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-rw-r--r--nerv/lib/matrix/generic/cukernel.cu571
1 files changed, 571 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
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