diff options
Diffstat (limited to 'matrix/generic')
-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 |
6 files changed, 0 insertions, 1382 deletions
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 |