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authorDeterminant <[email protected]>2015-06-05 10:58:57 +0800
committerDeterminant <[email protected]>2015-06-05 10:58:57 +0800
commitdf737041e4a9f3f55978cc74db9a9cea27fa9fa0 (patch)
treed656820be286550bc548f7c5ed4b1dcfecf3691c /matrix/generic/cumatrix.c
parentea6f2990f99dd9ded6a0e74d75a3ec84900a2518 (diff)
add profiling; add ce accurarcy; several other changes
Diffstat (limited to 'matrix/generic/cumatrix.c')
-rw-r--r--matrix/generic/cumatrix.c97
1 files changed, 84 insertions, 13 deletions
diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c
index 373fc42..8e7d34f 100644
--- a/matrix/generic/cumatrix.c
+++ b/matrix/generic/cumatrix.c
@@ -11,15 +11,11 @@
#define MATRIX_BASE_TNAME nerv_matrix_cuda_tname
#define NERV_GENERIC_MATRIX
#define NERV_GENERIC_CUKERNEL
+#define PROFILE_HASHMAP_SIZE 123457
#include "../../common.h"
#include "../cukernel.h"
-#include "cuda.h"
-#include "cuda_runtime.h"
-#include "driver_types.h"
-#include "cublas_v2.h"
#include "../cuda_helper.h"
-
-static cublasHandle_t cublas_handle;
+#include <string.h>
Matrix *nerv_matrix_(new_)(lua_State *L, long nrow, long ncol);
void nerv_matrix_(data_free)(lua_State *L, Matrix *self);
@@ -27,6 +23,7 @@ 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_CALL(
NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_N, CUBLAS_OP_N,
a->ncol, a->nrow,
@@ -35,6 +32,7 @@ static void nerv_matrix_(add_)(lua_State *L, const Matrix *a, const Matrix *b,
&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) {
@@ -75,6 +73,7 @@ static int nerv_matrix_(mul)(lua_State *L) {
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_CALL(
NERV_CUBLAS_(gemm)(cublas_handle, tb, ta,
bn, am, bm,
@@ -83,6 +82,7 @@ static int nerv_matrix_(mul)(lua_State *L) {
MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM),
&beta,
MATRIX_ELEM_PTR(c), c->stride / sizeof(MATRIX_ELEM)));
+ PROFILE_STOP
return 0;
}
@@ -97,7 +97,9 @@ 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;
}
@@ -107,30 +109,38 @@ static int nerv_matrix_(sigmoid_grad)(lua_State *L) {
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;
+ 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);
- cudak_(cuda_rowmax)(a, max);
+ 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);
- return 0;
+ 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;
}
@@ -138,7 +148,21 @@ static int nerv_matrix_(rowsum)(lua_State *L) {
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;
}
@@ -146,11 +170,24 @@ static int nerv_matrix_(colsum)(lua_State *L) {
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));
@@ -160,14 +197,18 @@ static int nerv_matrix_(add_row)(lua_State *L) {
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;
}
@@ -183,11 +224,13 @@ static int nerv_matrix_(copy_fromd)(lua_State *L) {
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;
}
@@ -204,11 +247,13 @@ static int nerv_matrix_(copy_fromh)(lua_State *L) {
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;
}
@@ -224,11 +269,13 @@ static int nerv_matrix_(copy_toh)(lua_State *L) {
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
return 0;
}
@@ -237,6 +284,7 @@ static int nerv_matrix_(trans)(lua_State *L) {
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_CALL(
NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_T, CUBLAS_OP_T,
a->nrow, a->ncol,
@@ -245,6 +293,7 @@ static int nerv_matrix_(trans)(lua_State *L) {
&beta,
MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM),
MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM)));
+ PROFILE_STOP
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
@@ -255,7 +304,9 @@ static int nerv_matrix_(mul_elem)(lua_State *L) {
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
return 0;
}
@@ -263,7 +314,9 @@ static int nerv_matrix_(log_elem)(lua_State *L) {
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
return 0;
}
@@ -274,8 +327,10 @@ static int nerv_matrix_(decompress)(lua_State *L) {
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
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
@@ -285,21 +340,25 @@ static int nerv_matrix_(copy_rows_fromh_by_idx)(lua_State *L) {
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);
+ 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;
- long nrow = a->nrow;
if (idx->nrow != 1)
nerv_error(L, "index should be a vector");
- if (idx->ncol != nrow)
- nerv_error(L, "index dimension mismatch");
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, idx_ptr[i]),
+ MATRIX_ROW_PTR(b, src_row),
b->stride,
cudaMemcpyHostToDevice, streams[i]));
}
@@ -308,6 +367,7 @@ static int nerv_matrix_(copy_rows_fromh_by_idx)(lua_State *L) {
CUDA_SAFE_CALL(cudaStreamSynchronize(streams[i]));
CUDA_SAFE_CALL(cudaStreamDestroy(streams[i]));
}
+ free(streams);
return 0;
}
@@ -319,7 +379,9 @@ static int nerv_matrix_(expand_frm)(lua_State *L) {
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
return 0;
}
@@ -330,7 +392,9 @@ static int nerv_matrix_(rearrange_frm)(lua_State *L) {
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
return 0;
}
@@ -341,15 +405,19 @@ static int nerv_matrix_(scale_row)(lua_State *L) {
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_row)(b, a);
+ PROFILE_STOP
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)},
/* in-place calc */
@@ -375,6 +443,7 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
static void cuda_matrix_(init)(lua_State *L) {
luaN_append_methods(L, nerv_matrix_(extra_methods));
cublasCreate(&cublas_handle);
+ profile = hashmap_create(PROFILE_HASHMAP_SIZE, bkdr_hash, strcmp);
}
static void cuda_matrix_(free)(lua_State *L, MATRIX_ELEM *ptr) {
@@ -383,7 +452,9 @@ static void cuda_matrix_(free)(lua_State *L, MATRIX_ELEM *ptr) {
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
}
static MATRIX_ELEM cuda_matrix_(read)(lua_State *L, MATRIX_ELEM *data,