diff options
author | Determinant <[email protected]> | 2015-06-22 19:01:29 +0800 |
---|---|---|
committer | Determinant <[email protected]> | 2015-06-22 19:01:29 +0800 |
commit | 2497fd9e7a0fae5ee4887890d7a312e0e08a93b8 (patch) | |
tree | 382f97575bd2df9ee6abb1662b11b279fc22d72b /matrix | |
parent | 196e9b48a3541caccdffc5743001cced70667091 (diff) |
major change: use luarocks to manage project
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_handle, CUBLAS_OP_N, CUBLAS_OP_N, - a->ncol, a->nrow, - &alpha, - MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM), - &beta, - MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM), - MATRIX_ELEM_PTR(c), c->stride / sizeof(MATRIX_ELEM))); - PROFILE_STOP -} - -static int nerv_matrix_(add)(lua_State *L) { - Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); - MATRIX_ELEM alpha = luaL_checknumber(L, 4); - MATRIX_ELEM beta = luaL_checknumber(L, 5); - CHECK_SAME_DIMENSION(a, b); - CHECK_SAME_DIMENSION(a, c); - nerv_matrix_(add_)(L, a, b, c, alpha, beta); - return 0; -} - -static int nerv_matrix_(get_cublas_op)(char ch) { - return (ch == 'T' || ch == 't') ? CUBLAS_OP_T : CUBLAS_OP_N; -} - -static int nerv_matrix_(mul)(lua_State *L) { -#define SWAP(a, b) \ - do { int t = (a); (a) = (b); (b) = t; } while (0) - - Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); - MATRIX_ELEM alpha = luaL_checknumber(L, 4); - MATRIX_ELEM beta = luaL_checknumber(L, 5); - int nargs = lua_gettop(L); - int ta = nargs > 5 ? nerv_matrix_(get_cublas_op)(*luaL_checkstring(L, 6)) \ - : CUBLAS_OP_N; - int tb = nargs > 6 ? nerv_matrix_(get_cublas_op)(*luaL_checkstring(L, 7)) \ - : CUBLAS_OP_N; - int am = a->nrow, an = a->ncol; - int bm = b->nrow, bn = b->ncol; - if (ta == CUBLAS_OP_T) SWAP(am, an); - if (tb == CUBLAS_OP_T) SWAP(bm, bn); - if (an != bm) - nerv_error(L, "Wrong dimension of multipliers"); -/* MATRIX_ELEM alpha = 1.0f, beta = 0.0f; */ - /* Because matrix in Nerv is row-major, here b comes first */ - PROFILE_START - CUBLAS_SAFE_SYNC_CALL( - NERV_CUBLAS_(gemm)(cublas_handle, tb, ta, - bn, am, bm, - &alpha, - MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM), - MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM), - &beta, - MATRIX_ELEM_PTR(c), c->stride / sizeof(MATRIX_ELEM))); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(create)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, a->nrow, a->ncol); - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(sigmoid)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - CHECK_SAME_DIMENSION(a, b); - PROFILE_START - cudak_(cuda_sigmoid)(b, a); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(sigmoid_grad)(lua_State *L) { - Matrix *nerr = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *err = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *output = luaT_checkudata(L, 3, nerv_matrix_(tname)); - CHECK_SAME_DIMENSION(nerr, err); - CHECK_SAME_DIMENSION(nerr, output); - PROFILE_START - cudak_(cuda_sigmoid_grad)(output, err, nerr); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(softmax)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *max, *max_idx; - Matrix *dno; - CHECK_SAME_DIMENSION(a, b); - max = nerv_matrix_(new_)(L, a->nrow, 1); - max_idx = nerv_matrix_(new_)(L, a->nrow, 1); - dno = nerv_matrix_(new_)(L, a->nrow, 1); - PROFILE_START - cudak_(cuda_rowmax_idx)(a, max, max_idx); - cudak_(cuda_softmax_denominator)(a, max, dno); - cudak_(cuda_softmax_final)(a, max, dno, b); - PROFILE_STOP - nerv_matrix_(data_free)(L, max); - nerv_matrix_(data_free)(L, dno); - luaT_pushudata(L, max_idx, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(rowsum)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, a->nrow, 1); - PROFILE_START - cudak_(cuda_rowsum)(a, b); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(colsum)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, 1, a->ncol); - PROFILE_START - cudak_(cuda_colsum)(a, b); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(colsame)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *ref = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, 1, a->ncol); - CHECK_SAME_DIMENSION(a, ref); - PROFILE_START - cudak_(cuda_colsame)(a, ref, b); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(rowmax)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, a->nrow, 1); - PROFILE_START - cudak_(cuda_rowmax)(a, b); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(rowmax_idx)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, a->nrow, 1); - Matrix *idx = nerv_matrix_(new_)(L, a->nrow, 1); - PROFILE_START - cudak_(cuda_rowmax_idx)(a, b, idx); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - luaT_pushudata(L, idx, nerv_matrix_(tname)); - return 2; -} - -static int nerv_matrix_(add_row)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname)); - double beta = luaL_checknumber(L, 3); - if (a->ncol != b->ncol) - nerv_error(L, "the number of columns is not the same"); - if (a->nrow != 1) - nerv_error(L, "a row vector is expected"); - PROFILE_START - cudak_(cuda_add_row)(a, b, beta); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(fill)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - double val = luaL_checknumber(L, 2); - PROFILE_START - cudak_(cuda_fill)(self, val); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(copy_fromd)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - int nargs = lua_gettop(L); - int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; - int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow; - int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; - if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow && - a_begin + b_end - b_begin <= a->nrow)) - nerv_error(L, "invalid copy interval"); - if (a->ncol != b->ncol) - nerv_error(L, "matrices should be of the same dimension"); - PROFILE_START - CUDA_SAFE_SYNC_CALL( - cudaMemcpy2D(MATRIX_ROW_PTR(a, a_begin), a->stride, - MATRIX_ROW_PTR(b, b_begin), b->stride, - sizeof(MATRIX_ELEM) * b->ncol, b_end - b_begin, - cudaMemcpyDeviceToDevice)); - PROFILE_STOP - return 0; -} - -extern const char *MATRIX_CUMATRIX_HOST_TNAME; -static int nerv_matrix_(copy_fromh)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); - int nargs = lua_gettop(L); - int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; - int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow; - int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; - if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow && - a_begin + b_end - b_begin <= a->nrow)) - nerv_error(L, "invalid copy interval"); - if (a->ncol != b->ncol) - nerv_error(L, "matrices should be of the same dimension"); - PROFILE_START - CUDA_SAFE_SYNC_CALL( - cudaMemcpy2D(MATRIX_ROW_PTR(a, a_begin), a->stride, - MATRIX_ROW_PTR(b, b_begin), b->stride, - sizeof(MATRIX_ELEM) * b->ncol, b_end - b_begin, - cudaMemcpyHostToDevice)); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(copy_toh)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); - int nargs = lua_gettop(L); - int a_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; - int a_end = nargs > 3 ? luaL_checkinteger(L, 4) : a->nrow; - int b_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; - if (!(0 <= a_begin && a_begin < a_end && a_end <= a->nrow && - b_begin + a_end - a_begin <= b->nrow)) - nerv_error(L, "invalid copy interval"); - if (b->ncol != a->ncol) - nerv_error(L, "matrices should be of the same dimension"); - PROFILE_START - CUDA_SAFE_SYNC_CALL( - cudaMemcpy2D(MATRIX_ROW_PTR(b, b_begin), b->stride, - MATRIX_ROW_PTR(a, a_begin), a->stride, - sizeof(MATRIX_ELEM) * a->ncol, a_end - a_begin, - cudaMemcpyDeviceToHost)); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(trans)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = nerv_matrix_(new_)(L, a->ncol, a->nrow); - MATRIX_ELEM alpha = 1, beta = 0; - /* FIXME: possible memory leak when lua error is raised */ - PROFILE_START - CUBLAS_SAFE_SYNC_CALL( - NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_T, CUBLAS_OP_T, - a->nrow, a->ncol, - &alpha, - MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM), - &beta, - MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM), - MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM))); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -static int nerv_matrix_(mul_elem)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); - Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); - CHECK_SAME_DIMENSION(a, b); - CHECK_SAME_DIMENSION(a, c); - PROFILE_START - cudak_(cuda_mul_elem)(a, b, c); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(log_elem)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname)); - CHECK_SAME_DIMENSION(a, b); - PROFILE_START - cudak_(cuda_log_elem)(a, b); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(decompress)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b; - int orig_col = luaL_checkinteger(L, 2); - if (a->ncol != 1) - nerv_error(L, "the compressed matrix must be a column vector"); - b = nerv_matrix_(new_)(L, a->nrow, orig_col); - PROFILE_START - cudak_(cuda_fill)(b, 0.0); - cudak_(cuda_decompress)(a, b); - PROFILE_STOP - luaT_pushudata(L, b, nerv_matrix_(tname)); - return 1; -} - -extern const char *nerv_matrix_host_int_tname; -static int nerv_matrix_(copy_rows_fromh_by_idx)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); - Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_host_int_tname); - long nrow = a->nrow; - int b_begin = lua_gettop(L) > 3 ? luaL_checkinteger(L, 4) : 0; - if (!(0 <= b_begin && b_begin + nrow <= idx->ncol)) - nerv_error(L, "invalid copy interval"); - long *idx_ptr = idx->data.i; - int i; - if (idx->nrow != 1) - nerv_error(L, "index should be a vector"); - if (a->ncol != b->ncol) - nerv_error(L, "source/destination dimension mismatch"); - cudaStream_t *streams = (cudaStream_t*)malloc(sizeof(cudaStream_t) * nrow); - for (i = 0; i < nrow; i++) - { - int src_row = idx_ptr[b_begin + i]; - if (!(0 <= src_row && src_row < b->nrow)) - nerv_error(L, "invalid index"); - CUDA_SAFE_CALL(cudaStreamCreate(streams + i)); - CUDA_SAFE_CALL(cudaMemcpyAsync(MATRIX_ROW_PTR(a, i), - MATRIX_ROW_PTR(b, src_row), - b->stride, - cudaMemcpyHostToDevice, streams[i])); - } - for (i = 0; i < nrow; i++) - { - CUDA_SAFE_CALL(cudaStreamSynchronize(streams[i])); - CUDA_SAFE_CALL(cudaStreamDestroy(streams[i])); - } - free(streams); - return 0; -} - -static int nerv_matrix_(expand_frm)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - int context = luaL_checkinteger(L, 3); - if (a->nrow != b->nrow) - nerv_error(L, "mismatching number of frames"); - if (a->ncol != b->ncol * (context * 2 + 1)) - nerv_error(L, "the width should be 2 * context + 1"); - PROFILE_START - cudak_(cuda_expand_frm)(b, a, context); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(rearrange_frm)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - int step = luaL_checkinteger(L, 3); - CHECK_SAME_DIMENSION(a, b); - if (b->ncol % step) - nerv_error(L, "the dimension of columns is not divisible by step"); - PROFILE_START - cudak_(cuda_rearrange_frm)(b, a, step); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(scale_rows_by_col)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - if (a->nrow != b->nrow) - nerv_error(L, "the number of rows is not the same"); - if (b->ncol != 1) - nerv_error(L, "a column vector is expected"); - PROFILE_START - cudak_(cuda_scale_rows_by_col)(b, a); - PROFILE_STOP - return 0; -} - -static int nerv_matrix_(scale_rows_by_row)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - if (a->ncol != b->ncol) - nerv_error(L, "the number of columns is not the same"); - if (b->nrow != 1) - nerv_error(L, "a row vector is expected"); - PROFILE_START - cudak_(cuda_scale_rows_by_row)(b, a); - PROFILE_STOP - return 0; -} - -static const luaL_Reg nerv_matrix_(extra_methods)[] = { - {"create", nerv_matrix_(create)}, - {"colsum", nerv_matrix_(colsum)}, - {"colsame", nerv_matrix_(colsame)}, - {"rowsum", nerv_matrix_(rowsum)}, - {"rowmax", nerv_matrix_(rowmax)}, - {"rowmax_idx", nerv_matrix_(rowmax_idx)}, - {"trans", nerv_matrix_(trans)}, - {"decompress", nerv_matrix_(decompress)}, - /* in-place calc */ - {"copy_fromh", nerv_matrix_(copy_fromh)}, - {"copy_fromd", nerv_matrix_(copy_fromd)}, - {"copy_toh", nerv_matrix_(copy_toh)}, - {"add", nerv_matrix_(add)}, - {"mul", nerv_matrix_(mul)}, - {"add_row", nerv_matrix_(add_row)}, - {"fill", nerv_matrix_(fill)}, - {"sigmoid", nerv_matrix_(sigmoid)}, - {"sigmoid_grad", nerv_matrix_(sigmoid_grad)}, - {"softmax", nerv_matrix_(softmax)}, - {"mul_elem", nerv_matrix_(mul_elem)}, - {"log_elem", nerv_matrix_(log_elem)}, - {"copy_rows_fromh_by_idx", nerv_matrix_(copy_rows_fromh_by_idx)}, - {"expand_frm", nerv_matrix_(expand_frm)}, - {"rearrange_frm", nerv_matrix_(rearrange_frm)}, - {"scale_rows_by_row", nerv_matrix_(scale_rows_by_row)}, - {"scale_rows_by_col", nerv_matrix_(scale_rows_by_col)}, - {NULL, NULL} -}; - -static void cuda_matrix_(init)(lua_State *L) { - luaN_append_methods(L, nerv_matrix_(extra_methods)); -} - -static void cuda_matrix_(free)(lua_State *L, MATRIX_ELEM *ptr) { - CUDA_SAFE_SYNC_CALL(cudaFree(ptr)); -} - -static void cuda_matrix_(alloc)(lua_State *L, MATRIX_ELEM **dptr, - size_t *stride, long width, long height) { - PROFILE_START - CUDA_SAFE_SYNC_CALL(cudaMallocPitch((void **)dptr, stride, width, height)); - PROFILE_STOP -} - -static MATRIX_ELEM cuda_matrix_(read)(lua_State *L, MATRIX_ELEM *data, - int idx) { - MATRIX_ELEM res; - CUDA_SAFE_SYNC_CALL(cudaMemcpy(&res, data + idx, - sizeof(MATRIX_ELEM), cudaMemcpyDeviceToHost)); - return res; -} - -static void cuda_matrix_(write)(lua_State *L, MATRIX_ELEM *data, - int idx, MATRIX_ELEM val) { - CUDA_SAFE_SYNC_CALL(cudaMemcpy(data + idx, &val, - sizeof(MATRIX_ELEM), cudaMemcpyHostToDevice)); -} - -int nerv_matrix_(get_elem)(lua_State *L) { - return nerv_error_method_not_implemented(L); -} - -int nerv_matrix_(set_elem)(lua_State *L) { - return nerv_error_method_not_implemented(L); -} - -#include "matrix.c" -#endif diff --git a/matrix/generic/elem_type.h b/matrix/generic/elem_type.h deleted file mode 100644 index bffe940..0000000 --- a/matrix/generic/elem_type.h +++ /dev/null @@ -1,22 +0,0 @@ -#ifdef MATRIX_USE_FLOAT - -#define MATRIX_ELEM float -#define MATRIX_ELEM_FMT "%f" -#define MATRIX_ELEM_WRITE_FMT "%.8f" -#define MATRIX_ELEM_PTR(self) ((self)->data.f) - -#elif defined(MATRIX_USE_DOUBLE) - -#define MATRIX_ELEM double -#define MATRIX_ELEM_FMT "%lf" -#define MATRIX_ELEM_WRITE_FMT "%.8lf" -#define MATRIX_ELEM_PTR(self) ((self)->data.d) - -#elif defined(MATRIX_USE_INT) - -#define MATRIX_ELEM long -#define MATRIX_ELEM_FMT "%ld" -#define MATRIX_ELEM_WRITE_FMT "%ld" -#define MATRIX_ELEM_PTR(self) ((self)->data.i) - -#endif diff --git a/matrix/generic/matrix.c b/matrix/generic/matrix.c deleted file mode 100644 index e17fb42..0000000 --- a/matrix/generic/matrix.c +++ /dev/null @@ -1,155 +0,0 @@ -#ifdef NERV_GENERIC_MATRIX -#include "../../common.h" -#include "matrix.h" - -extern const char *nerv_matrix_(tname); -extern const char *MATRIX_BASE_TNAME; - -void nerv_matrix_(data_free)(lua_State *L, Matrix *self) { - (void)L; - assert(*self->data_ref > 0); - if (--(*self->data_ref) == 0) - { - /* free matrix data */ - MATRIX_DATA_FREE(L, MATRIX_ELEM_PTR(self)); - free(self->data_ref); - free(self); - } -} - -void nerv_matrix_(data_retain)(Matrix *self) { - (*self->data_ref)++; -} - -Matrix *nerv_matrix_(new_)(lua_State *L, long nrow, long ncol) { - Matrix *self = (Matrix *)malloc(sizeof(Matrix)); - self->nrow = nrow; - self->ncol = ncol; - self->nmax = self->nrow * self->ncol; - MATRIX_DATA_ALLOC(L, &MATRIX_ELEM_PTR(self), &self->stride, - sizeof(MATRIX_ELEM) * self->ncol, self->nrow); - self->data_ref = (long *)malloc(sizeof(long)); - *self->data_ref = 0; - nerv_matrix_(data_retain)(self); - return self; -} - -int nerv_matrix_(new)(lua_State *L) { - luaT_pushudata(L, nerv_matrix_(new_)(L, luaL_checkinteger(L, 1), - luaL_checkinteger(L, 2)), - nerv_matrix_(tname)); - return 1; -} - -int nerv_matrix_(destroy)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - nerv_matrix_(data_free)(L, self); - return 1; -} - -int nerv_matrix_(get_elem)(lua_State *L); -int nerv_matrix_(set_elem)(lua_State *L); - -static Matrix *nerv_matrix_(getrow)(Matrix *self, int row) { - Matrix *prow = (Matrix *)malloc(sizeof(Matrix)); - prow->ncol = self->ncol; - prow->nrow = 1; - prow->stride = self->stride; - prow->nmax = prow->ncol; - MATRIX_ELEM_PTR(prow) = MATRIX_ROW_PTR(self, row); - prow->data_ref = self->data_ref; - nerv_matrix_(data_retain)(prow); - return prow; -} - -static int nerv_matrix_(newindex)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - if (lua_isnumber(L, 2)) - { - int idx = luaL_checkinteger(L, 2); - if (self->nrow == 1) - { - if (idx < 0 || idx >= self->ncol) - nerv_error(L, "index must be within range [0, %d)", self->ncol); - MATRIX_DATA_WRITE(L, MATRIX_ELEM_PTR(self), idx, - luaL_checknumber(L, 3)); - } - else - nerv_error(L, "cannot assign to row vector"); - lua_pushboolean(L, 1); - return 1; - } - else - { - lua_pushboolean(L, 0); - return 1; - } -} - - -static int nerv_matrix_(index)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - if (lua_isnumber(L, 2)) - { - int idx = luaL_checkinteger(L, 2); - if (self->nrow == 1) - { - if (idx < 0 || idx >= self->ncol) - nerv_error(L, "index must be within range [0, %d)", self->ncol); - lua_pushnumber(L, MATRIX_DATA_READ(L, MATRIX_ELEM_PTR(self), idx)); - } - else - { - if (idx < 0 || idx >= self->nrow) - nerv_error(L, "index must be within range [0, %d)", self->nrow); - luaT_pushudata(L, nerv_matrix_(getrow)(self, idx), nerv_matrix_(tname)); - } - lua_pushboolean(L, 1); - return 2; - } - else - { - lua_pushboolean(L, 0); - return 1; - } -} - -static int nerv_matrix_(ncol)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - lua_pushinteger(L, self->ncol); - return 1; -} - -static int nerv_matrix_(nrow)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - lua_pushinteger(L, self->nrow); - return 1; -} - -static int nerv_matrix_(get_dataref_value)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - lua_pushinteger(L, *(self->data_ref)); - return 1; -} - -static const luaL_Reg nerv_matrix_(methods)[] = { - {"get_elem", nerv_matrix_(get_elem)}, - {"set_elem", nerv_matrix_(set_elem)}, - {"ncol", nerv_matrix_(ncol)}, - {"nrow", nerv_matrix_(nrow)}, - {"get_dataref_value", nerv_matrix_(get_dataref_value)}, - {"__index__", nerv_matrix_(index)}, - {"__newindex__", nerv_matrix_(newindex)}, - {NULL, NULL} -}; - -void nerv_matrix_(init)(lua_State *L) { - luaT_newmetatable(L, nerv_matrix_(tname), MATRIX_BASE_TNAME, - nerv_matrix_(new), nerv_matrix_(destroy), NULL); - luaL_register(L, NULL, nerv_matrix_(methods)); -#ifdef MATRIX_INIT - MATRIX_INIT(L); -#endif - lua_pop(L, 1); -} -#endif diff --git a/matrix/generic/matrix.h b/matrix/generic/matrix.h deleted file mode 100644 index 833724b..0000000 --- a/matrix/generic/matrix.h +++ /dev/null @@ -1,19 +0,0 @@ -#ifndef NERV_GENERIC_MATRIX_H -#define NERV_GENERIC_MATRIX_H - -#include <stddef.h> -typedef struct Matrix { - size_t stride; /* size of a row */ - long ncol, nrow, nmax; /* dimension of the matrix */ - union { - float *f; - double *d; - long *i; - } data; /* pointer to actual storage */ - long *data_ref; -} Matrix; - -#define MATRIX_ROW_PTR(self, row) \ - (MATRIX_ELEM *)((char *)MATRIX_ELEM_PTR(self) + (row) * (self)->stride) - -#endif diff --git a/matrix/generic/mmatrix.c b/matrix/generic/mmatrix.c deleted file mode 100644 index b0f0791..0000000 --- a/matrix/generic/mmatrix.c +++ /dev/null @@ -1,122 +0,0 @@ -#ifdef NERV_GENERIC_MMATRIX -#include "matrix.h" -#include "elem_type.h" -#define MATRIX_DATA_FREE(L, ptr) free(ptr) -#define MATRIX_DATA_ALLOC(L, dptr, stride, width, height) \ - host_matrix_(alloc)(L, dptr, stride, width, height) -#define MATRIX_DATA_WRITE(L, data, idx, val) (data[idx] = val) -#define MATRIX_DATA_READ(L, data, idx) (data[idx]) -#define MATRIX_INIT(L) host_matrix_(init)(L) -#define MATRIX_BASE_TNAME nerv_matrix_host_tname -#define NERV_GENERIC_MATRIX -#include "../../common.h" -#include "../../io/chunk_file.h" -#include "string.h" - -static void host_matrix_(alloc)(lua_State *L, - MATRIX_ELEM **dptr, size_t *stride, - long width, long height) { - if ((*dptr = (MATRIX_ELEM *)malloc(width * height)) == NULL) - nerv_error(L, "mmatrix insufficient memory"); - *stride = width; -} - -int nerv_matrix_(get_elem)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - int idx = luaL_checkinteger(L, 2); - if (idx < 0 || idx >= self->nmax) - nerv_error(L, "index must be within range [0, %d)", self->nmax); - lua_pushnumber(L, MATRIX_ELEM_PTR(self)[idx]); - return 1; -} - -int nerv_matrix_(set_elem)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - int idx = luaL_checkinteger(L, 2); - MATRIX_ELEM v = luaL_checknumber(L, 3); - if (idx < 0 || idx >= self->nmax) - nerv_error(L, "index must be within range [0, %d)", self->nmax); - MATRIX_ELEM_PTR(self)[idx] = v; - return 0; -} - -static const luaL_Reg nerv_matrix_(extra_methods)[]; -static void host_matrix_(init)(lua_State *L) { - luaN_append_methods(L, nerv_matrix_(extra_methods)); -#ifdef MMATRIX_INIT - MMATRIX_INIT(L); -#endif -} - -#include "matrix.c" - -int nerv_matrix_(load)(lua_State *L) { - ChunkData *chunk = luaT_checkudata(L, 1, nerv_chunk_data_tname); - Matrix *self; - int i, j; - long nrow, ncol; - FILE *fp = chunk->fp; - if (fscanf(fp, "%ld %ld", &nrow, &ncol) != 2) - return 0; - self = nerv_matrix_(new_)(L, nrow, ncol); - for (i = 0; i < nrow; i++) - { - MATRIX_ELEM *row = MATRIX_ROW_PTR(self, i); - for (j = 0; j < ncol; j++) - if (fscanf(fp, MATRIX_ELEM_FMT, row + j) != 1) - { - free(self); - return 0; - } - } - luaT_pushudata(L, self, nerv_matrix_(tname)); - return 1; -} - -int nerv_matrix_(save)(lua_State *L) { - ChunkFileHandle *chunk = luaT_checkudata(L, 2, - nerv_chunk_file_handle_tname); - Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); - int i, j; - long nrow = self->nrow, ncol = self->ncol; - FILE *fp = chunk->fp; - if (fprintf(fp, "%ld %ld\n", nrow, ncol) < 0) - return 0; - for (i = 0; i < nrow; i++) - { - MATRIX_ELEM *row = MATRIX_ROW_PTR(self, i); - for (j = 0; j < ncol; j++) - if (fprintf(fp, MATRIX_ELEM_WRITE_FMT " ", row[j]) < 0) - return 0; - if (fprintf(fp, "\n") < 0) - return 0; - } - return 0; -} - -static int nerv_matrix_(copy_from)(lua_State *L) { - Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); - Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); - int nargs = lua_gettop(L); - int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; - int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow; - int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; - if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow && - a_begin + b_end - b_begin <= a->nrow)) - nerv_error(L, "invalid copy interval"); - if (a->ncol != b->ncol) - nerv_error(L, "matrices should be of the same dimension"); - memmove(MATRIX_ROW_PTR(a, a_begin), - MATRIX_ROW_PTR(b, b_begin), - sizeof(MATRIX_ELEM) * b->ncol * (b_end - b_begin)); - return 0; -} - -static const luaL_Reg nerv_matrix_(extra_methods)[] = { - {"load", nerv_matrix_(load)}, - {"save", nerv_matrix_(save)}, - {"copy_from", nerv_matrix_(copy_from)}, - {NULL, NULL} -}; - -#endif diff --git a/matrix/init.c b/matrix/init.c deleted file mode 100644 index c29d7e9..0000000 --- a/matrix/init.c +++ /dev/null @@ -1,35 +0,0 @@ -#include "../common.h" -#include "generic/matrix.h" - -const char *nerv_matrix_tname = "nerv.Matrix"; -const char *nerv_matrix_cuda_tname = "nerv.CuMatrix"; -const char *nerv_matrix_host_tname = "nerv.MMatrix"; - -void nerv_cumatrix_init(lua_State *L); -void nerv_mmatrix_init(lua_State *L); - -static const luaL_Reg matrix_methods[] = { - {"__tostring__", nerv_error_method_not_implemented }, - {"__add__", nerv_error_method_not_implemented }, - {"__sub__", nerv_error_method_not_implemented }, - {"__mul__", nerv_error_method_not_implemented }, - {NULL, NULL} -}; - -void nerv_matrix_init(lua_State *L) { - /* abstract base class: Matrix */ - luaT_newmetatable(L, nerv_matrix_tname, NULL, NULL, NULL, NULL); - luaL_register(L, NULL, matrix_methods); - lua_pop(L, 1); - - /* CuMatrix inherits from Matrix */ - luaT_newmetatable(L, nerv_matrix_cuda_tname, nerv_matrix_tname, - NULL, NULL, NULL); - nerv_cumatrix_init(L); - lua_pop(L, 1); - /* MMatrix inherits from Matrix */ - luaT_newmetatable(L, nerv_matrix_host_tname, nerv_matrix_tname, - NULL, NULL, NULL); - nerv_mmatrix_init(L); - lua_pop(L, 1); -} diff --git a/matrix/init.lua b/matrix/init.lua deleted file mode 100644 index 1a8925f..0000000 --- a/matrix/init.lua +++ /dev/null @@ -1,77 +0,0 @@ -function nerv.Matrix:__tostring__() - local ncol = self:ncol() - local nrow = self:nrow() - local strt = {} - local fmt - if self.fmt then - fmt = self.fmt - else - fmt = "%.8f " - end - if nrow == 1 then - for col = 0, ncol - 1 do - table.insert(strt, string.format(fmt, self[col])) - end - table.insert(strt, "\n") - else - for row = 0, nrow - 1 do - local rp = self[row] - for col = 0, ncol - 1 do - table.insert(strt, string.format(fmt, rp[col])) - end - table.insert(strt, "\n") - end - end - table.insert(strt, string.format( - "[%s %d x %d]", self.__typename, nrow, ncol)) - return table.concat(strt) -end - --- gen: a function takes take indices of the matrix and return the generated --- all entrys in the matrix will be assigned by calling gen(i, j) -function nerv.Matrix:generate(gen) - if (self:nrow() == 1) then - for j = 0, self:ncol() - 1 do - self[j] = gen(j) - end - else - for i = 0, self:nrow() - 1 do - local row = self[i] - for j = 0, self:ncol() - 1 do - row[j] = gen(i, j) - end - end - end -end - -nerv.MMatrixInt.fmt = "%d " - -function nerv.CuMatrix:__add__(b) - c = self:create() - c:add(self, b, 1.0, 1.0) - return c -end - -function nerv.CuMatrix:__sub__(b) - c = self:create() - c:add(self, b, 1.0, -1.0) - return c -end - -function nerv.CuMatrix:__mul__(b) - c = nerv.get_type(self.__typename)(self:nrow(), b:ncol()) - c:mul(self, b, 1.0, 0.0, 'N', 'N') - return c -end - -function nerv.CuMatrixFloat.new_from_host(mat) - local res = nerv.CuMatrixFloat(mat:nrow(), mat:ncol()) - res:copy_fromh(mat) - return res -end - -function nerv.CuMatrixFloat:new_to_host() - local res = nerv.MMatrixFloat(self:nrow(), self:ncol()) - self:copy_toh(res) - return res -end diff --git a/matrix/mmatrix.c b/matrix/mmatrix.c deleted file mode 100644 index d1d68b9..0000000 --- a/matrix/mmatrix.c +++ /dev/null @@ -1,77 +0,0 @@ -#define NERV_GENERIC_MMATRIX -#include <stdlib.h> -#include "../common.h" -void nerv_matrix_host_float_init(lua_State *L); -void nerv_matrix_host_double_init(lua_State *L); -void nerv_matrix_host_int_init(lua_State *L); - -void nerv_mmatrix_init(lua_State *L) { - srand(1); - nerv_matrix_host_float_init(L); - nerv_matrix_host_double_init(L); - nerv_matrix_host_int_init(L); -} - -#define MATRIX_USE_FLOAT -#define host_matrix_(NAME) host_matrix_float_##NAME -#define nerv_matrix_(NAME) nerv_matrix_host_float_##NAME -const char *nerv_matrix_(tname) = "nerv.MMatrixFloat"; -#include "generic/mmatrix.c" -#undef nerv_matrix_ -#undef host_matrix_ -#undef MATRIX_USE_FLOAT -#undef MATRIX_ELEM -#undef MATRIX_ELEM_PTR -#undef MATRIX_ELEM_FMT -#undef MATRIX_ELEM_WRITE_FMT - -#define NERV_GENERIC_MMATRIX -#define MATRIX_USE_DOUBLE -#define host_matrix_(NAME) host_matrix_double_##NAME -#define nerv_matrix_(NAME) nerv_matrix_host_double_##NAME -const char *nerv_matrix_(tname) = "nerv.MMatrixDouble"; -#include "generic/mmatrix.c" -#undef nerv_matrix_ -#undef host_matrix_ -#undef MATRIX_USE_DOUBLE -#undef MATRIX_ELEM -#undef MATRIX_ELEM_PTR -#undef MATRIX_ELEM_FMT -#undef MATRIX_ELEM_WRITE_FMT - -#define NERV_GENERIC_MMATRIX -#define MATRIX_USE_INT -#define host_matrix_(NAME) host_matrix_int_##NAME -#define nerv_matrix_(NAME) nerv_matrix_host_int_##NAME -const char *nerv_matrix_(tname) = "nerv.MMatrixInt"; -#define MMATRIX_INIT(L) host_matrix_(init_extra)(L) - -static const luaL_Reg nerv_matrix_(extra_methods_int)[]; -static void host_matrix_(init_extra)(lua_State *L) { - luaN_append_methods(L, nerv_matrix_(extra_methods_int)); -} - -#include "generic/mmatrix.c" - -static int nerv_matrix_(perm_gen)(lua_State *L) { - int i, ncol = luaL_checkinteger(L, 1); - Matrix *self = nerv_matrix_(new_)(L, 1, ncol); - long *prow = self->data.i; - for (i = 0; i < ncol; i++) - prow[i] = i; - for (i = ncol - 1; i >= 0; i--) - { - size_t j = rand() % (i + 1); - long tmp = prow[i]; - prow[i] = prow[j]; - prow[j] = tmp; - } - luaT_pushudata(L, self, nerv_matrix_(tname)); - return 1; -} - -static const luaL_Reg nerv_matrix_(extra_methods_int)[] = { - {"perm_gen", nerv_matrix_(perm_gen)}, - {NULL, NULL} -}; - |