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Basic_Matrix_Multiplication.cu
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116 lines (94 loc) · 4.27 KB
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#include <wb.h>
#define TILE_WIDTH 16
#define wbCheck(stmt) \
do { \
cudaError_t err = stmt; \
if (err != cudaSuccess) { \
wbLog(ERROR, "Failed to run stmt ", #stmt); \
wbLog(ERROR, "Got CUDA error ... ", cudaGetErrorString(err)); \
return -1; \
} \
} while (0)
// Compute C = A * B
__global__ void matrixMultiply(float *A, float *B, float *C, int numARows,
int numAColumns, int numBRows, int numBColumns,
int numCRows, int numCColumns) {
//@@ Insert code to implement matrix multiplication here
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
if (row < numCRows && col < numCColumns)
{
float value = 0.0;
for (int i = 0; i < numBRows; i++)
value += A[row * numAColumns + i] * B[i * numBColumns + col];
C[row * numCColumns + col] = value;
}
}
int main(int argc, char **argv) {
wbArg_t args;
float *hostA; // The A matrix
float *hostB; // The B matrix
float *hostC; // The output C matrix
float *deviceA;
float *deviceB;
float *deviceC;
int numARows; // number of rows in the matrix A
int numAColumns; // number of columns in the matrix A
int numBRows; // number of rows in the matrix B
int numBColumns; // number of columns in the matrix B
int numCRows; // number of rows in the matrix C (you have to set this)
int numCColumns; // number of columns in the matrix C (you have to set this)
args = wbArg_read(argc, argv);
wbTime_start(Generic, "Importing data and creating memory on host");
hostA =
( float * )wbImport(wbArg_getInputFile(args, 0), &numARows, &numAColumns);
hostB =
( float * )wbImport(wbArg_getInputFile(args, 1), &numBRows, &numBColumns);
//@@ Set numCRows and numCColumns
numCRows = numARows;
numCColumns = numBColumns;
//@@ Allocate the hostC matrix
wbTime_stop(Generic, "Importing data and creating memory on host");
int sizeA = numARows * numAColumns * sizeof(float);
int sizeB = numBRows * numBColumns * sizeof(float);
int sizeC = numCRows * numCColumns * sizeof(float);
hostC = (float*) malloc(sizeC);
wbLog(TRACE, "The dimensions of A are ", numARows, " x ", numAColumns);
wbLog(TRACE, "The dimensions of B are ", numBRows, " x ", numBColumns);
wbTime_start(GPU, "Allocating GPU memory.");
//@@ Allocate GPU memory here
wbCheck(cudaMalloc((void**)&deviceA, sizeA));
wbCheck(cudaMalloc((void**)&deviceB, sizeB));
wbCheck(cudaMalloc((void**)&deviceC, sizeC));
wbTime_stop(GPU, "Allocating GPU memory.");
wbTime_start(GPU, "Copying input memory to the GPU.");
//@@ Copy memory to the GPU here
wbCheck(cudaMemcpy(deviceA, hostA, sizeA, cudaMemcpyHostToDevice));
wbCheck(cudaMemcpy(deviceB, hostB, sizeB, cudaMemcpyHostToDevice));
wbTime_stop(GPU, "Copying input memory to the GPU.");
//@@ Initialize the grid and block dimensions here
dim3 gridDim3((numCColumns - 1)/TILE_WIDTH + 1, (numCRows - 1)/TILE_WIDTH + 1, 1);
dim3 blockDim3(TILE_WIDTH, TILE_WIDTH, 1);
wbTime_start(Compute, "Performing CUDA computation");
//@@ Launch the GPU Kernel here
matrixMultiply <<< gridDim3, blockDim3 >>> (deviceA, deviceB, deviceC,
numARows, numAColumns, numBRows,
numBColumns, numCRows, numCColumns);
cudaDeviceSynchronize();
wbTime_stop(Compute, "Performing CUDA computation");
wbTime_start(Copy, "Copying output memory to the CPU");
//@@ Copy the GPU memory back to the CPU here
wbCheck(cudaMemcpy(hostC, deviceC, sizeC, cudaMemcpyDeviceToHost));
wbTime_stop(Copy, "Copying output memory to the CPU");
wbTime_start(GPU, "Freeing GPU Memory");
//@@ Free the GPU memory here
wbCheck(cudaFree(deviceA));
wbCheck(cudaFree(deviceB));
wbCheck(cudaFree(deviceC));
wbTime_stop(GPU, "Freeing GPU Memory");
wbSolution(args, hostC, numCRows, numCColumns);
free(hostA);
free(hostB);
free(hostC);
return 0;
}