aboutsummaryrefslogtreecommitdiff
path: root/nerv/matrix/generic/cumatrix.c
diff options
context:
space:
mode:
Diffstat (limited to 'nerv/matrix/generic/cumatrix.c')
-rw-r--r--nerv/matrix/generic/cumatrix.c479
1 files changed, 166 insertions, 313 deletions
diff --git a/nerv/matrix/generic/cumatrix.c b/nerv/matrix/generic/cumatrix.c
index b5d1a35..859718e 100644
--- a/nerv/matrix/generic/cumatrix.c
+++ b/nerv/matrix/generic/cumatrix.c
@@ -1,10 +1,6 @@
#ifdef NERV_GENERIC_CUMATRIX
-#include "matrix.h"
+#include "../../lib/matrix/generic/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)
@@ -12,443 +8,303 @@
#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
-}
+#include "../../lib/matrix/generic/cumatrix.h"
-static int nerv_matrix_(add)(lua_State *L) {
+static int nerv_matrix_(lua_add)(lua_State *L) {
+ Status status;
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));
+ const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ const 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);
+ nerv_matrix_(add)(c, a, b, alpha, beta, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(get_cublas_op)(char ch) {
+static int nerv_matrix_(lua_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)
-
+static int nerv_matrix_(lua_mul)(lua_State *L) {
+ Status status;
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)) \
+ int ta = nargs > 5 ? nerv_matrix_(lua_get_cublas_op)(*luaL_checkstring(L, 6)) \
: CUBLAS_OP_N;
- int tb = nargs > 6 ? nerv_matrix_(get_cublas_op)(*luaL_checkstring(L, 7)) \
+ int tb = nargs > 6 ? nerv_matrix_(lua_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
+ nerv_matrix_(mul)(c, a, b, alpha, beta, ta, tb, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(create)(lua_State *L) {
+static int nerv_matrix_(lua_create)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = nerv_matrix_(new_)(L, a->nrow, a->ncol);
+ Matrix *b = nerv_matrix_(create)(a->nrow, a->ncol, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(sigmoid)(lua_State *L) {
+static int nerv_matrix_(lua_sigmoid)(lua_State *L) {
+ Status status;
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
+ nerv_matrix_(sigmoid)(a, b, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(sigmoid_grad)(lua_State *L) {
+static int nerv_matrix_(lua_sigmoid_grad)(lua_State *L) {
+ Status status;
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
+ nerv_matrix_(sigmoid_grad)(nerr, err, output, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(softmax)(lua_State *L) {
+static int nerv_matrix_(lua_softmax)(lua_State *L) {
+ Status status;
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);
+ Matrix *max_idx = nerv_matrix_(softmax)(b, a, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, max_idx, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(rowsum)(lua_State *L) {
+static int nerv_matrix_(lua_rowsum)(lua_State *L) {
+ Status status;
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
+ Matrix *b = nerv_matrix_(rowsum)(a, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(colsum)(lua_State *L) {
+static int nerv_matrix_(lua_colsum)(lua_State *L) {
+ Status status;
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
+ Matrix *b = nerv_matrix_(colsum)(a, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(colsame)(lua_State *L) {
+static int nerv_matrix_(lua_colsame)(lua_State *L) {
+ Status status;
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
+ const Matrix *ref = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ Matrix *b = nerv_matrix_(colsame)(a, ref, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(rowmax)(lua_State *L) {
+static int nerv_matrix_(lua_rowmax)(lua_State *L) {
+ Status status;
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
+ Matrix *b = nerv_matrix_(rowmax)(a, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(rowmax_idx)(lua_State *L) {
+static int nerv_matrix_(lua_rowmax_idx)(lua_State *L) {
+ Status status;
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
+ Matrix *b;
+ Matrix *idx;
+ nerv_matrix_(rowmax_idx)(a, &b, &idx, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
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));
+static int nerv_matrix_(lua_add_row)(lua_State *L) {
+ Status status;
+ const 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
+ nerv_matrix_(add_row)(b, a, beta, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(fill)(lua_State *L) {
+static int nerv_matrix_(lua_fill)(lua_State *L) {
+ Status status;
Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname));
double val = luaL_checknumber(L, 2);
- PROFILE_START
- cudak_(cuda_fill)(self, val);
- PROFILE_STOP
+ nerv_matrix_(fill)(self, val, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(copy_fromd)(lua_State *L) {
+static int nerv_matrix_(lua_copy_fromd)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ const 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
+ nerv_matrix_(copy_fromd)(a, b, a_begin, b_begin, b_end, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
extern const char *MATRIX_CUMATRIX_HOST_TNAME;
-static int nerv_matrix_(copy_fromh)(lua_State *L) {
+static int nerv_matrix_(lua_copy_fromh)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
+ const 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
+ nerv_matrix_(copy_fromh)(a, b, a_begin, b_begin, b_end, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(copy_toh)(lua_State *L) {
+static int nerv_matrix_(lua_copy_toh)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
+ const Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
int nargs = lua_gettop(L);
int a_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0;
int a_end = nargs > 3 ? luaL_checkinteger(L, 4) : a->nrow;
int b_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0;
- if (!(0 <= a_begin && a_begin < a_end && a_end <= a->nrow &&
- b_begin + a_end - a_begin <= b->nrow))
- nerv_error(L, "invalid copy interval");
- if (b->ncol != a->ncol)
- nerv_error(L, "matrices should be of the same dimension");
- 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));
- PROFILE_STOP
+ nerv_matrix_(copy_toh)(a, b, a_begin, a_end, b_begin, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(trans)(lua_State *L) {
+static int nerv_matrix_(lua_trans)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = nerv_matrix_(new_)(L, a->ncol, a->nrow);
- MATRIX_ELEM alpha = 1, beta = 0;
- /* FIXME: possible memory leak when lua error is raised */
- PROFILE_START
- CUBLAS_SAFE_SYNC_CALL(
- 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)));
- PROFILE_STOP
+ Matrix *b = nerv_matrix_(trans)(a, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
-static int nerv_matrix_(mul_elem)(lua_State *L) {
- Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname));
+static int nerv_matrix_(lua_mul_elem)(lua_State *L) {
+ Status status;
+ const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ const Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname));
Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname));
- CHECK_SAME_DIMENSION(a, b);
- CHECK_SAME_DIMENSION(a, c);
- PROFILE_START
- cudak_(cuda_mul_elem)(a, b, c);
- PROFILE_STOP
+ nerv_matrix_(mul_elem)(c, a, b, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(log_elem)(lua_State *L) {
- Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
+static int nerv_matrix_(lua_log_elem)(lua_State *L) {
+ Status status;
+ const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname));
- CHECK_SAME_DIMENSION(a, b);
- PROFILE_START
- cudak_(cuda_log_elem)(a, b);
- PROFILE_STOP
+ nerv_matrix_(log_elem)(b, a, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(decompress)(lua_State *L) {
- Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b;
+static int nerv_matrix_(lua_decompress)(lua_State *L) {
+ Status status;
+ const Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
int orig_col = luaL_checkinteger(L, 2);
- if (a->ncol != 1)
- nerv_error(L, "the compressed matrix must be a column vector");
- b = nerv_matrix_(new_)(L, a->nrow, orig_col);
- PROFILE_START
- cudak_(cuda_fill)(b, 0.0);
- cudak_(cuda_decompress)(a, b);
- PROFILE_STOP
+ Matrix *b = nerv_matrix_(decompress)(a, orig_col, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
extern const char *nerv_matrix_host_int_tname;
-static int nerv_matrix_(copy_rows_fromh_by_idx)(lua_State *L) {
+static int nerv_matrix_(lua_copy_rows_fromh_by_idx)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
- Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_host_int_tname);
+ const Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
+ const Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_host_int_tname);
long nrow = a->nrow;
int b_begin = lua_gettop(L) > 3 ? luaL_checkinteger(L, 4) : 0;
- if (!(0 <= b_begin && b_begin + nrow <= idx->ncol))
- nerv_error(L, "invalid copy interval");
- long *idx_ptr = idx->data.i;
- int i;
- if (idx->nrow != 1)
- nerv_error(L, "index should be a vector");
- if (a->ncol != b->ncol)
- nerv_error(L, "source/destination dimension mismatch");
- 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_error(L, "invalid index");
- CUDA_SAFE_CALL(cudaStreamCreate(streams + i));
- CUDA_SAFE_CALL(cudaMemcpyAsync(MATRIX_ROW_PTR(a, i),
- MATRIX_ROW_PTR(b, src_row),
- b->stride,
- cudaMemcpyHostToDevice, streams[i]));
- }
- for (i = 0; i < nrow; i++)
- {
- CUDA_SAFE_CALL(cudaStreamSynchronize(streams[i]));
- CUDA_SAFE_CALL(cudaStreamDestroy(streams[i]));
- }
- free(streams);
+ nerv_matrix_(copy_rows_fromh_by_idx)(a, b, idx, b_begin, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(expand_frm)(lua_State *L) {
+static int nerv_matrix_(lua_expand_frm)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
int context = luaL_checkinteger(L, 3);
- if (a->nrow != b->nrow)
- nerv_error(L, "mismatching number of frames");
- if (a->ncol != b->ncol * (context * 2 + 1))
- nerv_error(L, "the width should be 2 * context + 1");
- PROFILE_START
- cudak_(cuda_expand_frm)(b, a, context);
- PROFILE_STOP
+ nerv_matrix_(expand_frm)(a, b, context, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(rearrange_frm)(lua_State *L) {
+static int nerv_matrix_(lua_rearrange_frm)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
int step = luaL_checkinteger(L, 3);
- CHECK_SAME_DIMENSION(a, b);
- if (b->ncol % step)
- nerv_error(L, "the dimension of columns is not divisible by step");
- PROFILE_START
- cudak_(cuda_rearrange_frm)(b, a, step);
- PROFILE_STOP
+ nerv_matrix_(rearrange_frm)(a, b, step, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(scale_rows_by_col)(lua_State *L) {
+static int nerv_matrix_(lua_scale_rows_by_col)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
- if (a->nrow != b->nrow)
- nerv_error(L, "the number of rows is not the same");
- if (b->ncol != 1)
- nerv_error(L, "a column vector is expected");
- PROFILE_START
- cudak_(cuda_scale_rows_by_col)(b, a);
- PROFILE_STOP
+ const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ nerv_matrix_(scale_rows_by_col)(a, b, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
-static int nerv_matrix_(scale_rows_by_row)(lua_State *L) {
+static int nerv_matrix_(lua_scale_rows_by_row)(lua_State *L) {
+ Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
- if (a->ncol != b->ncol)
- nerv_error(L, "the number of columns is not the same");
- if (b->nrow != 1)
- nerv_error(L, "a row vector is expected");
- PROFILE_START
- cudak_(cuda_scale_rows_by_row)(b, a);
- PROFILE_STOP
+ const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ nerv_matrix_(scale_rows_by_row)(a, b, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
static const luaL_Reg nerv_matrix_(extra_methods)[] = {
- {"create", nerv_matrix_(create)},
- {"colsum", nerv_matrix_(colsum)},
- {"colsame", nerv_matrix_(colsame)},
- {"rowsum", nerv_matrix_(rowsum)},
- {"rowmax", nerv_matrix_(rowmax)},
- {"rowmax_idx", nerv_matrix_(rowmax_idx)},
- {"trans", nerv_matrix_(trans)},
- {"decompress", nerv_matrix_(decompress)},
+ {"create", nerv_matrix_(lua_create)},
+ {"colsum", nerv_matrix_(lua_colsum)},
+ {"colsame", nerv_matrix_(lua_colsame)},
+ {"rowsum", nerv_matrix_(lua_rowsum)},
+ {"rowmax", nerv_matrix_(lua_rowmax)},
+ {"rowmax_idx", nerv_matrix_(lua_rowmax_idx)},
+ {"trans", nerv_matrix_(lua_trans)},
+ {"decompress", nerv_matrix_(lua_decompress)},
/* in-place calc */
- {"copy_fromh", nerv_matrix_(copy_fromh)},
- {"copy_fromd", nerv_matrix_(copy_fromd)},
- {"copy_toh", nerv_matrix_(copy_toh)},
- {"add", nerv_matrix_(add)},
- {"mul", nerv_matrix_(mul)},
- {"add_row", nerv_matrix_(add_row)},
- {"fill", nerv_matrix_(fill)},
- {"sigmoid", nerv_matrix_(sigmoid)},
- {"sigmoid_grad", nerv_matrix_(sigmoid_grad)},
- {"softmax", nerv_matrix_(softmax)},
- {"mul_elem", nerv_matrix_(mul_elem)},
- {"log_elem", nerv_matrix_(log_elem)},
- {"copy_rows_fromh_by_idx", nerv_matrix_(copy_rows_fromh_by_idx)},
- {"expand_frm", nerv_matrix_(expand_frm)},
- {"rearrange_frm", nerv_matrix_(rearrange_frm)},
- {"scale_rows_by_row", nerv_matrix_(scale_rows_by_row)},
- {"scale_rows_by_col", nerv_matrix_(scale_rows_by_col)},
+ {"copy_fromh", nerv_matrix_(lua_copy_fromh)},
+ {"copy_fromd", nerv_matrix_(lua_copy_fromd)},
+ {"copy_toh", nerv_matrix_(lua_copy_toh)},
+ {"add", nerv_matrix_(lua_add)},
+ {"mul", nerv_matrix_(lua_mul)},
+ {"add_row", nerv_matrix_(lua_add_row)},
+ {"fill", nerv_matrix_(lua_fill)},
+ {"sigmoid", nerv_matrix_(lua_sigmoid)},
+ {"sigmoid_grad", nerv_matrix_(lua_sigmoid_grad)},
+ {"softmax", nerv_matrix_(lua_softmax)},
+ {"mul_elem", nerv_matrix_(lua_mul_elem)},
+ {"log_elem", nerv_matrix_(lua_log_elem)},
+ {"copy_rows_fromh_by_idx", nerv_matrix_(lua_copy_rows_fromh_by_idx)},
+ {"expand_frm", nerv_matrix_(lua_expand_frm)},
+ {"rearrange_frm", nerv_matrix_(lua_rearrange_frm)},
+ {"scale_rows_by_row", nerv_matrix_(lua_scale_rows_by_row)},
+ {"scale_rows_by_col", nerv_matrix_(lua_scale_rows_by_col)},
{NULL, NULL}
};
@@ -456,37 +312,34 @@ static void cuda_matrix_(init)(lua_State *L) {
luaN_append_methods(L, nerv_matrix_(extra_methods));
}
-static void cuda_matrix_(free)(lua_State *L, MATRIX_ELEM *ptr) {
- CUDA_SAFE_SYNC_CALL(cudaFree(ptr));
+int nerv_matrix_(lua_get_elem)(lua_State *L) {
+ return nerv_error_method_not_implemented(L);
}
-static void cuda_matrix_(alloc)(lua_State *L, MATRIX_ELEM **dptr,
- size_t *stride, long width, long height) {
- PROFILE_START
- CUDA_SAFE_SYNC_CALL(cudaMallocPitch((void **)dptr, stride, width, height));
- PROFILE_STOP
+int nerv_matrix_(lua_set_elem)(lua_State *L) {
+ return nerv_error_method_not_implemented(L);
}
static MATRIX_ELEM cuda_matrix_(read)(lua_State *L, MATRIX_ELEM *data,
- int idx) {
+ int idx) {
+ cudaError_t err;
MATRIX_ELEM res;
- CUDA_SAFE_SYNC_CALL(cudaMemcpy(&res, data + idx,
- sizeof(MATRIX_ELEM), cudaMemcpyDeviceToHost));
+ err = cudaMemcpy(&res, data + idx,
+ sizeof(MATRIX_ELEM), cudaMemcpyDeviceToHost);
+ if (err != cudaSuccess)
+ nerv_error(L, "cuda error: error while reading element");
+ cudaDeviceSynchronize();
return res;
}
static void cuda_matrix_(write)(lua_State *L, MATRIX_ELEM *data,
int idx, MATRIX_ELEM val) {
- CUDA_SAFE_SYNC_CALL(cudaMemcpy(data + idx, &val,
- sizeof(MATRIX_ELEM), cudaMemcpyHostToDevice));
-}
-
-int nerv_matrix_(get_elem)(lua_State *L) {
- return nerv_error_method_not_implemented(L);
-}
-
-int nerv_matrix_(set_elem)(lua_State *L) {
- return nerv_error_method_not_implemented(L);
+ cudaError_t err;
+ err = cudaMemcpy(data + idx, &val,
+ sizeof(MATRIX_ELEM), cudaMemcpyHostToDevice);
+ if (err != cudaSuccess)
+ nerv_error(L, "cuda error: error while writing element");
+ cudaDeviceSynchronize();
}
#include "matrix.c"
Powered by cgit, Themed by Ted Yin.