gpu
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37 changed files with 2669 additions and 371 deletions
106
gpu/tp3/c/src/ex1.cu
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106
gpu/tp3/c/src/ex1.cu
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#include <cstddef>
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#include <iostream>
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#define RANGE(I, FROM, TO) \
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size_t I = FROM; \
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I < TO; \
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I += 1
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//
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// example: CUDA_CHECK( cudaMalloc(dx, x, N*sizeof(int) );
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//
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#define CUDA_CHECK(code) \
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{ cuda_check((code), __FILE__, __LINE__); }
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inline void cuda_check(cudaError_t code, const char* file, int line) {
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if (code != cudaSuccess) {
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std::cout << file << ':' << line << ": [CUDA ERROR] " << cudaGetErrorString(code) << std::endl;
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std::abort();
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}
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}
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constexpr int bloc_count = 128; // constexpr equivalent to blockDim.x in CUDA kernel
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constexpr int threads_per_bloc = 32; // constexpr equivalent to gridDim.x in CUDA kernel
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constexpr int B = bloc_count;
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constexpr int T = threads_per_bloc;
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//
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// step 01
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//
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// dx: array of size N
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// dy: array of size N
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// dz: array of size B
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//
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typedef struct {
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size_t from;
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size_t to;
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} StrideRange;
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#define FMT_RANGE(R) "[" << R.from << "," << R.to << "]"
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__device__ __host__ static inline StrideRange stride_range_for(size_t array_length, size_t block_dim, size_t grid_dim,
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size_t block_id, size_t thread_id) {
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auto global_threads = block_dim * grid_dim;
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auto items_per_threads = (array_length / global_threads) + 1;
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auto global_thread_index = block_id * block_dim + thread_id;
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auto from = global_thread_index * items_per_threads;
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auto to = from + items_per_threads;
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return StrideRange{from, to};
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}
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__global__ void dot(int N, const int* dx, const int* dy, int* dz) {
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__shared__ int buffer[T];
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auto range = stride_range_for(N, blockDim.x, gridDim.x, blockIdx.x, threadIdx.x);
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if (range.from >= N) return;
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buffer[threadIdx.x] = 0;
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for (RANGE(i, range.from, range.to))
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if (i < N) buffer[threadIdx.x] += dx[i] * dy[i];
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__syncthreads();
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if (threadIdx.x != 0) return;
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dz[blockIdx.x] = 0;
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for (RANGE(i, 0, T)) dz[blockIdx.x] += buffer[i];
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}
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int main() {
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constexpr int N = 1e6;
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int* x = (int*)malloc(N * sizeof(int));
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int* y = (int*)malloc(N * sizeof(int));
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int host_expected_result = 0;
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for (int i = 0; i < N; i++) {
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x[i] = i % 10;
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y[i] = i % 3 - 1;
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host_expected_result += x[i] * y[i];
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}
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// step 02
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int *dx, *dy, *dz;
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auto size = N * sizeof(int);
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auto res_size = B * sizeof(int);
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cudaMalloc(&dx, size);
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cudaMalloc(&dy, size);
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cudaMemcpy(dx, x, size, cudaMemcpyHostToDevice);
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cudaMemcpy(dy, y, size, cudaMemcpyHostToDevice);
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cudaMalloc(&dz, res_size);
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// step 03
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dot<<<B, T>>>(N, dx, dy, dz);
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int result = 0;
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int* z = (int*)malloc(res_size);
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cudaMemcpy(z, dz, res_size, cudaMemcpyDeviceToHost);
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for (RANGE(i, 0, B)) result += z[i];
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// checking results
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if (host_expected_result == result) {
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std::cout << "Success" << std::endl;
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} else {
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std::cout << "Error" << std::endl;
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std::cout << " expected: " << host_expected_result << std::endl;
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std::cout << " got: " << result << std::endl;
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}
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free(x);
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free(y);
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return 0;
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}
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119
gpu/tp3/c/src/ex2.cu
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gpu/tp3/c/src/ex2.cu
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#include <iostream>
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//
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// example: CUDA_CHECK( cudaMalloc(dx, x, N*sizeof(int) );
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//
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#define CUDA_CHECK(code) \
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{ cuda_check((code), __FILE__, __LINE__); }
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inline void cuda_check(cudaError_t code, const char* file, int line) {
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if (code != cudaSuccess) {
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std::cout << file << ':' << line << ": [CUDA ERROR] " << cudaGetErrorString(code) << std::endl;
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std::abort();
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}
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}
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constexpr int bloc_count = 128; // constexpr equivalent to blockDim.x in CUDA kernel
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constexpr int threads_per_bloc = 32; // constexpr equivalent to gridDim.x in CUDA kernel
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constexpr int B = bloc_count;
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constexpr int T = threads_per_bloc;
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//
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// step 04
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//
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// dx: array of size N
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// dy: array of size N
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// dz: array of size B
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//
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#define RANGE(I, FROM, TO) \
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size_t I = FROM; \
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I < TO; \
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I += 1
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#define loop while (1)
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typedef struct {
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size_t from;
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size_t to;
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} StrideRange;
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#define FMT_RANGE(R) "[" << R.from << "," << R.to << "]"
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__device__ __host__ static inline StrideRange stride_range_for(size_t array_length, size_t block_dim, size_t grid_dim,
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size_t block_id, size_t thread_id) {
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auto global_threads = block_dim * grid_dim;
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auto items_per_threads = (array_length / global_threads) + 1;
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auto global_thread_index = block_id * block_dim + thread_id;
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auto from = global_thread_index * items_per_threads;
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auto to = from + items_per_threads;
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return StrideRange{from, to};
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}
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__device__ void reduce_rec(int N, int* array) {
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auto length = N;
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auto thread_id = threadIdx.x;
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loop {
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if (length <= 1) return;
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auto half = length / 2;
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auto used_threads = half;
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if (thread_id >= used_threads) return;
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__syncthreads();
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array[thread_id] += array[thread_id + half];
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length = half;
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}
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}
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__global__ void dot(int N, const int* dx, const int* dy, int* dz) {
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__shared__ int buffer[T];
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auto range = stride_range_for(N, blockDim.x, gridDim.x, blockIdx.x, threadIdx.x);
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if (range.from >= N) return;
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buffer[threadIdx.x] = 0;
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for (RANGE(i, range.from, range.to))
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if (i < N) buffer[threadIdx.x] += dx[i] * dy[i];
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reduce_rec(T, buffer);
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if (threadIdx.x != 0) return;
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dz[blockIdx.x] = buffer[0];
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}
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int main() {
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constexpr int N = 1e6;
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int* x = (int*)malloc(N * sizeof(int));
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int* y = (int*)malloc(N * sizeof(int));
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int host_expected_result = 0;
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for (int i = 0; i < N; i++) {
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x[i] = i % 10;
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y[i] = i % 3 - 1;
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host_expected_result += x[i] * y[i];
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}
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// step 05
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int result = 0;
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int *dx, *dy, *dz;
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auto size = N * sizeof(int);
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auto res_size = B * sizeof(int);
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cudaMalloc(&dx, size);
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cudaMalloc(&dy, size);
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cudaMemcpy(dx, x, size, cudaMemcpyHostToDevice);
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cudaMemcpy(dy, y, size, cudaMemcpyHostToDevice);
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cudaMalloc(&dz, res_size);
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dot<<<B, T>>>(N, dx, dy, dz);
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int* z;
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z = (int*)malloc(res_size);
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cudaMemcpy(z, dz, res_size, cudaMemcpyDeviceToHost);
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for (RANGE(i, 0, B)) result += z[i];
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// checking results
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if (host_expected_result == result) {
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std::cout << "Success" << std::endl;
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} else {
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std::cout << "Error" << std::endl;
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std::cout << " expected: " << host_expected_result << std::endl;
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std::cout << " got: " << result << std::endl;
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}
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free(x);
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free(y);
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return 0;
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}
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