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CUDA MatrixMultiplication

The document contains a CUDA program for performing matrix multiplication. It allocates memory for matrices on both the host and device, initializes them, and executes the multiplication using a kernel. The program also measures and prints the elapsed time for the operation.

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32 views2 pages

CUDA MatrixMultiplication

The document contains a CUDA program for performing matrix multiplication. It allocates memory for matrices on both the host and device, initializes them, and executes the multiplication using a kernel. The program also measures and prints the elapsed time for the operation.

Uploaded by

yaseeniqbal365
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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CUDA Program for Matrix Multiplication

#include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>

#define BLOCK_SIZE 16

__global__ void matrix_multiply(float *a, float *b, float *c, int n) {


int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
float sum = 0.0f;

if (row < n && col < n) {


for (int i = 0; i < n; ++i) {
sum += a[row * n + i] * b[i * n + col];
}
c[row * n + col] = sum;
}
}

int main() {
int n = 1024;
size_t size = n * n * sizeof(float);

float *a, *b, *c;


float *d_a, *d_b, *d_c;
cudaEvent_t start, stop;
float elapsed_time;

// Allocate host memory


a = (float*)malloc(size);
b = (float*)malloc(size);
c = (float*)malloc(size);

// Initialize matrices
for (int i = 0; i < n * n; ++i) {
a[i] = i % n;
b[i] = i % n;
}

// Allocate device memory


cudaMalloc(&d_a, size);
cudaMalloc(&d_b, size);
cudaMalloc(&d_c, size);

// Copy data to device


cudaMemcpy(d_a, a, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, size, cudaMemcpyHostToDevice);

// Configure kernel launch parameters


dim3 threads(BLOCK_SIZE, BLOCK_SIZE);
dim3 blocks((n + threads.x - 1) / threads.x, (n + threads.y - 1) /
threads.y);

// Launch and time the kernel


cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start);

matrix_multiply<<<blocks, threads>>>(d_a, d_b, d_c, n);

cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsed_time, start, stop);

// Copy result to host


cudaMemcpy(c, d_c, size, cudaMemcpyDeviceToHost);

printf("Elapsed time for matrix multiplication: %.2f ms\n", elapsed_time);

// Free memory
cudaFree(d_a); cudaFree(d_b); cudaFree(d_c);
free(a); free(b); free(c);

return 0;
}

Output:
Elapsed time for matrix multiplication: 58.74 ms

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