File size: 6,294 Bytes
26d5b81 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 | #ifndef NEUROFLOW_CUDA_CONTEXT_HPP
#define NEUROFLOW_CUDA_CONTEXT_HPP
#ifdef USE_CUDA
#include <cstddef>
#include <stdexcept>
#include <string>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#define CUDA_CHECK(call) \
do { \
cudaError_t err = (call); \
if (err != cudaSuccess) { \
throw std::runtime_error( \
std::string("[CUDA ERROR] ") + cudaGetErrorString(err) \
+ " at " + __FILE__ + ":" + std::to_string(__LINE__)); \
} \
} while (0)
#define CUBLAS_CHECK(call) \
do { \
cublasStatus_t status = (call); \
if (status != CUBLAS_STATUS_SUCCESS) { \
throw std::runtime_error( \
std::string("[CUBLAS ERROR] code=") + std::to_string(status) \
+ " at " + __FILE__ + ":" + std::to_string(__LINE__)); \
} \
} while (0)
namespace neuroflow {
class CudaContext {
public:
static CudaContext& instance() {
static CudaContext ctx;
return ctx;
}
bool initialize(int device_id = 0) {
if (initialized_) return true;
int device_count = 0;
cudaError_t err = cudaGetDeviceCount(&device_count);
if (err != cudaSuccess || device_count == 0) {
std::cerr << "[CUDA WARNING] No CUDA-capable GPU detected" << std::endl;
return false;
}
if (device_id >= device_count) {
std::cerr << "[CUDA WARNING] Device " << device_id
<< " not available (count=" << device_count << ")" << std::endl;
return false;
}
CUDA_CHECK(cudaSetDevice(device_id));
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, device_id));
if (prop.major < 8) {
std::cerr << "[CUDA WARNING] GPU Compute Capability " << prop.major
<< "." << prop.minor << " < 8.0 (Ampere required)" << std::endl;
return false;
}
CUDA_CHECK(cudaStreamCreate(&stream_));
CUBLAS_CHECK(cublasCreate(&cublas_handle_));
CUBLAS_CHECK(cublasSetStream(cublas_handle_, stream_));
device_id_ = device_id;
initialized_ = true;
std::cerr << "[CUDA] Initialized on " << prop.name
<< " (CC " << prop.major << "." << prop.minor
<< ", " << prop.totalGlobalMem / (1024*1024) << " MB)" << std::endl;
return true;
}
void finalize() {
if (!initialized_) return;
CUBLAS_CHECK(cublasDestroy(cublas_handle_));
CUDA_CHECK(cudaStreamDestroy(stream_));
initialized_ = false;
device_id_ = -1;
}
void sgemm(bool transA, bool transB,
int M, int N, int K,
float alpha, const float* d_A, int lda,
const float* d_B, int ldb,
float beta, float* d_C, int ldc) {
cublasOperation_t opA = transA ? CUBLAS_OP_T : CUBLAS_OP_N;
cublasOperation_t opB = transB ? CUBLAS_OP_T : CUBLAS_OP_N;
CUBLAS_CHECK(cublasSgemm(cublas_handle_, opA, opB,
M, N, K, &alpha, d_A, lda, d_B, ldb, &beta, d_C, ldc));
}
void sgemm_rowmajor(bool transA, bool transB,
int M, int N, int K,
float alpha, const float* d_A, int lda,
const float* d_B, int ldb,
float beta, float* d_C, int ldc) {
cublasOperation_t opA = transB ? CUBLAS_OP_T : CUBLAS_OP_N;
cublasOperation_t opB = transA ? CUBLAS_OP_T : CUBLAS_OP_N;
CUBLAS_CHECK(cublasSgemm(cublas_handle_, opA, opB,
N, M, K, &alpha, d_B, ldb, d_A, lda, &beta, d_C, ldc));
}
void* alloc(size_t bytes) {
void* d_ptr = nullptr;
CUDA_CHECK(cudaMalloc(&d_ptr, bytes));
return d_ptr;
}
void free(void* d_ptr) {
if (d_ptr) CUDA_CHECK(cudaFree(d_ptr));
}
void copy_h2d(void* dst, const void* src, size_t bytes) {
CUDA_CHECK(cudaMemcpyAsync(dst, src, bytes, cudaMemcpyHostToDevice, stream_));
}
void copy_d2h(void* dst, const void* src, size_t bytes) {
CUDA_CHECK(cudaMemcpyAsync(dst, src, bytes, cudaMemcpyDeviceToHost, stream_));
}
void copy_d2d(void* dst, const void* src, size_t bytes) {
CUDA_CHECK(cudaMemcpyAsync(dst, src, bytes, cudaMemcpyDeviceToDevice, stream_));
}
void synchronize() {
CUDA_CHECK(cudaStreamSynchronize(stream_));
}
bool is_available() const { return initialized_; }
size_t free_memory() const {
if (!initialized_) return 0;
size_t free = 0, total = 0;
CUDA_CHECK(cudaMemGetInfo(&free, &total));
return free;
}
size_t total_memory() const {
if (!initialized_) return 0;
size_t free = 0, total = 0;
CUDA_CHECK(cudaMemGetInfo(&free, &total));
return total;
}
cudaStream_t stream() const { return stream_; }
cublasHandle_t cublas_handle() const { return cublas_handle_; }
private:
CudaContext() = default;
~CudaContext() { finalize(); }
CudaContext(const CudaContext&) = delete;
CudaContext& operator=(const CudaContext&) = delete;
cublasHandle_t cublas_handle_ = nullptr;
cudaStream_t stream_ = nullptr;
bool initialized_ = false;
int device_id_ = -1;
};
} // namespace neuroflow
#endif // USE_CUDA
#endif // NEUROFLOW_CUDA_CONTEXT_HPP |