#ifdef NERV_GENERIC_CUMATRIX #include "matrix.h" #include "elem_type.h" #define MATRIX_DATA_FREE(ptr) cuda_matrix_(free)(ptr) #define MATRIX_DATA_ALLOC(dptr, stride, width, height) \ cuda_matrix_(alloc)(dptr, stride, width, height) #define MATRIX_DATA_WRITE(data, idx, val) cuda_matrix_(write)(data, idx, val) #define MATRIX_DATA_READ(data, idx) cuda_matrix_(read)(data, idx) #define MATRIX_INIT(L) cuda_matrix_(init)(L) #define MATRIX_BASE_TNAME nerv_matrix_cuda_tname #define NERV_GENERIC_MATRIX #define NERV_GENERIC_CUKERNEL #include "../../common.h" #include "../cukernel.h" #include "cuda.h" #include "cuda_runtime.h" #include "driver_types.h" #include "cublas_v2.h" static cublasHandle_t cublas_handle; Matrix *nerv_matrix_(new_)(long nrow, long ncol); static void nerv_matrix_(add_)(const Matrix *a, const Matrix *b, const Matrix *c, MATRIX_ELEM alpha, MATRIX_ELEM beta) { 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)); } static int nerv_matrix_(add)(lua_State *L) { 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); /* alpha */ MATRIX_ELEM beta = luaL_checknumber(L, 5); /* alpha */ if (!(a->nrow == b->nrow && a->ncol == b->ncol)) nerv_error(L, "Matrices should be of the same dimension"); nerv_matrix_(add_)(a, b, c, alpha, beta); return 0; } static int nerv_matrix_(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) 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)) \ : CUBLAS_OP_N; int tb = nargs > 6 ? nerv_matrix_(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; */ 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)); return 0; } static int nerv_matrix_(create)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); fprintf(stderr, "create\n"); Matrix *b = nerv_matrix_(new_)(a->nrow, a->ncol); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(sigmoid)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(new_)(a->nrow, a->ncol); cudak_(cuda_sigmoid)(a, b); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(softmax)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *max = nerv_matrix_(new_)(a->nrow, 1); Matrix *dno = nerv_matrix_(new_)(a->nrow, 1); Matrix *b = nerv_matrix_(new_)(a->nrow, a->ncol); cudak_(cuda_rowmax)(a, max); cudak_(cuda_softmax_denominator)(a, max, dno); cudak_(cuda_softmax_final)(a, max, dno, b); luaT_pushudata(L, b, 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_)(a->nrow, 1); cudak_(cuda_rowsum)(a, b); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(colsum)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(new_)(1, a->ncol); cudak_(cuda_colsum)(a, b); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(rowmax)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(new_)(a->nrow, 1); cudak_(cuda_rowmax)(a, b); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(add_row)(lua_State *L) { 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"); cudak_(cuda_add_row)(a, b, beta); 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); cudak_(cuda_fill)(self, val); return 0; } extern const char *MATRIX_CUMATRIX_HOST_TNAME; static int nerv_matrix_(copy_from)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); if (!(a->nrow == b->nrow && a->ncol == b->ncol)) nerv_error(L, "Matrices should be of the same dimension"); cudaMemcpy2D(MATRIX_ELEM_PTR(a), a->stride, MATRIX_ELEM_PTR(b), b->stride, sizeof(MATRIX_ELEM) * b->ncol, b->nrow, cudaMemcpyHostToDevice); return 0; } static int nerv_matrix_(copy_to)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); if (!(a->nrow == b->nrow && a->ncol == b->ncol)) nerv_error(L, "Matrices should be of the same dimension"); cudaMemcpy2D(MATRIX_ELEM_PTR(b), b->stride, MATRIX_ELEM_PTR(a), a->stride, sizeof(MATRIX_ELEM) * a->ncol, a->nrow, cudaMemcpyDeviceToHost); return 0; } static int nerv_matrix_(trans)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(new_)(a->ncol, a->nrow); MATRIX_ELEM alpha = 1, beta = 0; 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)); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static const luaL_Reg nerv_matrix_(extra_methods)[] = { {"create", nerv_matrix_(create)}, {"sigmoid", nerv_matrix_(sigmoid)}, {"softmax", nerv_matrix_(softmax)}, {"colsum", nerv_matrix_(colsum)}, {"rowsum", nerv_matrix_(rowsum)}, {"rowmax", nerv_matrix_(rowmax)}, {"copy_from", nerv_matrix_(copy_from)}, {"copy_to", nerv_matrix_(copy_to)}, {"trans", nerv_matrix_(trans)}, /* in-place calc */ {"add", nerv_matrix_(add)}, {"mul", nerv_matrix_(mul)}, {"add_row", nerv_matrix_(add_row)}, {"fill", nerv_matrix_(fill)}, {NULL, NULL} }; static void cuda_matrix_(init)(lua_State *L) { luaN_append_methods(L, nerv_matrix_(extra_methods)); cublasCreate(&cublas_handle); } static void cuda_matrix_(free)(MATRIX_ELEM *ptr) { cudaFree(ptr); } static void cuda_matrix_(alloc)(MATRIX_ELEM **dptr, size_t *stride, long width, long height) { cudaMallocPitch((void **)dptr, stride, width, height); } static MATRIX_ELEM cuda_matrix_(read)(MATRIX_ELEM *data, int idx) { MATRIX_ELEM res; cudaMemcpy(&res, data + idx, sizeof(MATRIX_ELEM), cudaMemcpyDeviceToHost); return res; } static void cuda_matrix_(write)(MATRIX_ELEM *data, int idx, MATRIX_ELEM val) { 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); } #include "matrix.c" #endif