diff options
Diffstat (limited to 'matrix')
-rw-r--r-- | matrix/cuda_helper.h | 75 | ||||
-rw-r--r-- | matrix/cukernel.cu | 17 | ||||
-rw-r--r-- | matrix/cukernel.h | 20 | ||||
-rw-r--r-- | matrix/cumatrix.c | 87 | ||||
-rw-r--r-- | matrix/generic/cukernel.cu | 571 | ||||
-rw-r--r-- | matrix/generic/cumatrix.c | 493 | ||||
-rw-r--r-- | matrix/generic/elem_type.h | 22 | ||||
-rw-r--r-- | matrix/generic/matrix.c | 155 | ||||
-rw-r--r-- | matrix/generic/matrix.h | 19 | ||||
-rw-r--r-- | matrix/generic/mmatrix.c | 122 | ||||
-rw-r--r-- | matrix/init.c | 35 | ||||
-rw-r--r-- | matrix/init.lua | 77 | ||||
-rw-r--r-- | matrix/mmatrix.c | 77 |
13 files changed, 0 insertions, 1770 deletions
diff --git a/matrix/cuda_helper.h b/matrix/cuda_helper.h deleted file mode 100644 index fde6f18..0000000 --- a/matrix/cuda_helper.h +++ /dev/null @@ -1,75 +0,0 @@ -#ifndef NERV_CUDA_HELPER_H -#define NERV_CUDA_HELPER_H -#include "cuda.h" -#include "cuda_runtime.h" -#include "driver_types.h" -#include "cublas_v2.h" -#define CUBLAS_SAFE_SYNC_CALL(call) \ - do { \ - cublasStatus_t err = (call); \ - if (err != CUBLAS_STATUS_SUCCESS) \ - nerv_error(L, "cumatrix cublas error: %s at %s:%d", \ - cublasGetErrorString(err), __FILE__, __LINE__); \ - cudaDeviceSynchronize(); \ - } while (0) - -#define CUDA_SAFE_CALL(call) \ - do { \ - cudaError_t err = (call); \ - if (err != cudaSuccess) \ - nerv_error(L, "cumatrix CUDA error: %s at %s:%d", \ - cudaGetErrorString(err), __FILE__, __LINE__); \ - } while (0) - -#define CUDA_SAFE_SYNC_CALL(call) \ - do { \ - CUDA_SAFE_CALL(call); \ - cudaDeviceSynchronize(); \ - } while (0) - -#define CHECK_SAME_DIMENSION(a, b) \ - do { \ - if (!(a->nrow == b->nrow && a->ncol == b->ncol)) \ - nerv_error(L, "matrices should be of the same dimension"); \ - } while (0) - -static const char *cublasGetErrorString(cublasStatus_t err) { - switch (err) - { - case CUBLAS_STATUS_SUCCESS: - return "CUBLAS_STATUS_SUCCESS"; - case CUBLAS_STATUS_NOT_INITIALIZED: - return "CUBLAS_STATUS_NOT_INITIALIZED"; - case CUBLAS_STATUS_ALLOC_FAILED: - return "CUBLAS_STATUS_ALLOC_FAILED"; - case CUBLAS_STATUS_INVALID_VALUE: - return "CUBLAS_STATUS_INVALID_VALUE"; - case CUBLAS_STATUS_ARCH_MISMATCH: - return "CUBLAS_STATUS_ARCH_MISMATCH"; - case CUBLAS_STATUS_MAPPING_ERROR: - return "CUBLAS_STATUS_MAPPING_ERROR"; - case CUBLAS_STATUS_EXECUTION_FAILED: - return "CUBLAS_STATUS_EXECUTION_FAILED"; - case CUBLAS_STATUS_INTERNAL_ERROR: - return "CUBLAS_STATUS_INTERNAL_ERROR"; -/* case CUBLAS_STATUS_NOT_SUPPORTED: - return "CUBLAS_STATUS_NOT_SUPPORTED"; - case CUBLAS_STATUS_LICENSE_ERROR: - return "CUBLAS_STATUS_LICENSE_ERROR"; */ - } - return "<unknown>"; -} - -#define PROFILE_START \ - do { \ - cudaEventRecord(profile_start, 0); -#define PROFILE_STOP \ - cudaEventRecord(profile_stop, 0); \ - cudaEventSynchronize(profile_stop); \ - float milliseconds = 0; \ - cudaEventElapsedTime(&milliseconds, profile_start, profile_stop); \ - accu_profile(__func__, milliseconds / 1000); \ - } while (0); - -#define PROFILE_END -#endif diff --git a/matrix/cukernel.cu b/matrix/cukernel.cu deleted file mode 100644 index a19030a..0000000 --- a/matrix/cukernel.cu +++ /dev/null @@ -1,17 +0,0 @@ -#define NERV_GENERIC_CUKERNEL - -#define cudak_(NAME) cudak_float_ ## NAME -#define MATRIX_USE_FLOAT -#include "generic/elem_type.h" -#include "generic/cukernel.cu" -#undef cudak_ -#undef MATRIX_USE_FLOAT -#undef MATRIX_ELEM -#undef MATRIX_ELEM_PTR -#undef MATRIX_ELEM_FMT -#undef MATRIX_ELEM_WRITE_FMT - -#define cudak_(NAME) cudak_double_ ## NAME -#define MATRIX_USE_DOUBLE -#include "generic/elem_type.h" -#include "generic/cukernel.cu" diff --git a/matrix/cukernel.h b/matrix/cukernel.h deleted file mode 100644 index 8a1494f..0000000 --- a/matrix/cukernel.h +++ /dev/null @@ -1,20 +0,0 @@ -#ifdef NERV_GENERIC_CUKERNEL -void cudak_(cuda_mul_elem)(const Matrix *a, const Matrix *b, Matrix *c); -void cudak_(cuda_log_elem)(const Matrix *a, Matrix *b); -void cudak_(cuda_sigmoid)(const Matrix *a, Matrix *b); -void cudak_(cuda_sigmoid_grad)(const Matrix *output, const Matrix *err, Matrix *nerr); -void cudak_(cuda_rowsum)(const Matrix *a, Matrix *b); -void cudak_(cuda_rowmax)(const Matrix *a, Matrix *b); -void cudak_(cuda_rowmax_idx)(const Matrix *a, Matrix *b, Matrix *idx); -void cudak_(cuda_colsum)(const Matrix *a, Matrix *b); -void cudak_(cuda_colsame)(const Matrix *a, const Matrix *ref, Matrix *b); -void cudak_(cuda_softmax_denominator)(const Matrix *a, const Matrix *max, Matrix *b); -void cudak_(cuda_softmax_final)(const Matrix *a, const Matrix *max, const Matrix *deno, Matrix *b); -void cudak_(cuda_add_row)(const Matrix *a, Matrix *b, double beta); -void cudak_(cuda_fill)(Matrix *a, double val); -void cudak_(cuda_expand_frm)(const Matrix *a, Matrix *b, int context); -void cudak_(cuda_rearrange_frm)(const Matrix *a, Matrix *b, int step); -void cudak_(cuda_scale_rows_by_row)(const Matrix *a, Matrix *b); -void cudak_(cuda_scale_rows_by_col)(const Matrix *a, Matrix *b); -void cudak_(cuda_decompress)(const Matrix *a, Matrix *b); -#endif diff --git a/matrix/cumatrix.c b/matrix/cumatrix.c deleted file mode 100644 index af34fb4..0000000 --- a/matrix/cumatrix.c +++ /dev/null @@ -1,87 +0,0 @@ -#define NERV_GENERIC_CUMATRIX -#include "../common.h" -#include "cuda_helper.h" -#include <string.h> -#define PROFILE_HASHMAP_SIZE 123457 -static cublasHandle_t cublas_handle; -static cudaEvent_t profile_start, profile_stop; -static HashMap *profile; - -static int print_profile(lua_State *L) { - (void)L; - size_t i; - fprintf(stderr, "*** [nerv cumatrix profile] **\n"); - for (i = 0; i < profile->size; i++) - { - HashNode *ptr; - for (ptr = profile->bucket[i]; ptr; ptr = ptr->next) - { - fprintf(stderr, "%s:\t%.6f\n", ptr->key, *(float *)ptr->val); - } - } - return 0; -} - -static int clear_profile(lua_State *L) { - (void)L; - hashmap_clear(profile); - return 0; -} - -void accu_profile(const char *name, float delta) { - float *val = hashmap_getval(profile, name); - if (!val) - { - val = malloc(sizeof(float)); - *val = 0; - hashmap_setval(profile, name, val); - } - *val += delta; -} - -static const luaL_Reg cumatrix_methods[] = { - {"print_profile", print_profile}, - {"clear_profile", clear_profile}, - {NULL, NULL} -}; - -extern void nerv_matrix_cuda_float_init(lua_State *L); -extern void nerv_matrix_cuda_double_init(lua_State *L); - -void nerv_cumatrix_init(lua_State *L) { - luaL_register(L, NULL, cumatrix_methods); - cublasCreate(&cublas_handle); - cudaEventCreate(&profile_start); - cudaEventCreate(&profile_stop); - profile = hashmap_create(PROFILE_HASHMAP_SIZE, bkdr_hash, strcmp); - nerv_matrix_cuda_float_init(L); - nerv_matrix_cuda_double_init(L); -} - -#define MATRIX_USE_FLOAT -#define cuda_matrix_(NAME) cuda_matrix_float_##NAME -#define nerv_matrix_(NAME) nerv_matrix_cuda_float_##NAME -#define cudak_(NAME) cudak_float_ ## NAME -#define NERV_CUBLAS_(NAME) cublasS##NAME -#define MATRIX_CUMATRIX_HOST_TNAME nerv_matrix_host_float_tname -const char *nerv_matrix_(tname) = "nerv.CuMatrixFloat"; -#include "generic/cumatrix.c" -#undef NERV_CUBLAS_ -#undef cudak_ -#undef nerv_matrix_ -#undef cuda_matrix_ -#undef MATRIX_USE_FLOAT -#undef MATRIX_ELEM -#undef MATRIX_ELEM_PTR -#undef MATRIX_ELEM_FMT -#undef MATRIX_ELEM_WRITE_FMT -#undef MATRIX_CUMATRIX_HOST_TNAME - -#define MATRIX_USE_DOUBLE -#define cuda_matrix_(NAME) cuda_matrix_double_##NAME -#define nerv_matrix_(NAME) nerv_matrix_cuda_double_##NAME -#define cudak_(NAME) cudak_double_ ## NAME -#define NERV_CUBLAS_(NAME) cublasD##NAME -#define MATRIX_CUMATRIX_HOST_TNAME nerv_matrix_host_double_tname -const char *nerv_matrix_(tname) = "nerv.CuMatrixDouble"; -#include "generic/cumatrix.c" diff --git a/matrix/generic/cukernel.cu b/matrix/generic/cukernel.cu deleted file mode 100644 index d6c8adc..0000000 --- a/matrix/generic/cukernel.cu +++ /dev/null @@ -1,571 +0,0 @@ -#ifdef NERV_GENERIC_CUKERNEL -#include <assert.h> -#include <stdio.h> -#include "matrix.h" -#include "cuda.h" -#include "float.h" -#define CUDA_THREADS_N 16 -#define CUDA_THREADS_NN ((CUDA_THREADS_N) * (CUDA_THREADS_N)) -#define CEIL_DIV(a, b) (((a) + (b) - 1) / (b)) -__global__ void cudak_(log_elem)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, int stride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - long idx; - MATRIX_ELEM tmp; - if (i >= nrow || j >= ncol) return; - idx = j + i * stride; - tmp = a[idx]; - if(tmp < FLT_MIN) tmp = FLT_MIN; - b[idx] = log(tmp); -} - -__global__ void cudak_(mul_elem)(const MATRIX_ELEM *a, const MATRIX_ELEM *b, - MATRIX_ELEM *c, - int nrow, int ncol, int stride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - long idx; - if (i >= nrow || j >= ncol) return; - idx = j + i * stride; - c[idx] = a[idx] * b[idx]; -} - -__global__ void cudak_(sigmoid)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, int stride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - long idx; - if (i >= nrow || j >= ncol) return; - idx = j + i * stride; - b[idx] = 1.0 / (1.0 + exp(-a[idx])); -} - -__global__ void cudak_(sigmoid_grad)(const MATRIX_ELEM *output, - const MATRIX_ELEM *err, - MATRIX_ELEM *nerr, - int nrow, int ncol, int stride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - long idx; - if (i >= nrow || j >= ncol) return; - idx = j + i * stride; - nerr[idx] = output[idx] * (1.0 - output[idx]) * err[idx]; -} - -__global__ void cudak_(softmax_final)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - const MATRIX_ELEM *max, const MATRIX_ELEM *deno, - int nrow, int ncol, int stride, int mstride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - long idx; - if (i >= nrow || j >= ncol) return; - idx = j + i * stride; - b[idx] = exp(a[idx] - max[0 + i * mstride]) / deno[0 + i * mstride]; -} - -__global__ void cudak_(block_reduce_rowsum)(const MATRIX_ELEM *input, - MATRIX_ELEM *output, - const int istride, const int ostride, - const int n) { - extern __shared__ MATRIX_ELEM cudak_(arr)[]; - int j = blockIdx.x * blockDim.x + threadIdx.x; - cudak_(arr)[threadIdx.x] = j < n ? input[j + istride * blockIdx.y] : 0; - __syncthreads(); - for (int offset = blockDim.x >> 1; offset; offset >>= 1) - { - if (threadIdx.x < offset) - cudak_(arr)[threadIdx.x] += cudak_(arr)[threadIdx.x + offset]; - __syncthreads(); - } - if (threadIdx.x == 0) - output[blockIdx.x + ostride * blockIdx.y] = cudak_(arr)[0]; -} - -__global__ void cudak_(block_reduce_colsum)(const MATRIX_ELEM *input, - MATRIX_ELEM *output, - const int istride, const int ostride, - const int n) { - extern __shared__ MATRIX_ELEM cudak_(arr)[]; - int i = blockIdx.y * blockDim.y + threadIdx.y; - cudak_(arr)[threadIdx.y] = i < n ? input[blockIdx.x + istride * i] : 0; - __syncthreads(); - for (int offset = blockDim.y >> 1; offset; offset >>= 1) - { - if (threadIdx.y < offset) - cudak_(arr)[threadIdx.y] += cudak_(arr)[threadIdx.y + offset]; - __syncthreads(); - } - if (threadIdx.y == 0) - output[blockIdx.x + ostride * blockIdx.y] = cudak_(arr)[0]; -} - -__global__ void cudak_(block_reduce_colsame)(const MATRIX_ELEM *input, - const MATRIX_ELEM *ref_input, - MATRIX_ELEM *output, - const int istride, const int ostride, - const int n) { - extern __shared__ MATRIX_ELEM cudak_(arr)[]; - int i = blockIdx.y * blockDim.y + threadIdx.y; - cudak_(arr)[threadIdx.y] = (i < n && input[blockIdx.x + istride * i] == \ - ref_input[blockIdx.x + istride * i]) ? 1.0 : 0; - __syncthreads(); - for (int offset = blockDim.y >> 1; offset; offset >>= 1) - { - if (threadIdx.y < offset) - cudak_(arr)[threadIdx.y] += cudak_(arr)[threadIdx.y + offset]; - __syncthreads(); - } - if (threadIdx.y == 0) - output[blockIdx.x + ostride * blockIdx.y] = cudak_(arr)[0]; -} - -__global__ void cudak_(block_reduce_softmax_rowsum)(const MATRIX_ELEM *input, - MATRIX_ELEM *output, - const MATRIX_ELEM *max, - const int istride, const int ostride, - const int mstride, const int n) { - extern __shared__ MATRIX_ELEM cudak_(arr)[]; - int j = blockIdx.x * blockDim.x + threadIdx.x; - cudak_(arr)[threadIdx.x] = j < n ? exp(input[j + istride * blockIdx.y] - \ - max[0 + mstride * blockIdx.y]) : 0; - __syncthreads(); - for (int offset = blockDim.x >> 1; offset; offset >>= 1) - { - if (threadIdx.x < offset) - cudak_(arr)[threadIdx.x] += cudak_(arr)[threadIdx.x + offset]; - __syncthreads(); - } - if (threadIdx.x == 0) - output[blockIdx.x + ostride * blockIdx.y] = cudak_(arr)[0]; -} - -__global__ void cudak_(block_reduce_rowmax)(const MATRIX_ELEM *input, - MATRIX_ELEM *output, - const int istride, const int ostride, - const int n) { - extern __shared__ MATRIX_ELEM cudak_(arr)[]; - int j = blockIdx.x * blockDim.x + threadIdx.x; - cudak_(arr)[threadIdx.x] = j < n ? input[j + istride * blockIdx.y] : -FLT_MAX; - __syncthreads(); - for (int offset = blockDim.x >> 1; offset; offset >>= 1) - { - if (threadIdx.x < offset) - { - MATRIX_ELEM l = cudak_(arr)[threadIdx.x], - r = cudak_(arr)[threadIdx.x + offset]; - if (r > l) - cudak_(arr)[threadIdx.x] = r; - } - __syncthreads(); - } - if (threadIdx.x == 0) - output[blockIdx.x + ostride * blockIdx.y] = cudak_(arr)[0]; -} - -__global__ void cudak_(block_reduce_rowmax_idx)(const MATRIX_ELEM *input, - const MATRIX_ELEM *idx_input, - MATRIX_ELEM *output, - MATRIX_ELEM *idx_output, - const int istride, const int ostride, - const int n) { - extern __shared__ MATRIX_ELEM cudak_(arr)[]; - MATRIX_ELEM *arr_val = cudak_(arr); - MATRIX_ELEM *arr_idx = arr_val + blockDim.x; - int j = blockIdx.x * blockDim.x + threadIdx.x; - arr_val[threadIdx.x] = j < n ? input[j + istride * blockIdx.y] : -FLT_MAX; - arr_idx[threadIdx.x] = j < n ? idx_input[j + istride * blockIdx.y] : 0; - __syncthreads(); - for (int offset = blockDim.x >> 1; offset; offset >>= 1) - { - if (threadIdx.x < offset) - { - MATRIX_ELEM l = arr_val[threadIdx.x], - r = arr_val[threadIdx.x + offset]; - if (r > l) - { - arr_val[threadIdx.x] = r; - arr_idx[threadIdx.x] = arr_idx[threadIdx.x + offset]; - } - } - __syncthreads(); - } - if (threadIdx.x == 0) - { - output[blockIdx.x + ostride * blockIdx.y] = arr_val[0]; - idx_output[blockIdx.x + ostride * blockIdx.y] = arr_idx[0]; - } -} - -__global__ void cudak_(add_row)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, int stride, double beta) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - b[j + i * stride] += beta * a[j]; -} - -__global__ void cudak_(fill)(MATRIX_ELEM *a, - int nrow, int ncol, int stride, double val) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - a[j + i * stride] = val; -} - -__global__ void cudak_(expand_frm)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, - int enrow, int encol, - int stride, int estride, - int context) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - int ridx; - if (i >= enrow || j >= encol) return; - ridx = i + j / ncol - context; - if (ridx < 0) ridx = 0; - else if (ridx >= nrow) ridx = nrow - 1; - b[j + i * estride] = a[j % ncol + ridx * stride]; -} - -__global__ void cudak_(rearrange_frm)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, - int stride, int step, int orig_dim) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - b[j + i * stride] = a[j / step + (j % step) * orig_dim + i * stride]; -} - -__global__ void cudak_(scale_rows_by_col)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, - int astride, int bstride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - b[j + i * bstride] *= a[i * astride]; -} - -__global__ void cudak_(scale_rows_by_row)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, - int stride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - b[j + i * stride] *= a[j]; -} - -__global__ void cudak_(decompress)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, - int stride_a, int stride_b) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - b[lrintf(a[j + i * stride_a]) + i * stride_b] = 1.0; -} - -__global__ void cudak_(gen_col_idx)(MATRIX_ELEM *b, - int nrow, int ncol, int stride) { - int j = blockIdx.x * blockDim.x + threadIdx.x; - int i = blockIdx.y * blockDim.y + threadIdx.y; - if (i >= nrow || j >= ncol) return; - b[j + i * stride] = j; -} - -extern "C" { -#include "../cukernel.h" - void cudak_(cuda_log_elem)(const Matrix *a, Matrix *b) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(log_elem)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_mul_elem)(const Matrix *a, const Matrix *b, - Matrix *c) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(mul_elem)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - MATRIX_ELEM_PTR(c), - b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_sigmoid)(const Matrix *a, Matrix *b) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(sigmoid)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), b->nrow, b->ncol, - b->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_sigmoid_grad)(const Matrix *output, - const Matrix *err, Matrix *nerr) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(nerr->ncol, threadsPerBlock.x), - CEIL_DIV(nerr->nrow, threadsPerBlock.y)); - cudak_(sigmoid_grad)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(output), MATRIX_ELEM_PTR(err), - MATRIX_ELEM_PTR(nerr), - nerr->nrow, nerr->ncol, - nerr->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_rowsum)(const Matrix *a, Matrix *b) { - dim3 block(CUDA_THREADS_NN, 1); - int ncol = a->ncol; - int blocks_per_row = CEIL_DIV(ncol, block.x); - dim3 grid(blocks_per_row, a->nrow); - MATRIX_ELEM *res; - size_t stride; - cudaMallocPitch(&res, &stride, blocks_per_row * sizeof(MATRIX_ELEM), a->nrow); - cudak_(block_reduce_rowsum)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ - (MATRIX_ELEM_PTR(a), res, - a->stride / sizeof(MATRIX_ELEM), stride / sizeof(MATRIX_ELEM), - ncol); - ncol = blocks_per_row; - assert((unsigned long)ncol <= block.x); - grid.x = 1; - cudaStreamSynchronize(0); - cudak_(block_reduce_rowsum)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ - (res, MATRIX_ELEM_PTR(b), - stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), - ncol); - cudaStreamSynchronize(0); - cudaFree(res); - } - - void cudak_(cuda_colsame)(const Matrix *a, const Matrix *ref, Matrix *b) { - dim3 block(1, CUDA_THREADS_NN); - int nrow = a->nrow; - int blocks_per_col = CEIL_DIV(nrow, block.y); - dim3 grid(a->ncol, blocks_per_col); - MATRIX_ELEM *res; - size_t stride; - cudaMallocPitch(&res, &stride, a->ncol * sizeof(MATRIX_ELEM), blocks_per_col); - cudak_(block_reduce_colsame)<<<grid, block, block.y * sizeof(MATRIX_ELEM)>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(ref), res, - a->stride / sizeof(MATRIX_ELEM), stride / sizeof(MATRIX_ELEM), - nrow); - nrow = blocks_per_col; - assert((unsigned long)nrow <= block.y); - grid.y = 1; - cudaStreamSynchronize(0); - cudak_(block_reduce_colsum)<<<grid, block, block.y * sizeof(MATRIX_ELEM)>>> \ - (res, MATRIX_ELEM_PTR(b), - stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), - nrow); - cudaStreamSynchronize(0); - cudaFree(res); - } - - void cudak_(cuda_colsum)(const Matrix *a, Matrix *b) { - dim3 block(1, CUDA_THREADS_NN); - int nrow = a->nrow; - int blocks_per_col = CEIL_DIV(nrow, block.y); - dim3 grid(a->ncol, blocks_per_col); - MATRIX_ELEM *res; - size_t stride; - cudaMallocPitch(&res, &stride, a->ncol * sizeof(MATRIX_ELEM), blocks_per_col); - cudak_(block_reduce_colsum)<<<grid, block, block.y * sizeof(MATRIX_ELEM)>>> \ - (MATRIX_ELEM_PTR(a), res, - a->stride / sizeof(MATRIX_ELEM), stride / sizeof(MATRIX_ELEM), - nrow); - nrow = blocks_per_col; - assert((unsigned long)nrow <= block.y); - grid.y = 1; - cudaStreamSynchronize(0); - cudak_(block_reduce_colsum)<<<grid, block, block.y * sizeof(MATRIX_ELEM)>>> \ - (res, MATRIX_ELEM_PTR(b), - stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), - nrow); - cudaStreamSynchronize(0); - cudaFree(res); - } - - void cudak_(cuda_softmax_final)(const Matrix *a, const Matrix *max, - const Matrix *deno, Matrix *b) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(softmax_final)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - MATRIX_ELEM_PTR(max), MATRIX_ELEM_PTR(deno), - b->nrow, b->ncol, - b->stride / sizeof(MATRIX_ELEM), - max->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_softmax_denominator)(const Matrix *a, const Matrix *max, Matrix *b) { - dim3 block(CUDA_THREADS_NN, 1); - int ncol = a->ncol; - int blocks_per_row = CEIL_DIV(ncol, block.x); - dim3 grid(blocks_per_row, a->nrow); - MATRIX_ELEM *res; - size_t stride; - assert(max->ncol == 1); - cudaMallocPitch(&res, &stride, blocks_per_row * sizeof(MATRIX_ELEM), a->nrow); - cudak_(block_reduce_softmax_rowsum) \ - <<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ - (MATRIX_ELEM_PTR(a), res, MATRIX_ELEM_PTR(max), - a->stride / sizeof(MATRIX_ELEM), stride / sizeof(MATRIX_ELEM), - max->stride / sizeof(MATRIX_ELEM), - ncol); - ncol = blocks_per_row; - assert((unsigned long)ncol <= block.x); - grid.x = 1; - cudaStreamSynchronize(0); - cudak_(block_reduce_rowsum) \ - <<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ - (res, MATRIX_ELEM_PTR(b), - stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), - ncol); - cudaStreamSynchronize(0); - cudaFree(res); - } - - void cudak_(cuda_rowmax)(const Matrix *a, Matrix *b) { - dim3 block(CUDA_THREADS_NN, 1); - int ncol = a->ncol; - int blocks_per_row = CEIL_DIV(ncol, block.x); - dim3 grid(blocks_per_row, a->nrow); - MATRIX_ELEM *res; - size_t stride; - cudaMallocPitch(&res, &stride, blocks_per_row * sizeof(MATRIX_ELEM), a->nrow); - cudak_(block_reduce_rowmax)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ - (MATRIX_ELEM_PTR(a), res, - a->stride / sizeof(MATRIX_ELEM), stride / sizeof(MATRIX_ELEM), - ncol); - ncol = blocks_per_row; - assert((unsigned long)ncol <= block.x); - grid.x = 1; - cudaStreamSynchronize(0); - cudak_(block_reduce_rowmax)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ - (res, MATRIX_ELEM_PTR(b), - stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), - ncol); - cudaStreamSynchronize(0); - cudaFree(res); - } - - void cudak_(cuda_rowmax_idx)(const Matrix *a, Matrix *b, Matrix *b_idx) { - dim3 block(CUDA_THREADS_NN, 1); - int ncol = a->ncol; - int blocks_per_row = CEIL_DIV(ncol, block.x); - dim3 grid(blocks_per_row, a->nrow); - MATRIX_ELEM *a_idx, *res, *res_idx; - size_t stride; - cudaMallocPitch(&a_idx, &stride, a->stride, a->nrow); - cudak_(gen_col_idx)<<<grid, block>>>(a_idx, a->nrow, ncol, stride / sizeof(MATRIX_ELEM)); - cudaMallocPitch(&res, &stride, blocks_per_row * sizeof(MATRIX_ELEM), a->nrow); - cudaMallocPitch(&res_idx, &stride, blocks_per_row * sizeof(MATRIX_ELEM), a->nrow); - cudaStreamSynchronize(0); - cudak_(block_reduce_rowmax_idx)<<<grid, block, - 2 * block.x * sizeof(MATRIX_ELEM)>>> \ - (MATRIX_ELEM_PTR(a), a_idx, res, res_idx, - a->stride / sizeof(MATRIX_ELEM), stride / sizeof(MATRIX_ELEM), - ncol); - ncol = blocks_per_row; - assert((unsigned long)ncol <= block.x); - grid.x = 1; - cudaStreamSynchronize(0); - cudak_(block_reduce_rowmax_idx)<<<grid, block, - 2 * block.x * sizeof(MATRIX_ELEM)>>> \ - (res, res_idx, MATRIX_ELEM_PTR(b), MATRIX_ELEM_PTR(b_idx), - stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), - ncol); - cudaStreamSynchronize(0); - cudaFree(a_idx); - cudaFree(res); - cudaFree(res_idx); - } - - /* in-place calc */ - void cudak_(cuda_add_row)(const Matrix *a, Matrix *b, double beta) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(add_row)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), b->nrow, b->ncol, - b->stride / sizeof(MATRIX_ELEM), beta); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_fill)(Matrix *a, double val) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(a->ncol, threadsPerBlock.x), - CEIL_DIV(a->nrow, threadsPerBlock.y)); - cudak_(fill)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), a->nrow, a->ncol, - a->stride / sizeof(MATRIX_ELEM), val); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_expand_frm)(const Matrix *a, Matrix *b, int context) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(expand_frm)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - a->nrow, a->ncol, - b->nrow, b->ncol, - a->stride / sizeof(MATRIX_ELEM), - b->stride / sizeof(MATRIX_ELEM), - context); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_rearrange_frm)(const Matrix *a, Matrix *b, int step) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(rearrange_frm)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM), - step, b->ncol / step); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_scale_rows_by_col)(const Matrix *a, Matrix *b) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(scale_rows_by_col)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - b->nrow, b->ncol, - a->stride / sizeof(MATRIX_ELEM), - b->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_scale_rows_by_row)(const Matrix *a, Matrix *b) { - dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); - dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), - CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(scale_rows_by_row)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } - - void cudak_(cuda_decompress)(const Matrix *a, Matrix *b) { - dim3 threadsPerBlock(1, CUDA_THREADS_NN); - dim3 numBlocks(1, CEIL_DIV(a->nrow, threadsPerBlock.y)); - cudak_(decompress)<<<numBlocks, threadsPerBlock>>> \ - (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), - a->nrow, a->ncol, - a->stride / sizeof(MATRIX_ELEM), - b->stride / sizeof(MATRIX_ELEM)); - cudaStreamSynchronize(0); - } -} -#endif diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c deleted file mode 100644 index b5d1a35..0000000 --- a/matrix/generic/cumatrix.c +++ /dev/null @@ -1,493 +0,0 @@ -#ifdef NERV_GENERIC_CUMATRIX -#include "matrix.h" -#include "elem_type.h" - -#define MATRIX_DATA_FREE(L, ptr) cuda_matrix_(free)(L, ptr) -#define MATRIX_DATA_ALLOC(L, dptr, stride, width, height) \ - cuda_matrix_(alloc)(L, dptr, stride, width, height) -#define MATRIX_DATA_WRITE(L, data, idx, val) cuda_matrix_(write)(L, data, idx, val) -#define MATRIX_DATA_READ(L, data, idx) cuda_matrix_(read)(L, data, idx) -#define MATRIX_INIT(L) cuda_matrix_(init)(L) -#define MATRIX_BASE_TNAME nerv_matrix_cuda_tname -#define NERV_GENERIC_MATRIX -#define NERV_GENERIC_CUKERNEL -#include "../../common.h" -#include "../cukernel.h" -#include "../cuda_helper.h" - -Matrix *nerv_matrix_(new_)(lua_State *L, long nrow, long ncol); -void nerv_matrix_(data_free)(lua_State *L, Matrix *self); - -static void nerv_matrix_(add_)(lua_State *L, const Matrix *a, const Matrix *b, - const Matrix *c, - MATRIX_ELEM alpha, MATRIX_ELEM beta) { - PROFILE_START - CUBLAS_SAFE_SYNC_CALL( - NERV_CUBLAS_(geam)(cublas_ha |