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/*
* Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/* Sample CUDA application for shared memory bank conflicts.
* Transposes a N x N square matrix of float elements in
* global memory and generates an output matrix in global memory.
*
*/
#include <stdio.h>
#include <cuda_runtime_api.h>
#define DEFAULT_KERNEL_OPTION 1
#define DEFAULT_MATRIX_SIZE 512
#define RUNTIME_API_CALL(apiFuncCall) \
do \
{ \
cudaError_t _status = apiFuncCall; \
if (_status != cudaSuccess) \
{ \
fprintf(stderr, "%s:%d: error: function %s failed with error %s.\n", __FILE__, \
__LINE__, #apiFuncCall, cudaGetErrorString(_status)); \
exit(EXIT_FAILURE); \
} \
} while (0)
#define PRINT_PROGRAM_USAGE() \
fprintf(stderr, "Usage: %s [<kernel option>] [<matrix size>] [<cache config option>]\n" \
" Default kernel option: %d\n" \
" Use 1 for '%s' and 2 for '%s'\n" \
" Default matrix size: %d\n" \
" Matrix size should be greater than or equal to tile size: %d and" \
" must be an integral multiple of tile size.\n" \
" Default cache config option: none\n" \
" Options: none|shared|l1|equal\n", \
argv[0], DEFAULT_KERNEL_OPTION, \
"transposeCoalesced", "transposeNoBankConflicts", \
DEFAULT_MATRIX_SIZE, TILE_DIM)
// Each block transposes a tile of (TILE_DIM x TILE_DIM) elements
// using TILE_DIM x BLOCK_ROWS threads,
// so that each thread transposes (TILE_DIM / BLOCK_ROWS) elements.
// TILE_DIM must be an integral multiple of BLOCK_ROWS
#define TILE_DIM 32
#define BLOCK_ROWS 8
// Coalesced global memory transpose with shared memory bank conflicts
__global__ void transposeCoalesced(float* odata, float* idata, int width, int height)
{
__shared__ float tile[TILE_DIM][TILE_DIM];
int xIndex = blockIdx.x * TILE_DIM + threadIdx.x;
int yIndex = blockIdx.y * TILE_DIM + threadIdx.y;
int indexIn = xIndex + yIndex*width;
xIndex = blockIdx.y * TILE_DIM + threadIdx.x;
yIndex = blockIdx.x * TILE_DIM + threadIdx.y;
int indexOut = xIndex + yIndex*height;
for (int i = 0; i < TILE_DIM; i += BLOCK_ROWS)
{
tile[threadIdx.y + i][threadIdx.x] = idata[indexIn + i * width];
}
__syncthreads();
for (int i = 0; i < TILE_DIM; i += BLOCK_ROWS)
{
odata[indexOut + i * height] = tile[threadIdx.x][threadIdx.y + i];
}
}
// Coalesced global memory transpose with no shared memory bank conflicts
__global__ void transposeNoBankConflicts(float* odata, float* idata, int width, int height)
{
__shared__ float tile[TILE_DIM][TILE_DIM + 1];
int xIndex = blockIdx.x * TILE_DIM + threadIdx.x;
int yIndex = blockIdx.y * TILE_DIM + threadIdx.y;
int indexIn = xIndex + yIndex*width;
xIndex = blockIdx.y * TILE_DIM + threadIdx.x;
yIndex = blockIdx.x * TILE_DIM + threadIdx.y;
int indexOut = xIndex + yIndex*height;
for (int i = 0; i < TILE_DIM; i += BLOCK_ROWS)
{
tile[threadIdx.y + i][threadIdx.x] = idata[indexIn + i * width];
}
__syncthreads();
for (int i = 0; i < TILE_DIM; i += BLOCK_ROWS)
{
odata[indexOut + i * height] = tile[threadIdx.x][threadIdx.y + i];
}
}
void computeTransposeGold(float* gold, float* idata, const int size_x, const int size_y)
{
for (int y = 0; y < size_y; ++y)
{
for (int x = 0; x < size_x; ++x)
{
gold[(x * size_y) + y] = idata[(y * size_x) + x];
}
}
}
bool compareData(const float* reference, const float* data, const unsigned int len)
{
const float epsilon = 0.01f;
for (unsigned int i = 0; i < len; ++i)
{
float diff = reference[i] - data[i];
if ((diff > epsilon) || (diff < -epsilon))
return false;
}
return true;
}
int setCacheConfig(const char *cacheConfigStr, const void *kernel)
{
const int NumCacheConfigs = 4;
const char *cacheConfigOptionsStr[NumCacheConfigs] = { "none", "shared", "l1", "equal"};
cudaFuncCache cacheConfigOptions[NumCacheConfigs] = {cudaFuncCachePreferNone, cudaFuncCachePreferShared, cudaFuncCachePreferL1, cudaFuncCachePreferEqual};
cudaFuncCache cacheConfigOption;
int i;
for(i = 0; i < NumCacheConfigs; i++)
{
if (strcmp(cacheConfigStr, cacheConfigOptionsStr[i]) == 0)
{
cacheConfigOption = cacheConfigOptions[i];
break;
}
}
if (i >= NumCacheConfigs)
{
fprintf(stderr, "Invalid cache config option : '%s'\n", cacheConfigStr);
return -1;
}
fprintf(stderr, "Set cache config option : '%s'\n", cacheConfigStr);
RUNTIME_API_CALL(cudaFuncSetCacheConfig(kernel, cacheConfigOption));
return 0;
}
int main(int argc, char* argv[])
{
int kernelOption = DEFAULT_KERNEL_OPTION;
if (argc > 1)
{
kernelOption = atoi(argv[1]);
}
void (*kernel)(float*, float*, int, int);
const char* kernelName;
if (kernelOption == 1)
{
kernel = &transposeCoalesced;
kernelName = "transposeCoalesced";
}
else if (kernelOption == 2)
{
kernel = &transposeNoBankConflicts;
kernelName = "transposeNoBankConflicts";
}
else
{
fprintf(stderr, "** Invalid kernel option: %s\n", argv[1]);
PRINT_PROGRAM_USAGE();
exit(EXIT_FAILURE);
}
int matrixSize = DEFAULT_MATRIX_SIZE;
if (argc > 2)
{
matrixSize = atoi(argv[2]);
}
if ((matrixSize < TILE_DIM) || (matrixSize % TILE_DIM != 0))
{
fprintf(stderr, "** Invalid matrix size: %s\n", argv[2]);
PRINT_PROGRAM_USAGE();
exit(EXIT_FAILURE);
}
// size of memory required to store the matrix
size_t memSize = sizeof(float) * matrixSize * matrixSize;
// allocate host memory
float* h_idata = (float*)malloc(memSize);
float* h_odata = (float*)malloc(memSize);
float* transposeGold = (float*)malloc(memSize);
// allocate device memory
float *d_idata, *d_odata;
RUNTIME_API_CALL(cudaMalloc((void**)&d_idata, memSize));
RUNTIME_API_CALL(cudaMalloc((void**)&d_odata, memSize));
// initialize host data
for (int i = 0; i < (matrixSize * matrixSize); ++i)
{
h_idata[i] = (float)i;
}
// copy host data to device
RUNTIME_API_CALL(cudaMemcpy(d_idata, h_idata, memSize, cudaMemcpyHostToDevice));
printf("\nmatrix size: %dx%d (%dx%d tiles), kernel name: '%s', "
"tile size: %dx%d, block size: %dx%d\n",
matrixSize, matrixSize,
matrixSize/TILE_DIM, matrixSize/TILE_DIM,
kernelName,
TILE_DIM, TILE_DIM,
TILE_DIM, BLOCK_ROWS);
if ((argc > 3) && setCacheConfig(argv[3], (const void *)kernel))
{
PRINT_PROGRAM_USAGE();
exit(EXIT_FAILURE);
}
// execution configuration parameters
dim3 grid(matrixSize / TILE_DIM, matrixSize / TILE_DIM);
dim3 threads(TILE_DIM, BLOCK_ROWS);
kernel<<<grid, threads>>>(d_odata, d_idata, matrixSize, matrixSize);
cudaError_t err = cudaGetLastError();
if (err != cudaSuccess)
{
fprintf(stderr, "Failed to launch '%s' kernel (error code %s)!\n",
kernelName, cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
RUNTIME_API_CALL(cudaMemcpy(h_odata, d_odata, memSize, cudaMemcpyDeviceToHost));
// Compute reference transpose solution
computeTransposeGold(transposeGold, h_idata, matrixSize, matrixSize);
bool res = compareData(transposeGold, h_odata, matrixSize * matrixSize);
if (res == false)
{
fprintf(stderr, "** '%s' kernel FAILED\n", kernelName);
exit(EXIT_FAILURE);
}
printf("Done\n");
return 0;
}
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