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MP2.c
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#include <wb.h>
#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 < numARows) && (Col < numBColumns)) {
float Pvalue = 0;
for (int k = 0; k < numAColumns; ++k) {
Pvalue += A[Row * numAColumns + k] * B[k * numBColumns + Col];
}
C[Row * numCColumns + Col] = Pvalue;
}
}
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
hostC = (float*) malloc(numCColumns * numCRows * sizeof(float));
wbTime_stop(Generic, "Importing data and creating memory on host");
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
int sizeA = numARows * numAColumns * sizeof(float);
int sizeB = numBRows * numBColumns * sizeof(float);
int sizeC = numCRows * numCColumns * sizeof(float);
cudaMalloc((void **) &deviceA, sizeA);
cudaMalloc((void **) &deviceB, sizeB);
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
cudaMemcpy(deviceA, hostA, sizeA, cudaMemcpyHostToDevice);
cudaMemcpy(deviceB, hostB, sizeB, cudaMemcpyHostToDevice);
wbTime_stop(GPU, "Copying input memory to the GPU.");
//@@ Initialize the grid and block dimensions here
dim3 dimGridC(ceil(numCColumns * 1.0 / 2), ceil(numCRows * 1.0 / 2), 1);
dim3 dimBlock(2, 2, 1);
wbTime_start(Compute, "Performing CUDA computation");
//@@ Launch the GPU Kernel here
matrixMultiply<<<dimGridC, dimBlock>>>(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
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
cudaFree(deviceA);
cudaFree(deviceB);
cudaFree(deviceC);
wbTime_stop(GPU, "Freeing GPU Memory");
wbSolution(args, hostC, numCRows, numCColumns);
free(hostA);
free(hostB);
free(hostC);
return 0;
}