From 5e407d74130accfbbf94d2cabcb03fc126a89410 Mon Sep 17 00:00:00 2001
From: Determinant <ted.sybil@gmail.com>
Date: Wed, 24 Jun 2015 22:48:24 +0800
Subject: separate non-Lua part of matrix code to a dedicated dir

---
 nerv/lib/matrix/generic/cukernel.cu | 571 ++++++++++++++++++++++++++++++++++++
 1 file changed, 571 insertions(+)
 create mode 100644 nerv/lib/matrix/generic/cukernel.cu

(limited to 'nerv/lib/matrix/generic/cukernel.cu')

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
-- 
cgit v1.2.3