major change: use luarocks to manage project

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);