.cu | /*
-- MAGMA (version 1.4.1) --
Univ. of Tennessee, Knoxville
Univ. of California, Berkeley
Univ. of Colorado, Denver
December 2013
@precisions normal c -> d s
*/
#include "common_magma.h"
#define PRECISION_c
/* The version for fermi can be found in csymv_fermi.cu */
/* TODO: g... |
bd057c05f3a461ce527098667ad01336bb97d1d4.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
// ------------------------------------------------------------------
// Fast R-CNN
// Copyright (c) 2015 Microsoft
// Licensed under The MIT License [see fast-rcnn/LICENSE for details]
// Written by Ross Girshick
// ---------------... | bd057c05f3a461ce527098667ad01336bb97d1d4.cu | // ------------------------------------------------------------------
// Fast R-CNN
// Copyright (c) 2015 Microsoft
// Licensed under The MIT License [see fast-rcnn/LICENSE for details]
// Written by Ross Girshick
// ------------------------------------------------------------------
#include <cfloat>
#include <stdio.h... |
24d5977c07af709cba03597c8d3b32752d5592e6.hip | // !!! This is a file automatically generated by hipify!!!
/*
* gapped_extender_test.cpp
*
* Created on: 2012/11/20
* Author: shu
*/
#include <gtest/gtest.h>
#include <string>
#include <stdint.h>
#include <fstream>
#include <limits.h>
#include "../src/score_matrix.h"
#include "../src/alphabet_coder.h"
#incl... | 24d5977c07af709cba03597c8d3b32752d5592e6.cu | /*
* gapped_extender_test.cpp
*
* Created on: 2012/11/20
* Author: shu
*/
#include <gtest/gtest.h>
#include <string>
#include <stdint.h>
#include <fstream>
#include <limits.h>
#include "../src/score_matrix.h"
#include "../src/alphabet_coder.h"
#include "../src/sequence_type.h"
#include "../src/protein_type.... |
780db9fb3fc93a0be6fa234c02751de8ea961453.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
//
// Transpose.cu
// MNN
//
// Created by MNN on b'2021/12/09'.
// Copyright 2018, Alibaba Group Holding Limited
//
#include "Transpose_hip.cuh"
#include "core/Macro.h"
#include "MNNCUDADefine.hpp"
#include "MNNCUDAFunction.c... | 780db9fb3fc93a0be6fa234c02751de8ea961453.cu | //
// Transpose.cu
// MNN
//
// Created by MNN on b'2021/12/09'.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "Transpose.cuh"
#include "core/Macro.h"
#include "MNNCUDADefine.hpp"
#include "MNNCUDAFunction.cuh"
namespace MNN {
namespace CUDA {
template<typename T0, typename T1>
__global__ void UN... |
2138a1664da6dc9b318ed4a25bee196ec6e1903f.hip | // !!! This is a file automatically generated by hipify!!!
#include <cstdio>
#include "hip/hip_runtime.h"
#include "utils.cuh"
#include "../device/device_context.cuh"
#include "tsvd.h"
#include <ctime>
#include <thrust/iterator/counting_iterator.h>
#include<algorithm>
#include <thrust/sequence.h>
namespace tsvd
{
/**... | 2138a1664da6dc9b318ed4a25bee196ec6e1903f.cu | #include <cstdio>
#include "cuda_runtime.h"
#include "utils.cuh"
#include "../device/device_context.cuh"
#include "tsvd.h"
#include <ctime>
#include <thrust/iterator/counting_iterator.h>
#include<algorithm>
#include <thrust/sequence.h>
namespace tsvd
{
/**
* Division utility to get explained variance ratio
*
* @pa... |
c2650d9f6ba1721e7ac8bb41364bf00fc2e479e6.hip | // !!! This is a file automatically generated by hipify!!!
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you und... | c2650d9f6ba1721e7ac8bb41364bf00fc2e479e6.cu | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you ... |
54422a1a9502edcfe48d02d6b14b58cc55279da3.hip | // !!! This is a file automatically generated by hipify!!!
/******************************************************************************
MIT License
Copyright (c) 2016 Antti-Pekka Hynninen
Copyright (c) 2016 Oak Ridge National Laboratory (UT-Batelle)
Permission is hereby granted, free of charge, to any person obtai... | 54422a1a9502edcfe48d02d6b14b58cc55279da3.cu | /******************************************************************************
MIT License
Copyright (c) 2016 Antti-Pekka Hynninen
Copyright (c) 2016 Oak Ridge National Laboratory (UT-Batelle)
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation f... |
be08bb247f73c85e40cfd22868abc3891a9de343.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <hipcub/hipcub.hpp>
#include <hipcub/hipcub.hpp>
#include <moderngpu/transform.hxx>
#include <moderngpu/kernel_scan.hxx>
#include <moderngpu/kernel_load_balance.hxx>
using namespace mgpu;
using namespace cub;
__global__
... | be08bb247f73c85e40cfd22868abc3891a9de343.cu | #include <cub/util_allocator.cuh>
#include <cub/device/device_scan.cuh>
#include <moderngpu/transform.hxx>
#include <moderngpu/kernel_scan.hxx>
#include <moderngpu/kernel_load_balance.hxx>
using namespace mgpu;
using namespace cub;
__global__
void GetneighLen(uint32_t *nodes, int sizeNode, uint32_t *tr_offset, uint... |
6b2ff27d3659f51258bc0db8353a02a99613d97f.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/* 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 va... | 6b2ff27d3659f51258bc0db8353a02a99613d97f.cu |
/* 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* ... |
66ce1f044e90d9c8ab1ba1c04824926bd839958e.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*
* Copyright 1993-2006 NVIDIA Corporation. All rights reserved.
*
* NOTICE TO USER:
*
* This source code is subject to NVIDIA ownership rights under U.S. and
* international Copyright laws.
*
* This software and the... | 66ce1f044e90d9c8ab1ba1c04824926bd839958e.cu | /*
* Copyright 1993-2006 NVIDIA Corporation. All rights reserved.
*
* NOTICE TO USER:
*
* This source code is subject to NVIDIA ownership rights under U.S. and
* international Copyright laws.
*
* This software and the information contained herein is PROPRIETARY and
* CONFIDENTIAL to NVIDIA and is being... |
d43ea4f1a0878019413ed847cb51a76e6d7c86bd.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
#include <math.h>
#include <gpu_error.cuh>
__global__
void saxpy(int n, float a, float *x, float *y) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
int stride = gridDim.x * blockDim.x;
for (int ... | d43ea4f1a0878019413ed847cb51a76e6d7c86bd.cu | #include <stdio.h>
#include <math.h>
#include <gpu_error.cuh>
__global__
void saxpy(int n, float a, float *x, float *y) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
int stride = gridDim.x * blockDim.x;
for (int i = index; i < n; i += stride) {
y[i] = a * x[i] + y[i];
}
}
int main(void)... |
168c40f49e00cd0d0b08f76b95bc18608621d6d5.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "./argsort.cuh"
#include "./bitonic_sort.cuh"
#include "megdnn/basic_types.h"
#include "src/cuda/utils.cuh"
#include "src/cuda/hipcub/hipcub.hpp"
#include "src/cuda/cub/device/device_segmented_radix_sort.cuh"
#include "src... | 168c40f49e00cd0d0b08f76b95bc18608621d6d5.cu | #include "./argsort.cuh"
#include "./bitonic_sort.cuh"
#include "megdnn/basic_types.h"
#include "src/cuda/utils.cuh"
#include "src/cuda/cub/device/device_radix_sort.cuh"
#include "src/cuda/cub/device/device_segmented_radix_sort.cuh"
#include "src/cuda/kernel_common/diagnostic_prologue.cuh"
using namespace megdnn;
usi... |
43f768cfe599b760ef0004d9697d27e22747f56e.hip | // !!! This is a file automatically generated by hipify!!!
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
extern "C" {
void * alloc_gpu_mem( size_t N)
{
void*d;
int size = N *sizeof(float);
int err;
err = hipMalloc(&d, size);
if (err != 0) printf("cuda malloc error: %d\n", err);
return d;
}}
// s... | 43f768cfe599b760ef0004d9697d27e22747f56e.cu | #include <stdio.h>
#include <stdlib.h>
#include <time.h>
extern "C" {
void * alloc_gpu_mem( size_t N)
{
void*d;
int size = N *sizeof(float);
int err;
err = cudaMalloc(&d, size);
if (err != 0) printf("cuda malloc error: %d\n", err);
return d;
}}
// see kernels.cu for launch_kernel functions
extern "C" {
vo... |
d8844cf3c74ee005539426d699f32486aaae4204.hip | // !!! This is a file automatically generated by hipify!!!
#include<iostream>
#include<complex>
#include<stdlib.h>
#include <hip/hip_runtime.h>
#include <hip/hip_complex.h>
#include <math.h>
#include<hiprand/hiprand.h>
#include<hiprand/hiprand_kernel.h>
#include "stopwatch.hpp"
stopwatch<std::milli, float> sw;
#define... | d8844cf3c74ee005539426d699f32486aaae4204.cu | #include<iostream>
#include<complex>
#include<stdlib.h>
#include <cuda.h>
#include <cuComplex.h>
#include <math.h>
#include<curand.h>
#include<curand_kernel.h>
#include "stopwatch.hpp"
stopwatch<std::milli, float> sw;
#define RADIUS 3
#define FRAME_SIZE 4096*8*7
#define NBPSC 2
#define NSC 64
#define NCBPS 128
typ... |
62a7c612f709cc59ff67dfade587ebb4c0fb72fd.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "includes.h"
__global__ void bp_maxpool(float* d_preact, float* preact, float* p_output, float* nd_output, const int kernel_size, const int size, const int n_size, const int in_channel, bool SAME)
{
const int pos = blockIdx... | 62a7c612f709cc59ff67dfade587ebb4c0fb72fd.cu | #include "includes.h"
__global__ void bp_maxpool(float* d_preact, float* preact, float* p_output, float* nd_output, const int kernel_size, const int size, const int n_size, const int in_channel, bool SAME)
{
const int pos = blockIdx.x * blockDim.x + threadIdx.x;
const int totalPos = blockDim.x * gridDim.x;
const int N ... |
fb88d3e7f26b194f88a934abd1df19cd9e609b1e.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
__global__
void saxpy(int n, float a, float* x, float* y)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n) y[i] = a * x[i] + y[i];
}
int main(void)
{
int N = 1 << 20;
float* x, * y, * d_x, * d_y;
... | fb88d3e7f26b194f88a934abd1df19cd9e609b1e.cu | #include <stdio.h>
__global__
void saxpy(int n, float a, float* x, float* y)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n) y[i] = a * x[i] + y[i];
}
int main(void)
{
int N = 1 << 20;
float* x, * y, * d_x, * d_y;
x = (float*)malloc(N * sizeof(float));
y = (float*)malloc(N * sizeof(float));
cudaMa... |
526783aa0ebad9996054d3e157359e451b3d744a.hip | // !!! This is a file automatically generated by hipify!!!
/*
* (C) Copyright 1996-2016 ECMWF.
*
* This software is licensed under the terms of the Apache Licence Version 2.0
* which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
* In applying this licence, ECMWF does not waive the privileges and i... | 526783aa0ebad9996054d3e157359e451b3d744a.cu | /*
* (C) Copyright 1996-2016 ECMWF.
*
* This software is licensed under the terms of the Apache Licence Version 2.0
* which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
* In applying this licence, ECMWF does not waive the privileges and immunities
* granted to it by virtue of its status as an in... |
207d1a99bed514fbadb9d456d28d22ac04ad8692.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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 ... | 207d1a99bed514fbadb9d456d28d22ac04ad8692.cu | /* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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... |
7adf076be48f49d02139779ed23d621b71790251.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
// This exercise is for student to get familiarized with passing data between host and device
#include <stdio.h>
__global__
void vector_add(int *d_c, int *d_a, int *d_b, int n){
int i = blockIdx.x * blockDim.x + threadIdx.x;
... | 7adf076be48f49d02139779ed23d621b71790251.cu | // This exercise is for student to get familiarized with passing data between host and device
#include <stdio.h>
__global__
void vector_add(int *d_c, int *d_a, int *d_b, int n){
int i = blockIdx.x * blockDim.x + threadIdx.x;
d_c[i] = d_a[i] + d_b[i];
//printf("GPU[%d] done!\n", i);
}
int main(void){... |
ef80c6c3657bae7163d414c7041e1a13c82ac48e.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <string.h>
#include <iostream>
#include "timer.h"
using namespace std;
/* Utility function, use to do error checking.
Use this function like this:
checkCuda... | ef80c6c3657bae7163d414c7041e1a13c82ac48e.cu | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <string.h>
#include <iostream>
#include "timer.h"
using namespace std;
/* Utility function, use to do error checking.
Use this function like this:
checkCudaCall(cudaMalloc((void **) &deviceRGB, imgS * sizeof(color_t)));
And to check the res... |
d020a380e7a887ade564a828df1797c94f7ca7e5.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
// Modified from
// https://github.com/LikeLy-Journey/SegmenTron/blob/master/segmentron/modules/csrc/criss_cross_attention/ca_cuda.cu
#include <THH/THH.h>
#include <THH/THHDeviceUtils.cuh>
#include "cc_attention_cuda_kernel.cuh"
... | d020a380e7a887ade564a828df1797c94f7ca7e5.cu | // Modified from
// https://github.com/LikeLy-Journey/SegmenTron/blob/master/segmentron/modules/csrc/criss_cross_attention/ca_cuda.cu
#include <THC/THC.h>
#include <THC/THCDeviceUtils.cuh>
#include "cc_attention_cuda_kernel.cuh"
#include "pytorch_cuda_helper.hpp"
void CAForwardCUDAKernelLauncher(const Tensor t, con... |
0d2fcaeb3d9b279a4f1493a509762cf27484f9ee.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <stdio.h>
__global__ void kernelA(int N){
int globalThreadId = blockIdx.x * blockDim.x + threadIdx.x;
// Conditional statement to exit if index (globalThreadId) is out of bounds
if(globalThreadId >= N) ... | 0d2fcaeb3d9b279a4f1493a509762cf27484f9ee.cu | #include <stdio.h>
__global__ void kernelA(int N){
int globalThreadId = blockIdx.x * blockDim.x + threadIdx.x;
// Conditional statement to exit if index (globalThreadId) is out of bounds
if(globalThreadId >= N) {
return;
}
//Insert code here
printf("Hello from block %d, thread... |
c7ca18d736f2dc1b4cef4d25345f3309ea04fc72.hip | // !!! This is a file automatically generated by hipify!!!
#include <cstdio>
#include <cstdlib>
#include <cmath>
#include <ctime>
#include <cfloat>
#include <algorithm>
#include <chrono>
#include <iomanip>
#include <iostream>
#include <map>
#include <memory>
#include <random>
#include <sstream>
#include <string>
#incl... | c7ca18d736f2dc1b4cef4d25345f3309ea04fc72.cu | #include <cstdio>
#include <cstdlib>
#include <cmath>
#include <ctime>
#include <cfloat>
#include <algorithm>
#include <chrono>
#include <iomanip>
#include <iostream>
#include <map>
#include <memory>
#include <random>
#include <sstream>
#include <string>
#include <vector>
#include <cuda_runtime.h>
#include <device_la... |
98e6f67992f1d5458f86bd025c83c8d17fb34d13.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "includes.h"
__global__ void accumulate_kernel(float *x, int n, int groups, float *sum)
{
int k;
int i = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
if (i >= groups) return;
sum[i] = 0;
for(k = 0; k < n;... | 98e6f67992f1d5458f86bd025c83c8d17fb34d13.cu | #include "includes.h"
__global__ void accumulate_kernel(float *x, int n, int groups, float *sum)
{
int k;
int i = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
if (i >= groups) return;
sum[i] = 0;
for(k = 0; k < n; ++k){
sum[i] += x[k*groups + i];
}
} |
4bf9ed8003e9b35661c09218188909f422fb6695.hip | // !!! This is a file automatically generated by hipify!!!
// From PTT
// (, )
#include <hip/hip_runtime.h>
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
////////////////////////////////////////
// (GPU)
// __global__
// void
////////////////////////////////////////
__global__ void ... | 4bf9ed8003e9b35661c09218188909f422fb6695.cu | // From PTT
// (單一區塊, 多執行緒)
#include <cuda.h>
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
////////////////////////////////////////
// 向量加法的運算核心 (GPU)
// 函式前加 __global__ 即為核心
// 核心只傳回 void
////////////////////////////////////////
__global__ void gpu_add(float* c, float* a, float* b, in... |
288e26c827da19a8d1249faf248300e45a341112.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "includes.h"
__global__ void kernel(float *array, int size) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < size) {
array[index] += 1.f;
if (index == 0)
printf("### Array size: %d\n", size);
}
} | 288e26c827da19a8d1249faf248300e45a341112.cu | #include "includes.h"
__global__ void kernel(float *array, int size) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < size) {
array[index] += 1.f;
if (index == 0)
printf("### Array size: %d\n", size);
}
} |
454673db31159599ea4001c2f62d8b62a989167a.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "nbody.h"
#include <math.h>
#include <omp.h>
#include <stdio.h>
#include <stdlib.h> // drand48
#include <sys/time.h>
enum Initializer initializer = RANDOM_INITIALIZER;
#ifdef DUMP
FILE *output;
#endif
__global__ void Upd... | 454673db31159599ea4001c2f62d8b62a989167a.cu | #include "nbody.h"
#include <math.h>
#include <omp.h>
#include <stdio.h>
#include <stdlib.h> // drand48
#include <sys/time.h>
enum Initializer initializer = RANDOM_INITIALIZER;
#ifdef DUMP
FILE *output;
#endif
__global__ void UpdateParticle(const int nParticles,
struct ParticleArray *c... |
a28f4db34f27cc4e55e32247738f6379708a08a7.hip | // !!! This is a file automatically generated by hipify!!!
/* Copyright 2018 Stanford
*
* 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
... | a28f4db34f27cc4e55e32247738f6379708a08a7.cu | /* Copyright 2018 Stanford
*
* 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 wri... |
6bbd14aa77b75627692322f3491f4510e3a1ed7c.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#define TORCH_ASSERT_NO_OPERATORS
#include <ATen/Dispatch.h>
#include <ATen/native/TensorIterator.h>
#include <ATen/native/LinearAlgebra.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/hip/Loops.cuh>
#include <ATen/na... | 6bbd14aa77b75627692322f3491f4510e3a1ed7c.cu | #define TORCH_ASSERT_NO_OPERATORS
#include <ATen/Dispatch.h>
#include <ATen/native/TensorIterator.h>
#include <ATen/native/LinearAlgebra.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/cuda/Loops.cuh>
#include <ATen/native/SharedReduceOps.h>
#include <ATen/native/ReduceOps.h>
#include <c10/core/Scalar.h>... |
1b093fcc0b3c79946d3a4518ad2c802bd4cb2fe0.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "includes.h"
__global__ void CopyConnectionsCoordinatesKernel( int *connectionMatrix, float *pointsCoordinates, float *vertexData, int *connectionCount, int maxCells )
{
int threadId = blockDim.x*blockIdx.y*gridDim.x //r... | 1b093fcc0b3c79946d3a4518ad2c802bd4cb2fe0.cu | #include "includes.h"
__global__ void CopyConnectionsCoordinatesKernel( int *connectionMatrix, float *pointsCoordinates, float *vertexData, int *connectionCount, int maxCells )
{
int threadId = blockDim.x*blockIdx.y*gridDim.x //rows preceeding current row in grid
+ blockDim.x*blockIdx.x //blocks preceeding curren... |
39b9e86df456101fcd95ba2150c03f8db4df014d.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/*
* ******************************************************************************
* *
* *
* * This program and the accompanying materials are made available under the
* * terms of the Apache License, Version 2.0 which is... | 39b9e86df456101fcd95ba2150c03f8db4df014d.cu | /*
* ******************************************************************************
* *
* *
* * This program and the accompanying materials are made available under the
* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
* *
* * See the NOT... |
90b490704dc3727e4879d2fcb963f3e4a3a01834.hip | // !!! This is a file automatically generated by hipify!!!
#include <primitiv/config.h>
#include <iostream>
#include <primitiv/devices/cuda/device.h>
#include <primitiv/devices/cuda/ops/common.h>
#include <primitiv/internal/cuda/utils.h>
namespace primitiv {
namespace devices {
void CUDA::dump_description() const {... | 90b490704dc3727e4879d2fcb963f3e4a3a01834.cu | #include <primitiv/config.h>
#include <iostream>
#include <primitiv/devices/cuda/device.h>
#include <primitiv/devices/cuda/ops/common.h>
#include <primitiv/internal/cuda/utils.h>
namespace primitiv {
namespace devices {
void CUDA::dump_description() const {
using std::cerr;
using std::endl;
cerr << "Device "... |
b61ed1f0ad7749786fcf9a3c6db6fc38cec6e7d7.hip | // !!! This is a file automatically generated by hipify!!!
/**
* Copyright (c) 2020 Xiaomi Corporation (authors: Daniel Povey, Haowen Qiu,
* Wei Kang)
* Mobvoi Inc. (authors: Fangjun Kuang)
*
* See LICENSE for clarification regarding m... | b61ed1f0ad7749786fcf9a3c6db6fc38cec6e7d7.cu | /**
* Copyright (c) 2020 Xiaomi Corporation (authors: Daniel Povey, Haowen Qiu,
* Wei Kang)
* Mobvoi Inc. (authors: Fangjun Kuang)
*
* See LICENSE for clarification regarding multiple authors
*
* Licensed under the Apache License, Ve... |
b19081090de3175f678c51449d3572b64f177167.hip | // !!! This is a file automatically generated by hipify!!!
/***********************************************************************************
Implementing Breadth first search on CUDA using algorithm given in HiPC'07
paper "Accelerating Large Graph Algorithms on the GPU using CUDA"
Copyright (c) 2008 Internati... | b19081090de3175f678c51449d3572b64f177167.cu | /***********************************************************************************
Implementing Breadth first search on CUDA using algorithm given in HiPC'07
paper "Accelerating Large Graph Algorithms on the GPU using CUDA"
Copyright (c) 2008 International Institute of Information Technology - Hyderabad.
Al... |
5a601ce0bc1d6567768a230949c11e88e0bd7510.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/**
* intList.cu
*/
#include "header/intList.h"
__device__ void copyTabDev(uint64_t *src, uint64_t *dest, int size) {
if (blockIdx.x == 0) {
int tid = threadIdx.x;
if (tid < size) {
dest[tid] = src[tid];
}
}
}
//1 blo... | 5a601ce0bc1d6567768a230949c11e88e0bd7510.cu | /**
* intList.cu
*/
#include "header/intList.h"
__device__ void copyTabDev(uint64_t *src, uint64_t *dest, int size) {
if (blockIdx.x == 0) {
int tid = threadIdx.x;
if (tid < size) {
dest[tid] = src[tid];
}
}
}
//1 block ; size thread
__global__ void copyTabGPU(uint64_t *src, uint64_t *dest, int size) {
... |
87a74e1c8c82f4b4d0879873dbd5c09c3d5e6ad3.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <basicOps.cuh>
#include <hiprand/hiprand.h>
#include <hiprand/hiprand_kernel.h>
#include <float.h>
const int NUM_THREADS = 32;
__global__ void kGetNonZeroElements(float *A, float *out, int size)
{
const unsigned int num... | 87a74e1c8c82f4b4d0879873dbd5c09c3d5e6ad3.cu | #include <basicOps.cuh>
#include <curand.h>
#include <curand_kernel.h>
#include <float.h>
const int NUM_THREADS = 32;
__global__ void kGetNonZeroElements(float *A, float *out, int size)
{
const unsigned int numThreads = blockDim.x * gridDim.x;
const int idx = (blockIdx.x * blockDim.x) + threadIdx.x;
for (unsigned... |
bb96edd9bedd5a15c6937b8038707cfe5e62a49b.hip | // !!! This is a file automatically generated by hipify!!!
/* Sample code for Sparse-Matrix-Vector multiplication.*/
#include <iostream>
#include <cstdlib>
#include <time.h>
#include <hip/hip_runtime.h>
#include <minigun/minigun.h>
#include "../samples_utils.h"
#include "../samples_io.h"
struct GData {
float* cur{n... | bb96edd9bedd5a15c6937b8038707cfe5e62a49b.cu | /* Sample code for Sparse-Matrix-Vector multiplication.*/
#include <iostream>
#include <cstdlib>
#include <time.h>
#include <cuda_runtime.h>
#include <minigun/minigun.h>
#include "../samples_utils.h"
#include "../samples_io.h"
struct GData {
float* cur{nullptr};
float* next{nullptr};
float* weight{nullptr};
i... |
f2e98459274f88ddd86fa3ab3796e844f9a3f509.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "Indice2D.h"
#include "DomaineMathGPUs.h"
#include "DomaineMaths.h"
#include "IndiceXY.h"
#include "cudaTools.h"
#include "Sphere.h"
#include "ColorToolCuda.h"
#include "FonctionsRaytracing.h"
/*---------------------------... | f2e98459274f88ddd86fa3ab3796e844f9a3f509.cu | #include "Indice2D.h"
#include "DomaineMathGPUs.h"
#include "DomaineMaths.h"
#include "IndiceXY.h"
#include "cudaTools.h"
#include "Sphere.h"
#include "ColorToolCuda.h"
#include "FonctionsRaytracing.h"
/*----------------------------------------------------------------------*\
|* Declaration *|
\*-------------... |
1a081687cf859bfd2f4cb02233364e8401b67e28.hip | // !!! This is a file automatically generated by hipify!!!
#include "LinearSearch.h"
#include "hip/hip_runtime.h"
#include "device_launch_parameters.h"
#include <random>
#include <math.h>
#include <memory>
namespace {
__global__
void searchWithCuda(int64_t * arr, size_t N, int64_t x) {
int index = threadIdx.x;
... | 1a081687cf859bfd2f4cb02233364e8401b67e28.cu | #include "LinearSearch.h"
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <random>
#include <math.h>
#include <memory>
namespace {
__global__
void searchWithCuda(int64_t * arr, size_t N, int64_t x) {
int index = threadIdx.x;
int stride = blockDim.x;
for (int i = index; i < N; i += ... |
244ab14cf63924a5438b4819e8b9491596b5a9ba.hip | // !!! This is a file automatically generated by hipify!!!
#include "GoL.h"
#include <iostream>
#include <fstream>
#include <iomanip>
int max_generations = 1000;
int n_small = 9;
int n_large = 20;
// Perform a single run
void timedRun(int sz, bool small, std::ofstream &myfile, hipEvent_t start, hipEvent_t stop){
... | 244ab14cf63924a5438b4819e8b9491596b5a9ba.cu | #include "GoL.h"
#include <iostream>
#include <fstream>
#include <iomanip>
int max_generations = 1000;
int n_small = 9;
int n_large = 20;
// Perform a single run
void timedRun(int sz, bool small, std::ofstream &myfile, cudaEvent_t start, cudaEvent_t stop){
// Set input parameters
auto rows = sz*10;
aut... |
51c2e4e8267ddc08cd84a060140692254a5cb2ce.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "task_filljtr.cuh"
template<typename T>
__global__ void d_fillJTr( DeviceMemory<T>* mem ) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if( idx >= mem->nParamPoints ) return;
if( !mem->paramsUsed[idx] ) return;
T... | 51c2e4e8267ddc08cd84a060140692254a5cb2ce.cu | #include "task_filljtr.cuh"
template<typename T>
__global__ void d_fillJTr( DeviceMemory<T>* mem ) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if( idx >= mem->nParamPoints ) return;
if( !mem->paramsUsed[idx] ) return;
T sumx = 0;
T sumy = 0;
T sumx2 = 0;
T sumy2 = 0;
int idxm = idx % mem->frameW;
if... |
984c7a679f1500f4d3534214ae122e9ee04ecde8.hip | // !!! This is a file automatically generated by hipify!!!
#include <algorithm>
#include <cfloat>
#include <vector>
#include "caffe/layers/triplet_loss_layer.hpp"
#include "caffe/util/math_functions.hpp"
namespace caffe {
template <typename Dtype>
void TripletLossLayer<Dtype>::Forward_gpu(
const vector<Blob<Dty... | 984c7a679f1500f4d3534214ae122e9ee04ecde8.cu | #include <algorithm>
#include <cfloat>
#include <vector>
#include "caffe/layers/triplet_loss_layer.hpp"
#include "caffe/util/math_functions.hpp"
namespace caffe {
template <typename Dtype>
void TripletLossLayer<Dtype>::Forward_gpu(
const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top) {
Colle... |
b18b55eecada4380003854e32ed485a6964f1f4a.hip | // !!! This is a file automatically generated by hipify!!!
// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// The MIT License (M... | b18b55eecada4380003854e32ed485a6964f1f4a.cu | // ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// The MIT License (MIT)
//
// Copyright (c) 2020 www.open3d.org
//
// Permissio... |
04f4e1c21df38739f3544a05fa0e9df45a3c0ab0.hip | // !!! This is a file automatically generated by hipify!!!
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <hip/hip_runtime.h>
#include <hiprand/hiprand_kernel.h>
// Calculate an estimated value of pi using n random Monte-Carlo draws
__global__ void estimate_pi(int seed, int per_thread, hiprandState... | 04f4e1c21df38739f3544a05fa0e9df45a3c0ab0.cu | #include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <cuda.h>
#include <curand_kernel.h>
// Calculate an estimated value of pi using n random Monte-Carlo draws
__global__ void estimate_pi(int seed, int per_thread, curandState *state, unsigned int *result)
{
int id = threadIdx.x + blockIdx.x * blockD... |
47fbeebea4d5be2748d67be0f4c4c933897e617f.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <ATen/ATen.h>
#include <ATen/InitialTensorOptions.h>
#include <ATen/NativeFunctions.h>
#include <ATen/hip/HIPApplyUtils.cuh>
#include <ATen/hip/HIPContext.h>
#include <ATen/native/TensorFactories.h>
#include <ATen/native/hi... | 47fbeebea4d5be2748d67be0f4c4c933897e617f.cu | #include <ATen/ATen.h>
#include <ATen/InitialTensorOptions.h>
#include <ATen/NativeFunctions.h>
#include <ATen/cuda/CUDAApplyUtils.cuh>
#include <ATen/cuda/CUDAContext.h>
#include <ATen/native/TensorFactories.h>
#include <ATen/native/cuda/Resize.cuh>
#include <c10/util/Exception.h>
#include <THC/THCGeneral.h>
#include... |
1a7216b79e804be5c07965ee6b1d37826f611b7f.hip | // !!! This is a file automatically generated by hipify!!!
#include "CUDAFCM.h"
#include <iostream>
#include <cmath>
#include <omp.h>
#include <stdio.h>
#include <hiprand/hiprand.h>
#include <hip/hip_runtime.h>
#include <vector>
/*
Code: Fuzzy C-means
Developer: Dennis Carnelossi Furlaneto
License: MIT
*/
namespace CU... | 1a7216b79e804be5c07965ee6b1d37826f611b7f.cu | #include "CUDAFCM.h"
#include <iostream>
#include <cmath>
#include <omp.h>
#include <stdio.h>
#include <curand.h>
#include <cuda.h>
#include <vector>
/*
Code: Fuzzy C-means
Developer: Dennis Carnelossi Furlaneto
License: MIT
*/
namespace CUDAFCM
{
#define N_THREADS 256
#define CUDA_CALL(x) do { if((x)!=cudaSucce... |
c239315edbbd9423b711fc17eef37db7bc7dab37.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "cudarray/common.hpp"
#include "cudarray/elementwise.hpp"
namespace cudarray {
#define BINARY_OP(name, operation) \
template <typename Ta, typename Tb, typename Tc> \
struct name { \
__device__ Tc operator()(const Ta ... | c239315edbbd9423b711fc17eef37db7bc7dab37.cu | #include "cudarray/common.hpp"
#include "cudarray/elementwise.hpp"
namespace cudarray {
#define BINARY_OP(name, operation) \
template <typename Ta, typename Tb, typename Tc> \
struct name { \
__device__ Tc operator()(const Ta a, const Tb b) { \
return operation; \
} \
};
BINARY_OP(AddOp, a + b)
BINARY_OP(D... |
9220f1569768bf0d244b82830640beea594432e3.hip | // !!! This is a file automatically generated by hipify!!!
#ifndef _MYNN
#define _MYNN
#include <hip/hip_runtime.h>
#include <math.h>
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <vector>
using namespace std;
#include "types.h"
#include "libnn.h"
#define... | 9220f1569768bf0d244b82830640beea594432e3.cu | #ifndef _MYNN
#define _MYNN
#include <cuda.h>
#include <math.h>
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <vector>
using namespace std;
#include "types.h"
#include "libnn.h"
#define LAYERS (2)
#define NINPUTS (2)
#define NOUTPUTS (2)
#define MIDDLE ... |
36e94d6e1515d07ec47d8695a75ccefcbe624894.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "ristretto/base_ristretto_layer.hpp"
#include "ristretto/base_ristretto_layer.cuh"
namespace caffe {
template <typename Dtype>
void BaseRistrettoLayer<Dtype>::QuantizeWeights_gpu(
vector<shared_ptr<Blob<Dtype> > > w... | 36e94d6e1515d07ec47d8695a75ccefcbe624894.cu | #include "ristretto/base_ristretto_layer.hpp"
#include "ristretto/base_ristretto_layer.cuh"
namespace caffe {
template <typename Dtype>
void BaseRistrettoLayer<Dtype>::QuantizeWeights_gpu(
vector<shared_ptr<Blob<Dtype> > > weights_quantized, const int rounding,
const bool bias_term) {
Dtype* weight = we... |
kernel_functions_for_tex_2d.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
texture<int, 2, hipReadModeElementType> tex_2d;
__global__ void read_texture_2d(int nx, int ny){
int x = threadIdx.x + blockDim.x * blockIdx.x;
int y = threadIdx.y + blockDim.y * blockIdx.y;
if (x < nx && y < ny){
i... | kernel_functions_for_tex_2d.cu | texture<int, 2, cudaReadModeElementType> tex_2d;
__global__ void read_texture_2d(int nx, int ny){
int x = threadIdx.x + blockDim.x * blockIdx.x;
int y = threadIdx.y + blockDim.y * blockIdx.y;
if (x < nx && y < ny){
int value = tex2D(tex_2d, x, y);
printf("x: %d, y: %d, my value is %d\n", x, y, ... |
1fddf82d690852ad20c715ef6904c8bf20b36757.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <chrono>
#include "array2d.h"
#include "cuda_helper.h"
#include "ns2d.h"
#define value_t double
#define index_t int
// constants
__constant__ value_t c_zero, c_two, c_half;
__global__ void predictor(index_t Nx, index_t N... | 1fddf82d690852ad20c715ef6904c8bf20b36757.cu | #include <chrono>
#include "array2d.h"
#include "cuda_helper.h"
#include "ns2d.h"
#define value_t double
#define index_t int
// constants
__constant__ value_t c_zero, c_two, c_half;
__global__ void predictor(index_t Nx, index_t Ny,
value_t *u, value_t *v, value_t *p,
... |
2688a0872f112b8e826f471dded80da854940803.hip | // !!! This is a file automatically generated by hipify!!!
//Program to multiply square matrix with activation vector, both filled with random numbers, and then to multiply the resulting vector by the matrix again- repeat for the
//specified number of iterations.
#include <hip/hip_runtime.h>
#include <rocblas.h>
#inc... | 2688a0872f112b8e826f471dded80da854940803.cu | //Program to multiply square matrix with activation vector, both filled with random numbers, and then to multiply the resulting vector by the matrix again- repeat for the
//specified number of iterations.
#include <cuda.h>
#include <cublas_v2.h>
#include <curand.h>
#include <cstdlib>
#include <iostream>
using std::co... |
77d50ad86abeb0e57d2131adb6213475c6fbcc2c.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "mat_ones_kernel.h"
#define BLOCK_SIZE 32
__global__ void mat_ones_kernel(const float *__restrict__ src, float *__restrict__ dst,
int m, int n) {
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = b... | 77d50ad86abeb0e57d2131adb6213475c6fbcc2c.cu | #include "mat_ones_kernel.h"
#define BLOCK_SIZE 32
__global__ void mat_ones_kernel(const float *__restrict__ src, float *__restrict__ dst,
int m, int n) {
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
if (row < m && col < n) {
dst[row * n... |
a379dbe091ae1d93e56dc84ea98b17cb2c99fc13.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
//#include <cutil.h> // cutil32.lib
#include <string.h>
#include "system_kern.cu"
extern Particles_struct specie;
extern "C"
{
int iDivUp (int a, int b)
{
return (a % b != 0) ? (a / b + 1) : (a / b);
}
void computeNumBloc... | a379dbe091ae1d93e56dc84ea98b17cb2c99fc13.cu | //#include <cutil.h> // cutil32.lib
#include <string.h>
#include "system_kern.cu"
extern Particles_struct specie;
extern "C"
{
int iDivUp (int a, int b)
{
return (a % b != 0) ? (a / b + 1) : (a / b);
}
void computeNumBlocks (int numPnts, int maxThreads, int &numBlocks, int &numThreads)
{
//numThreads = ... |
ae7ce8f1e13e5a896d8d79b158ac6147a095eebb.hip | // !!! This is a file automatically generated by hipify!!!
/*******************************************************
* Copyright (c) 2014, ArrayFire
* All rights reserved.
*
* This file is distributed under 3-clause BSD license.
* The complete license agreement can be obtained at:
* http://arrayfire.com/licenses/B... | ae7ce8f1e13e5a896d8d79b158ac6147a095eebb.cu | /*******************************************************
* Copyright (c) 2014, ArrayFire
* All rights reserved.
*
* This file is distributed under 3-clause BSD license.
* The complete license agreement can be obtained at:
* http://arrayfire.com/licenses/BSD-3-Clause
**********************************************... |
6c5cc2fba7c78a399edc6c0b43b0ee75968b2aa6.hip | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "includes.h"
__global__ void ThirdAngle(int *a1, int *a2, int *a3)
{
*a3 = (180-*a1-*a2);
} | 6c5cc2fba7c78a399edc6c0b43b0ee75968b2aa6.cu | #include "includes.h"
__global__ void ThirdAngle(int *a1, int *a2, int *a3)
{
*a3 = (180-*a1-*a2);
} |
c4bb06aefc4b50b5272b981ac6c84ec9a0088c10.hip | // !!! This is a file automatically generated by hipify!!!
#include <Chain.h>
#include <Config.h>
#include <constants.h>
#include <functions.h>
#include <stdlib.h>
#include <stdio.h>
#include <sys/stat.h>
#include <unistd.h>
__host__ void oneChain(Chain *host_a, Chain *dev_a, Config *cfg){
++cfg->chainNum;
if(cfg... | c4bb06aefc4b50b5272b981ac6c84ec9a0088c10.cu | #include <Chain.h>
#include <Config.h>
#include <constants.h>
#include <functions.h>
#include <stdlib.h>
#include <stdio.h>
#include <sys/stat.h>
#include <unistd.h>
__host__ void oneChain(Chain *host_a, Chain *dev_a, Config *cfg){
++cfg->chainNum;
if(cfg->verbose)
printf("\n Chain %d of %d.\n", cfg->chainNu... |
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