#include #include // Kernel function to add the elements of two arrays __global__ void add(int n, float *x, float *y) { int index = threadIdx.x; int stride = blockDim.x; for (int i = index; i < n; i += stride) y[i] = x[i] + y[i]; } /* __global__ void add(int n, float *x, float *y) { for (int i = 0; i < n; i++) y[i] = x[i] + y[i]; } */ int main(void) { int N = 1<<20; float *x, *y; // Allocate Unified Memory – accessible from CPU or GPU cudaMallocManaged(&x, N*sizeof(float)); cudaMallocManaged(&y, N*sizeof(float)); // initialize x and y arrays on the host for (int i = 0; i < N; i++) { x[i] = 1.0f; y[i] = 2.0f; } // Run kernel on 1M elements on the GPU add<<<1, 256>>>(N, x, y); // Wait for GPU to finish before accessing on host cudaDeviceSynchronize(); // Check for errors (all values should be 3.0f) float maxError = 0.0f; for (int i = 0; i < N; i++) maxError = fmax(maxError, fabs(y[i]-3.0f)); std::cout << "Max error: " << maxError << std::endl; // Free memory cudaFree(x); cudaFree(y); return 0; }