mirror of
https://github.com/guilhermewerner/nvidia-cuda
synced 2025-06-15 12:44:20 +00:00
91 lines
2.1 KiB
Plaintext
91 lines
2.1 KiB
Plaintext
#include <stdio.h>
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__global__ void initWith(float num, float *a, int N)
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{
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int index = threadIdx.x + blockIdx.x * blockDim.x;
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int stride = blockDim.x * gridDim.x;
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for (int i = index; i < N; i += stride)
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{
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a[i] = num;
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}
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}
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__global__ void addVectorsInto(float *result, float *a, float *b, int N)
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{
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int index = threadIdx.x + blockIdx.x * blockDim.x;
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int stride = blockDim.x * gridDim.x;
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for (int i = index; i < N; i += stride)
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{
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result[i] = a[i] + b[i];
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}
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}
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void checkElementsAre(float target, float *vector, int N)
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{
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for (int i = 0; i < N; i++)
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{
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if (vector[i] != target)
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{
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printf("FAIL: vector[%d] - %0.0f does not equal %0.0f\n", i, vector[i], target);
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exit(1);
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}
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}
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printf("Success! All values calculated correctly.\n");
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}
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int main()
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{
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int deviceId;
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int numberOfSMs;
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cudaGetDevice(&deviceId);
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cudaDeviceGetAttribute(&numberOfSMs, cudaDevAttrMultiProcessorCount, deviceId);
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const int N = 2 << 24;
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size_t size = N * sizeof(float);
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float *a;
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float *b;
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float *c;
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cudaMallocManaged(&a, size);
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cudaMallocManaged(&b, size);
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cudaMallocManaged(&c, size);
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cudaMemPrefetchAsync(a, size, deviceId);
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cudaMemPrefetchAsync(b, size, deviceId);
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cudaMemPrefetchAsync(c, size, deviceId);
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size_t threadsPerBlock;
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size_t numberOfBlocks;
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threadsPerBlock = 256;
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numberOfBlocks = 32 * numberOfSMs;
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cudaError_t addVectorsErr;
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cudaError_t asyncErr;
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initWith<<<numberOfBlocks, threadsPerBlock>>>(3, a, N);
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initWith<<<numberOfBlocks, threadsPerBlock>>>(4, b, N);
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initWith<<<numberOfBlocks, threadsPerBlock>>>(0, c, N);
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addVectorsInto<<<numberOfBlocks, threadsPerBlock>>>(c, a, b, N);
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addVectorsErr = cudaGetLastError();
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if (addVectorsErr != cudaSuccess)
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printf("Error: %s\n", cudaGetErrorString(addVectorsErr));
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asyncErr = cudaDeviceSynchronize();
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if (asyncErr != cudaSuccess)
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printf("Error: %s\n", cudaGetErrorString(asyncErr));
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checkElementsAre(7, c, N);
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cudaFree(a);
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cudaFree(b);
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cudaFree(c);
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}
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