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mp2_implement.cu
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mp2_implement.cu
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#include <wb.h>
#define BLOCK_SIZE 8
#define wbCheck(stmt) do { \
cudaError_t err = stmt; \
if (err != cudaSuccess) { \
wbLog(ERROR, "Failed to run stmt ", #stmt); \
return -1; \
} \
} while(0)
int ceil(int a, int b){
return int((a + b - 1) / b);
}
// 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.x * blockDim.x + threadIdx.x;
int col = blockIdx.y * blockDim.y + threadIdx.y;
float PValue = 0;
if(row < numCColumns && col < numCColumns){
for(int j = 0; j < numAColumns; j ++){
PValue += A[row * numAColumns + j] * B[j * 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(sizeof(float) * numCRows * numCColumns);
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);
wbLog(TRACE, "The dimensions of C are ", numCRows, " x ", numCColumns);
wbTime_start(GPU, "Allocating GPU memory.");
//@@ Allocate GPU memory here
cudaMalloc((void**) &deviceA, sizeof(float) * numAColumns * numARows);
cudaMalloc((void**) &deviceB, sizeof(float) * numBColumns * numBRows);
cudaMalloc((void**) &deviceC, sizeof(float) * numCColumns * numCRows);
wbTime_stop(GPU, "Allocating GPU memory.");
wbTime_start(GPU, "Copying input memory to the GPU.");
//@@ Copy memory to the GPU here
cudaMemcpy(deviceA, hostA, sizeof(float) * numAColumns * numARows, cudaMemcpyHostToDevice);
cudaMemcpy(deviceB, hostB, sizeof(float) * numBColumns * numBRows, cudaMemcpyHostToDevice);
wbTime_stop(GPU, "Copying input memory to the GPU.");
//@@ Initialize the grid and block dimensions here
dim3 DimGrid(ceil(numCColumns * numCRows, BLOCK_SIZE), ceil(numCColumns * numCRows, BLOCK_SIZE), 1);
dim3 DimBlock(BLOCK_SIZE, BLOCK_SIZE,1);
wbTime_start(Compute, "Performing CUDA computation");
//@@ Launch the GPU Kernel here
matrixMultiply<<<DimGrid, DimBlock>>>(deviceA, deviceB, deviceC, numARows, numAColumns, numBRows, numBColumns, numCRows, numCColumns);
cudaThreadSynchronize();
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, sizeof(float) * numCColumns * numCRows, 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");
float res = 0;
for(int index = 0; index < numAColumns; index ++){
res += hostA[index] * hostB[index * numBColumns];
}
printf("res is \t %f\n", res);
wbSolution(args, hostC, numCRows, numCColumns);
free(hostA);
free(hostB);
free(hostC);
return 0;
}