#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