diff options
Diffstat (limited to 'nerv/lib/matrix/generic')
-rw-r--r-- | nerv/lib/matrix/generic/cukernel.cu | 571 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/cumatrix.c | 403 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/cumatrix.h | 50 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/elem_type.h | 22 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/matrix.c | 57 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/matrix.h | 4 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/mmatrix.c | 82 | ||||
-rw-r--r-- | nerv/lib/matrix/generic/mmatrix.h | 7 |
8 files changed, 1196 insertions, 0 deletions
diff --git a/nerv/lib/matrix/generic/cukernel.cu b/nerv/lib/matrix/generic/cukernel.cu new file mode 100644 index 0000000..6111193 --- /dev/null +++ b/nerv/lib/matrix/generic/cukernel.cu @@ -0,0 +1,571 @@ +#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/nerv/lib/matrix/generic/cumatrix.c b/nerv/lib/matrix/generic/cumatrix.c new file mode 100644 index 0000000..11aacec --- /dev/null +++ b/nerv/lib/matrix/generic/cumatrix.c @@ -0,0 +1,403 @@ +#ifdef NERV_GENERIC_CUMATRIX +#include "matrix.h" +#include "elem_type.h" +#define MATRIX_DATA_FREE(ptr, status) cuda_matrix_(free)(ptr, status) +#define MATRIX_DATA_ALLOC(dptr, stride, width, height, status) \ + cuda_matrix_(alloc)(dptr, stride, width, height, status) + +#define NERV_GENERIC_MATRIX +#define NERV_GENERIC_CUKERNEL +#include "../../../common.h" +#include "../cukernel.h" +#include "../cuda_helper.h" + +void nerv_matrix_(add)(Matrix *c, const Matrix *a, const Matrix *b, + MATRIX_ELEM alpha, MATRIX_ELEM beta, + Status *status) { + CHECK_SAME_DIMENSION(a, b, status); + CHECK_SAME_DIMENSION(a, c, status); + 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)), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(mul)(Matrix *c, const Matrix *a, const Matrix *b, + MATRIX_ELEM alpha, MATRIX_ELEM beta, + int ta, int tb, Status *status) { +#define SWAP(a, b) \ + do { int t = (a); (a) = (b); (b) = t; } while (0) + + 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_EXIT_STATUS(status, MAT_WRONG_MULT_DIM, 0); + /* 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)), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(sigmoid)(Matrix *a, const Matrix *b, Status *status) { + CHECK_SAME_DIMENSION(a, b, status); + PROFILE_START + cudak_(cuda_sigmoid)(b, a); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(sigmoid_grad)(Matrix *nerr, const Matrix *err, + const Matrix *output, Status *status) { + CHECK_SAME_DIMENSION(nerr, err, status); + CHECK_SAME_DIMENSION(nerr, output, status); + PROFILE_START + cudak_(cuda_sigmoid_grad)(output, err, nerr); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +Matrix *nerv_matrix_(softmax)(Matrix *b, const Matrix *a, Status *status) { + Matrix *max, *max_idx; + Matrix *dno; + CHECK_SAME_DIMENSION_RET(a, b, status); + max = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + return NULL; + max_idx = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + { + nerv_matrix_(destroy)(max, status); + return NULL; + } + dno = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + { /* FIXME: destroy may also fail? */ + nerv_matrix_(destroy)(max, status); + nerv_matrix_(destroy)(max_idx, status); + return NULL; + } + 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_(destroy)(max, status); + nerv_matrix_(destroy)(dno, status); + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return max_idx; +} + +Matrix *nerv_matrix_(rowsum)(Matrix *a, Status *status) { + Matrix *b = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + return NULL; + PROFILE_START + cudak_(cuda_rowsum)(a, b); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return b; +} + +Matrix *nerv_matrix_(colsum)(Matrix *a, Status *status) { + Matrix *b = nerv_matrix_(create)(1, a->ncol, status); + if (status->err_code != MAT_NORMAL) + return NULL; + PROFILE_START + cudak_(cuda_colsum)(a, b); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return b; +} + +Matrix *nerv_matrix_(colsame)(Matrix *a, const Matrix *ref, + Status *status) { + Matrix *b = nerv_matrix_(create)(1, a->ncol, status); + if (status->err_code != MAT_NORMAL) + return NULL; + CHECK_SAME_DIMENSION_RET(a, ref, status); + PROFILE_START + cudak_(cuda_colsame)(a, ref, b); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return b; +} + +Matrix *nerv_matrix_(rowmax)(Matrix *a, Status *status) { + Matrix *b = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + return NULL; + PROFILE_START + cudak_(cuda_rowmax)(a, b); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return b; +} + +void nerv_matrix_(rowmax_idx)(Matrix *a, Matrix **b, Matrix **idx, + Status *status) { + *b = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + return; + *idx = nerv_matrix_(create)(a->nrow, 1, status); + if (status->err_code != MAT_NORMAL) + { + /* FIXME: destroy may also fail? */ + nerv_matrix_(destroy)(*b, status); + return; + } + PROFILE_START + cudak_(cuda_rowmax_idx)(a, *b, *idx); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(add_row)(Matrix *b, const Matrix *a, double beta, + Status *status) { + if (a->ncol != b->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + if (a->nrow != 1) + NERV_EXIT_STATUS(status, MAT_ROW_VECTOR_EXP, 0); + PROFILE_START + cudak_(cuda_add_row)(a, b, beta); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(fill)(Matrix *self, double val, Status *status) { + PROFILE_START + cudak_(cuda_fill)(self, val); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(copy_fromd)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status) { + if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow && + a_begin + b_end - b_begin <= a->nrow)) + NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0); + if (a->ncol != b->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + 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), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(copy_fromh)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status) { + if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow && + a_begin + b_end - b_begin <= a->nrow)) + NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0); + if (a->ncol != b->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + 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), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(copy_toh)(Matrix *a, const Matrix *b, + int a_begin, int a_end, int b_begin, + Status *status) { + if (!(0 <= a_begin && a_begin < a_end && a_end <= a->nrow && + b_begin + a_end - a_begin <= b->nrow)) + NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0); + if (b->ncol != a->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + 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), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +Matrix *nerv_matrix_(trans)(Matrix *a, Status *status) { + MATRIX_ELEM alpha = 1, beta = 0; + Matrix *b = nerv_matrix_(create)(a->ncol, a->nrow, status); + if (status->err_code != MAT_NORMAL) + return NULL; + /* FIXME: possible memory leak when lua error is raised */ + PROFILE_START + CUBLAS_SAFE_SYNC_CALL_RET( + 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)), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return b; +} + +void nerv_matrix_(mul_elem)(Matrix *c, const Matrix *a, const Matrix *b, + Status *status) { + CHECK_SAME_DIMENSION(a, b, status); + CHECK_SAME_DIMENSION(a, c, status); + PROFILE_START + cudak_(cuda_mul_elem)(a, b, c); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(log_elem)(Matrix *b, const Matrix *a, Status *status) { + CHECK_SAME_DIMENSION(a, b, status); + PROFILE_START + cudak_(cuda_log_elem)(a, b); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +Matrix *nerv_matrix_(decompress)(const Matrix *a, int orig_col, Status *status) { + Matrix *b; + if (a->ncol != 1) + { + NERV_SET_STATUS(status, MAT_COL_VECTOR_EXP, 0); + return NULL; + } + b = nerv_matrix_(create)(a->nrow, orig_col, status); + if (status->err_code != MAT_NORMAL) + return NULL; + PROFILE_START + cudak_(cuda_fill)(b, 0.0); + cudak_(cuda_decompress)(a, b); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return b; +} + +void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b, + const Matrix *idx, int b_begin, Status *status) { + long nrow = a->nrow; + if (!(0 <= b_begin && b_begin + nrow <= idx->ncol)) + NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0); + long *idx_ptr = idx->data.i; + int i; + if (idx->nrow != 1) + NERV_EXIT_STATUS(status, MAT_IDX_VECTOR_EXP, 0); + if (a->ncol != b->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + 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_EXIT_STATUS(status, MAT_INVALID_IDX, 0); + CUDA_SAFE_CALL(cudaStreamCreate(streams + i), status); + CUDA_SAFE_CALL(cudaMemcpyAsync(MATRIX_ROW_PTR(a, i), + MATRIX_ROW_PTR(b, src_row), + b->stride, + cudaMemcpyHostToDevice, streams[i]), status); + } + for (i = 0; i < nrow; i++) + { + CUDA_SAFE_CALL(cudaStreamSynchronize(streams[i]), status); + CUDA_SAFE_CALL(cudaStreamDestroy(streams[i]), status); + } + free(streams); + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(expand_frm)(Matrix *a, const Matrix *b, + int context, Status *status) { + if (a->nrow != b->nrow) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + if (a->ncol != b->ncol * (context * 2 + 1)) + NERV_EXIT_STATUS(status, MAT_GENERAL_ERR, + "the width should be 2 * context + 1"); + PROFILE_START + cudak_(cuda_expand_frm)(b, a, context); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(rearrange_frm)(Matrix *a, const Matrix *b, + int step, Status *status) { + CHECK_SAME_DIMENSION(a, b, status); + if (b->ncol % step) + NERV_EXIT_STATUS(status, MAT_GENERAL_ERR, + "the dimension of columns is not divisible by step"); + PROFILE_START + cudak_(cuda_rearrange_frm)(b, a, step); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(scale_rows_by_col)(Matrix *a, const Matrix *b, + Status *status) { + if (a->nrow != b->nrow) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + if (b->ncol != 1) + NERV_EXIT_STATUS(status, MAT_COL_VECTOR_EXP, 0); + PROFILE_START + cudak_(cuda_scale_rows_by_col)(b, a); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(scale_rows_by_row)(Matrix *a, const Matrix *b, + Status *status) { + if (a->ncol != b->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + if (b->nrow != 1) + NERV_EXIT_STATUS(status, MAT_ROW_VECTOR_EXP, 0); + PROFILE_START + cudak_(cuda_scale_rows_by_row)(b, a); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +static void cuda_matrix_(free)(MATRIX_ELEM *ptr, Status *status) { + CUDA_SAFE_SYNC_CALL(cudaFree(ptr), status); + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +static void cuda_matrix_(alloc)(MATRIX_ELEM **dptr, + size_t *stride, long width, long height, + Status *status) { + PROFILE_START + CUDA_SAFE_SYNC_CALL(cudaMallocPitch((void **)dptr, stride, width, height), + status); + PROFILE_STOP + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +#include "matrix.c" +#endif diff --git a/nerv/lib/matrix/generic/cumatrix.h b/nerv/lib/matrix/generic/cumatrix.h new file mode 100644 index 0000000..9a4f87e --- /dev/null +++ b/nerv/lib/matrix/generic/cumatrix.h @@ -0,0 +1,50 @@ +#include "../../../common.h" + +void nerv_matrix_(add)(Matrix *c, const Matrix *a, const Matrix *b, + MATRIX_ELEM alpha, MATRIX_ELEM beta, + Status *status); +void nerv_matrix_(mul)(Matrix *c, const Matrix *a, const Matrix *b, + MATRIX_ELEM alpha, MATRIX_ELEM beta, + int ta, int tb, Status *status); +void nerv_matrix_(sigmoid)(Matrix *a, const Matrix *b, Status *status); +void nerv_matrix_(sigmoid_grad)(Matrix *nerr, const Matrix *err, + const Matrix *output, Status *status); + +Matrix *nerv_matrix_(softmax)(Matrix *b, const Matrix *a, Status *status); +Matrix *nerv_matrix_(rowsum)(Matrix *a, Status *status); +Matrix *nerv_matrix_(colsum)(Matrix *a, Status *status); +Matrix *nerv_matrix_(colsame)(Matrix *a, const Matrix *ref, + Status *status); +Matrix *nerv_matrix_(rowmax)(Matrix *a, Status *status); +void nerv_matrix_(rowmax_idx)(Matrix *a, Matrix **b, Matrix **idx, + Status *status); +void nerv_matrix_(add_row)(Matrix *b, const Matrix *a, double beta, + Status *status); +void nerv_matrix_(fill)(Matrix *self, double val, Status *status); +void nerv_matrix_(copy_fromd)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status); +void nerv_matrix_(copy_fromh)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status); +void nerv_matrix_(copy_toh)(Matrix *a, const Matrix *b, + int a_begin, int a_end, int b_begin, + Status *status); +Matrix *nerv_matrix_(trans)(Matrix *a, Status *status); +void nerv_matrix_(mul_elem)(Matrix *c, const Matrix *a, const Matrix *b, + Status *status); + +void nerv_matrix_(log_elem)(Matrix *b, const Matrix *a, Status *status); + +Matrix *nerv_matrix_(decompress)(const Matrix *a, int orig_col, Status *status); +void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b, + const Matrix *idx, int b_begin, Status *status); + +void nerv_matrix_(expand_frm)(Matrix *a, const Matrix *b, + int context, Status *status); +void nerv_matrix_(rearrange_frm)(Matrix *a, const Matrix *b, + int step, Status *status); +void nerv_matrix_(scale_rows_by_col)(Matrix *a, const Matrix *b, + Status *status); +void nerv_matrix_(scale_rows_by_row)(Matrix *a, const Matrix *b, + Status *status); diff --git a/nerv/lib/matrix/generic/elem_type.h b/nerv/lib/matrix/generic/elem_type.h new file mode 100644 index 0000000..bffe940 --- /dev/null +++ b/nerv/lib/matrix/generic/elem_type.h @@ -0,0 +1,22 @@ +#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/nerv/lib/matrix/generic/matrix.c b/nerv/lib/matrix/generic/matrix.c new file mode 100644 index 0000000..91577e1 --- /dev/null +++ b/nerv/lib/matrix/generic/matrix.c @@ -0,0 +1,57 @@ +#ifdef NERV_GENERIC_MATRIX +#include "../../../common.h" +#include "matrix.h" +/* FIXME: malloc failure detection */ + +static void nerv_matrix_(data_free)(Matrix *self, Status *status) { + assert(*self->data_ref > 0); + if (--(*self->data_ref) == 0) + { + /* free matrix data */ + MATRIX_DATA_FREE(MATRIX_ELEM_PTR(self), status); + free(self->data_ref); + free(self); + } + else NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +static void nerv_matrix_(data_retain)(Matrix *self) { + (*self->data_ref)++; +} + +Matrix *nerv_matrix_(create)(long nrow, long ncol, Status *status) { + Matrix *self = (Matrix *)malloc(sizeof(Matrix)); + self->nrow = nrow; + self->ncol = ncol; + self->nmax = self->nrow * self->ncol; + MATRIX_DATA_ALLOC(&MATRIX_ELEM_PTR(self), &self->stride, + sizeof(MATRIX_ELEM) * self->ncol, self->nrow, + status); + if (status->err_code != MAT_NORMAL) + { + free(self); + return NULL; + } + self->data_ref = (long *)malloc(sizeof(long)); + *self->data_ref = 0; + nerv_matrix_(data_retain)(self); + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return self; +} + +void nerv_matrix_(destroy)(Matrix *self, Status *status) { + nerv_matrix_(data_free)(self, status); +} + +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; +} +#endif diff --git a/nerv/lib/matrix/generic/matrix.h b/nerv/lib/matrix/generic/matrix.h new file mode 100644 index 0000000..9d44e6d --- /dev/null +++ b/nerv/lib/matrix/generic/matrix.h @@ -0,0 +1,4 @@ +#include "../matrix.h" +Matrix *nerv_matrix_(create)(long nrow, long ncol, Status *status); +void nerv_matrix_(destroy)(Matrix *self, Status *status); +Matrix *nerv_matrix_(getrow)(Matrix *self, int row); diff --git a/nerv/lib/matrix/generic/mmatrix.c b/nerv/lib/matrix/generic/mmatrix.c new file mode 100644 index 0000000..e3d1f93 --- /dev/null +++ b/nerv/lib/matrix/generic/mmatrix.c @@ -0,0 +1,82 @@ +#ifdef NERV_GENERIC_MMATRIX +#include "matrix.h" +#include "elem_type.h" +#define MATRIX_DATA_FREE(ptr, status) host_matrix_(free)(ptr, status) +#define MATRIX_DATA_ALLOC(dptr, stride, width, height, status) \ + host_matrix_(alloc)(dptr, stride, width, height, status) +#define NERV_GENERIC_MATRIX +#include "../../../common.h" +#include "../../io/chunk_file.h" +#include "string.h" + +static void host_matrix_(free)(MATRIX_ELEM *ptr, Status *status) { + free(ptr); + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +static void host_matrix_(alloc)(MATRIX_ELEM **dptr, size_t *stride, + long width, long height, Status *status) { + if ((*dptr = (MATRIX_ELEM *)malloc(width * height)) == NULL) + NERV_EXIT_STATUS(status, MAT_INSUF_MEM, 0); + *stride = width; + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +#include "matrix.c" +Matrix *nerv_matrix_(load)(ChunkData *cdp, Status *status) { + int i, j; + long nrow, ncol; + FILE *fp = cdp->fp; + Matrix *self; + if (fscanf(fp, "%ld %ld", &nrow, &ncol) != 2) + NERV_EXIT_STATUS(status, MAT_INVALID_FORMAT, 0); + self = nerv_matrix_(create)(nrow, ncol, status); + if (status->err_code != MAT_NORMAL) + return NULL; + 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); + NERV_EXIT_STATUS(status, MAT_INVALID_FORMAT, 0); + } + } + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return self; +} + +void nerv_matrix_(save)(Matrix *self, ChunkFile *cfp, Status *status) { + int i, j; + long nrow = self->nrow, ncol = self->ncol; + FILE *fp = cfp->fp; + if (fprintf(fp, "%ld %ld\n", nrow, ncol) < 0) + NERV_EXIT_STATUS(status, MAT_WRITE_ERROR, 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) + NERV_EXIT_STATUS(status, MAT_WRITE_ERROR, 0); + if (fprintf(fp, "\n") < 0) + NERV_EXIT_STATUS(status, MAT_WRITE_ERROR, 0); + } + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +void nerv_matrix_(copy_from)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status) { + if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow && + a_begin + b_end - b_begin <= a->nrow)) + NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0); + if (a->ncol != b->ncol) + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); + memmove(MATRIX_ROW_PTR(a, a_begin), + MATRIX_ROW_PTR(b, b_begin), + sizeof(MATRIX_ELEM) * b->ncol * (b_end - b_begin)); + NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +#endif diff --git a/nerv/lib/matrix/generic/mmatrix.h b/nerv/lib/matrix/generic/mmatrix.h new file mode 100644 index 0000000..5336e7a --- /dev/null +++ b/nerv/lib/matrix/generic/mmatrix.h @@ -0,0 +1,7 @@ +#include "../../../common.h" + +Matrix *nerv_matrix_(load)(ChunkData *cdp, Status *status); +void nerv_matrix_(save)(Matrix *self, ChunkFile *cfp, Status *status); +void nerv_matrix_(copy_from)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status); |