darknet/src/cuda.c

179 lines
4.0 KiB
C

int gpu_index = 0;
#ifdef GPU
#include "cuda.h"
#include "utils.h"
#include "blas.h"
#include <assert.h>
#include <stdlib.h>
#include <time.h>
void cuda_set_device(int n)
{
gpu_index = n;
cudaError_t status = cudaSetDevice(n);
check_error(status);
}
int cuda_get_device()
{
int n = 0;
cudaError_t status = cudaGetDevice(&n);
check_error(status);
return n;
}
void check_error(cudaError_t status)
{
//cudaDeviceSynchronize();
cudaError_t status2 = cudaGetLastError();
if (status != cudaSuccess)
{
const char *s = cudaGetErrorString(status);
char buffer[256];
printf("CUDA Error: %s\n", s);
assert(0);
snprintf(buffer, 256, "CUDA Error: %s", s);
error(buffer);
}
if (status2 != cudaSuccess)
{
const char *s = cudaGetErrorString(status);
char buffer[256];
printf("CUDA Error Prev: %s\n", s);
assert(0);
snprintf(buffer, 256, "CUDA Error Prev: %s", s);
error(buffer);
}
}
dim3 cuda_gridsize(size_t n){
size_t k = (n-1) / BLOCK + 1;
size_t x = k;
size_t y = 1;
if(x > 65535){
x = ceil(sqrt(k));
y = (n-1)/(x*BLOCK) + 1;
}
dim3 d = {x, y, 1};
//printf("%ld %ld %ld %ld\n", n, x, y, x*y*BLOCK);
return d;
}
#ifdef CUDNN
cudnnHandle_t cudnn_handle()
{
static int init[16] = {0};
static cudnnHandle_t handle[16];
int i = cuda_get_device();
if(!init[i]) {
cudnnCreate(&handle[i]);
init[i] = 1;
}
return handle[i];
}
#endif
cublasHandle_t blas_handle()
{
static int init[16] = {0};
static cublasHandle_t handle[16];
int i = cuda_get_device();
if(!init[i]) {
cublasCreate(&handle[i]);
init[i] = 1;
}
return handle[i];
}
float *cuda_make_array(float *x, size_t n)
{
float *x_gpu;
size_t size = sizeof(float)*n;
cudaError_t status = cudaMalloc((void **)&x_gpu, size);
check_error(status);
if(x){
status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
check_error(status);
} else {
fill_gpu(n, 0, x_gpu, 1);
}
if(!x_gpu) error("Cuda malloc failed\n");
return x_gpu;
}
void cuda_random(float *x_gpu, size_t n)
{
static curandGenerator_t gen[16];
static int init[16] = {0};
int i = cuda_get_device();
if(!init[i]){
curandCreateGenerator(&gen[i], CURAND_RNG_PSEUDO_DEFAULT);
curandSetPseudoRandomGeneratorSeed(gen[i], time(0));
init[i] = 1;
}
curandGenerateUniform(gen[i], x_gpu, n);
check_error(cudaPeekAtLastError());
}
float cuda_compare(float *x_gpu, float *x, size_t n, char *s)
{
float *tmp = calloc(n, sizeof(float));
cuda_pull_array(x_gpu, tmp, n);
//int i;
//for(i = 0; i < n; ++i) printf("%f %f\n", tmp[i], x[i]);
axpy_cpu(n, -1, x, 1, tmp, 1);
float err = dot_cpu(n, tmp, 1, tmp, 1);
printf("Error %s: %f\n", s, sqrt(err/n));
free(tmp);
return err;
}
int *cuda_make_int_array(int *x, size_t n)
{
int *x_gpu;
size_t size = sizeof(int)*n;
cudaError_t status = cudaMalloc((void **)&x_gpu, size);
check_error(status);
if(x){
status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
check_error(status);
}
if(!x_gpu) error("Cuda malloc failed\n");
return x_gpu;
}
void cuda_free(float *x_gpu)
{
cudaError_t status = cudaFree(x_gpu);
check_error(status);
}
void cuda_push_array(float *x_gpu, float *x, size_t n)
{
size_t size = sizeof(float)*n;
cudaError_t status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
check_error(status);
}
void cuda_pull_array(float *x_gpu, float *x, size_t n)
{
size_t size = sizeof(float)*n;
cudaError_t status = cudaMemcpy(x, x_gpu, size, cudaMemcpyDeviceToHost);
check_error(status);
}
float cuda_mag_array(float *x_gpu, size_t n)
{
float *temp = calloc(n, sizeof(float));
cuda_pull_array(x_gpu, temp, n);
float m = mag_array(temp, n);
free(temp);
return m;
}
#else
void cuda_set_device(int n){}
#endif