From 5e407d74130accfbbf94d2cabcb03fc126a89410 Mon Sep 17 00:00:00 2001 From: Determinant Date: Wed, 24 Jun 2015 22:48:24 +0800 Subject: separate non-Lua part of matrix code to a dedicated dir --- nerv/Makefile | 43 +-- nerv/common.c | 25 ++ nerv/common.h | 45 +++ nerv/lib/io/chunk_file.c | 18 +- nerv/lib/matrix/cuda_helper.h | 110 +++++++ nerv/lib/matrix/cukernel.cu | 17 ++ nerv/lib/matrix/cukernel.h | 20 ++ nerv/lib/matrix/cumatrix.c | 69 +++++ nerv/lib/matrix/cumatrix.h | 6 + nerv/lib/matrix/generic/cukernel.cu | 571 ++++++++++++++++++++++++++++++++++++ nerv/lib/matrix/generic/cumatrix.c | 403 +++++++++++++++++++++++++ nerv/lib/matrix/generic/cumatrix.h | 50 ++++ nerv/lib/matrix/generic/elem_type.h | 22 ++ nerv/lib/matrix/generic/matrix.c | 57 ++++ nerv/lib/matrix/generic/matrix.h | 4 + nerv/lib/matrix/generic/mmatrix.c | 82 ++++++ nerv/lib/matrix/generic/mmatrix.h | 7 + nerv/lib/matrix/init.lua | 77 +++++ nerv/lib/matrix/matrix.h | 19 ++ nerv/lib/matrix/mmatrix.c | 53 ++++ nerv/lib/matrix/mmatrix.h | 4 + nerv/matrix/cuda_helper.h | 75 ----- nerv/matrix/cukernel.cu | 17 -- nerv/matrix/cukernel.h | 20 -- nerv/matrix/cumatrix.c | 44 +-- nerv/matrix/generic/cumatrix.c | 479 +++++++++++------------------- nerv/matrix/generic/matrix.c | 102 +++---- nerv/matrix/generic/matrix.h | 19 -- nerv/matrix/generic/mmatrix.c | 80 ++--- nerv/matrix/init.c | 9 +- nerv/matrix/mmatrix.c | 34 +-- nerv/nerv-scm-1.rockspec | 1 + speech | 2 +- 33 files changed, 1926 insertions(+), 658 deletions(-) create mode 100644 nerv/lib/matrix/cuda_helper.h create mode 100644 nerv/lib/matrix/cukernel.cu create mode 100644 nerv/lib/matrix/cukernel.h create mode 100644 nerv/lib/matrix/cumatrix.c create mode 100644 nerv/lib/matrix/cumatrix.h create mode 100644 nerv/lib/matrix/generic/cukernel.cu create mode 100644 nerv/lib/matrix/generic/cumatrix.c create mode 100644 nerv/lib/matrix/generic/cumatrix.h create mode 100644 nerv/lib/matrix/generic/elem_type.h create mode 100644 nerv/lib/matrix/generic/matrix.c create mode 100644 nerv/lib/matrix/generic/matrix.h create mode 100644 nerv/lib/matrix/generic/mmatrix.c create mode 100644 nerv/lib/matrix/generic/mmatrix.h create mode 100644 nerv/lib/matrix/init.lua create mode 100644 nerv/lib/matrix/matrix.h create mode 100644 nerv/lib/matrix/mmatrix.c create mode 100644 nerv/lib/matrix/mmatrix.h delete mode 100644 nerv/matrix/cuda_helper.h delete mode 100644 nerv/matrix/cukernel.cu delete mode 100644 nerv/matrix/cukernel.h delete mode 100644 nerv/matrix/generic/matrix.h diff --git a/nerv/Makefile b/nerv/Makefile index 4008453..06a439a 100644 --- a/nerv/Makefile +++ b/nerv/Makefile @@ -1,58 +1,65 @@ .PHONY: build install clean SHELL := /bin/bash BUILD_DIR := $(CURDIR)/build -OBJS := nerv.o lib/luaT/luaT.o lib/io/chunk_file.o common.o \ - matrix/mmatrix.o matrix/cumatrix.o matrix/init.o matrix/cukernel.o \ +LIB_PATH := $(LUA_BINDIR)/../lib +OBJ_DIR := $(BUILD_DIR)/objs +CORE_OBJS := common.o lib/io/chunk_file.o lib/matrix/mmatrix.o lib/matrix/cumatrix.o lib/matrix/cukernel.o +NERV_OBJS := nerv.o \ + matrix/mmatrix.o matrix/cumatrix.o matrix/init.o \ io/init.o io/chunk_file.o \ examples/oop_example.o -LIBS := libnerv.so +LUAT_OBJS := lib/luaT/luaT.o +CORE_OBJS := $(addprefix $(OBJ_DIR)/,$(CORE_OBJS)) +NERV_OBJS := $(addprefix $(OBJ_DIR)/,$(NERV_OBJS)) +LUAT_OBJS := $(addprefix $(OBJ_DIR)/,$(LUAT_OBJS)) +OBJS := $(CORE_OBJS) $(NERV_OBJS) $(LUAT_OBJS) +LIBS := $(INST_LIBDIR)/libnerv.so $(LIB_PATH)/libnervcore.so $(LIB_PATH)/libluaT.so LUA_LIBS := matrix/init.lua io/init.lua init.lua \ layer/init.lua layer/affine.lua layer/sigmoid.lua layer/softmax_ce.lua \ layer/window.lua layer/bias.lua layer/combiner.lua layer/mse.lua \ nn/init.lua nn/layer_repo.lua nn/param_repo.lua nn/layer_dag.lua \ io/sgd_buffer.lua INCLUDE := -I $(LUA_INCDIR) -DLUA_USE_APICHECK -CUDA_BASE := /usr/local/cuda-6.5 -#CUDA_BASE := /usr/local/cuda-5.0 +#CUDA_BASE := /usr/local/cuda-6.5 +CUDA_BASE := /usr/local/cuda-5.0 CUDA_INCLUDE := -I $(CUDA_BASE)/include/ INCLUDE += $(CUDA_INCLUDE) LDFLAGS := -L$(CUDA_BASE)/lib64/ -Wl,-rpath=$(CUDA_BASE)/lib64/ -lcudart -lcublas CFLAGS := -Wall -Wextra -O2 -OBJ_DIR := $(BUILD_DIR)/objs -SUBDIR := matrix io layer examples nn lib/io lib/luaT +SUBDIR := matrix io layer examples nn lib/io lib/luaT lib/matrix NVCC := $(CUDA_BASE)/bin/nvcc NVCC_FLAGS := -Xcompiler -fPIC,-Wall,-Wextra LUA_DIR = $(INST_LUADIR)/nerv -OBJS := $(addprefix $(OBJ_DIR)/,$(OBJS)) OBJ_SUBDIR := $(addprefix $(OBJ_DIR)/,$(SUBDIR)) LUA_SUBDIR := $(addprefix $(LUA_DIR)/,$(SUBDIR)) -LIBS := $(addprefix $(INST_LIBDIR)/,$(LIBS)) LUA_LIBS := $(addprefix $(LUA_DIR)/,$(LUA_LIBS)) build: $(OBJ_DIR) $(OBJ_SUBDIR) $(OBJS) + $(OBJ_DIR) $(LUA_DIR) $(OBJ_SUBDIR) $(LUA_SUBDIR): -mkdir -p $@ $(OBJ_DIR)/%.o: %.c $(patsubst /%.o,/%.c,$@) gcc -c -o $@ $< $(INCLUDE) -fPIC $(CFLAGS) -$(OBJ_DIR)/matrix/cukernel.o: matrix/cukernel.cu +$(OBJ_DIR)/lib/matrix/cukernel.o: lib/matrix/cukernel.cu $(NVCC) -c -o $@ $< $(INCLUDE) $(NVCC_FLAGS) $(LUA_DIR)/%.lua: %.lua cp $< $@ #$(OBJ_DIR)/luaT.o: # gcc -c -o $@ luaT/luaT.c $(INCLUDE) -fPIC -$(LIBS): $(OBJS) - gcc -shared -o $@ $(OBJS) $(LDFLAGS) +$(LIB_PATH)/libnervcore.so: $(CORE_OBJS) + gcc -shared -o $@ $^ $(LDFLAGS) +$(LIB_PATH)/libluaT.so: $(LUAT_OBJS) + gcc -shared -o $@ $^ $(LDFLAGS) +$(INST_LIBDIR)/libnerv.so: $(NERV_OBJS) $(LIB_PATH)/libnervcore.so $(LIB_PATH)/libluaT.so + gcc -shared -o $@ $(NERV_OBJS) $(LDFLAGS) -Wl,-rpath=$(LIB_PATH) -L$(LIB_PATH) -lnervcore -lluaT $(OBJ_DIR)/matrix/cumatrix.o: matrix/generic/cumatrix.c matrix/generic/matrix.c matrix/generic/cukernel.cu $(OBJ_DIR)/matrix/mmatrix.o: matrix/generic/mmatrix.c matrix/generic/matrix.c -$(OBJ_DIR)/matrix/cukernel.o: matrix/generic/cukernel.cu - -.PHONY: speech -speech: - -mkdir -p build/objs/speech/tnet_io - $(MAKE) -C speech/ BUILD_DIR=$(BUILD_DIR) LIB_DIR=$(LIB_DIR) OBJ_DIR=$(CURDIR)/build/objs/speech/ LUA_DIR=$(LUA_DIR) +$(OBJ_DIR)/lib/matrix/cumatrix.o: lib/matrix/generic/cumatrix.c lib/matrix/generic/matrix.c lib/matrix/generic/cukernel.cu +$(OBJ_DIR)/lib/matrix/mmatrix.o: lib/matrix/generic/mmatrix.c lib/matrix/generic/matrix.c +$(OBJ_DIR)/lib/matrix/cukernel.o: lib/matrix/generic/cukernel.cu clean: -rm -rf $(OBJ_DIR) diff --git a/nerv/common.c b/nerv/common.c index b4e39e6..0584438 100644 --- a/nerv/common.c +++ b/nerv/common.c @@ -11,6 +11,31 @@ int nerv_error(lua_State *L, const char *err_mesg_fmt, ...) { return 0; } +int nerv_error_status(lua_State *L, Status *status) { + const char *mmesg = NULL; + switch (status->err_code) + { + case MAT_GENERAL_ERR: mmesg = "general error"; break; + case MAT_INSUF_MEM: mmesg = "insufficient memory"; break; + case MAT_INVALID_FORMAT: mmesg = "invalid matrix format"; break; + case MAT_WRITE_ERROR: mmesg = "error while writing matrix"; break; + case MAT_INVALID_COPY_INTERVAL: mmesg = "invalid copy interval"; break; + case MAT_MISMATCH_DIM: mmesg = "mismatching matrix dimension"; break; + case MAT_WRONG_MULT_DIM: mmesg = "wrong multipier dimension"; break; + case MAT_ROW_VECTOR_EXP: mmesg = "row vector expected"; break; + case MAT_COL_VECTOR_EXP: mmesg = "column vector expected"; break; + case MAT_IDX_VECTOR_EXP: mmesg = "index vector expected"; break; + case MAT_INVALID_IDX: mmesg = "invalid index"; break; + case MAT_CUDA_ERR: mmesg = "cuda error"; break; + case MAT_CUBLAS_ERR: mmesg = "cublas error"; break; + } + if (status->msg) + nerv_error(L, "%s: %s @%s:%d", mmesg, status->msg, + status->file, status->lineno); + else + nerv_error(L, "%s @%s:%d", mmesg, status->file, status->lineno); +} + int nerv_error_method_not_implemented(lua_State *L) { return nerv_error(L, "method not implemented"); } diff --git a/nerv/common.h b/nerv/common.h index 6657dc4..413ca51 100644 --- a/nerv/common.h +++ b/nerv/common.h @@ -7,6 +7,50 @@ #include #include +enum { + MAT_NORMAL, + MAT_GENERAL_ERR, + MAT_INSUF_MEM, + MAT_INVALID_FORMAT, + MAT_WRITE_ERROR, + MAT_INVALID_COPY_INTERVAL, + MAT_MISMATCH_DIM, + MAT_WRONG_MULT_DIM, + MAT_ROW_VECTOR_EXP, + MAT_COL_VECTOR_EXP, + MAT_IDX_VECTOR_EXP, + MAT_INVALID_IDX, + MAT_CUDA_ERR, + MAT_CUBLAS_ERR +}; + +typedef struct Status { + int err_code; + const char *file; + int lineno; + const char *msg; +} Status; + +#define NERV_SET_STATUS(status, code, m) \ + do { \ + (status)->err_code = code; \ + (status)->msg = m; \ + (status)->file = __FILE__; \ + (status)->lineno = __LINE__; \ + } while (0) + +#define NERV_EXIT_STATUS(status, code, msg) \ + do { \ + NERV_SET_STATUS(status, code, msg); \ + return; \ + } while (0) + +#define NERV_LUA_CHECK_STATUS(L, status) \ + do { \ + if (status.err_code != MAT_NORMAL) \ + nerv_error_status(L, &status); \ + } while (0) + typedef struct HashNode { const char *key; void *val; @@ -31,6 +75,7 @@ void hashmap_clear(HashMap *h); size_t bkdr_hash(const char *key); int nerv_error(lua_State *L, const char *err_mesg_fmt, ...); +int nerv_error_status(lua_State *L, Status *status); int nerv_error_method_not_implemented(lua_State *L); void luaN_append_methods(lua_State *L, const luaL_Reg *mlist); #endif diff --git a/nerv/lib/io/chunk_file.c b/nerv/lib/io/chunk_file.c index a305962..e70ffc9 100644 --- a/nerv/lib/io/chunk_file.c +++ b/nerv/lib/io/chunk_file.c @@ -91,6 +91,7 @@ static ChunkFile *open_write(const char *fn, int *status) { } cfp = (ChunkFile *)malloc(sizeof(ChunkFile)); cfp->fp = fp; + cfp->info = NULL; cfp->status = CF_WRITE; *status = CF_NORMAL; return cfp; @@ -111,8 +112,6 @@ static ChunkFile *open_read(const char *fn, int *status) { return NULL; } cfp = (ChunkFile *)malloc(sizeof(ChunkFile)); - cfp->fp = fp; - cfp->status = CF_READ; offset = ftello(fp); /* fprintf(stderr, "%d\n", (int)offset); */ for (i = 0;; offset += chunk_len, i++) @@ -144,7 +143,9 @@ static ChunkFile *open_read(const char *fn, int *status) { head = cip; } *status = CF_NORMAL; + cfp->fp = fp; cfp->info = head; + cfp->status = CF_READ; return cfp; } @@ -208,13 +209,16 @@ void nerv_chunk_file_close(ChunkFile *cfp) { void nerv_chunk_file_destroy(ChunkFile *cfp) { ChunkInfo *i, *ni; - if (cfp->status != CF_CLOSED) fclose(cfp->fp); - for (i = cfp->info; i; i = ni) + if (cfp->info) { - ni = i->next; - free(i->metadata); - free(i); + for (i = cfp->info; i; i = ni) + { + ni = i->next; + free(i->metadata); + free(i); + } } + if (cfp->status != CF_CLOSED) fclose(cfp->fp); free(cfp); } diff --git a/nerv/lib/matrix/cuda_helper.h b/nerv/lib/matrix/cuda_helper.h new file mode 100644 index 0000000..8041efb --- /dev/null +++ b/nerv/lib/matrix/cuda_helper.h @@ -0,0 +1,110 @@ +#ifndef NERV_CUDA_HELPER_H +#define NERV_CUDA_HELPER_H +#include "cuda.h" +#include "cuda_runtime.h" +#include "driver_types.h" +#include "cublas_v2.h" + +#define CUBLAS_SAFE_SYNC_CALL_RET(call, status) \ + do { \ + cublasStatus_t err = (call); \ + if (err != CUBLAS_STATUS_SUCCESS) \ + { \ + NERV_SET_STATUS(status, MAT_CUBLAS_ERR, cublasGetErrorString(err)); \ + return 0; \ + } \ + cudaDeviceSynchronize(); \ + } while (0) + +#define CUBLAS_SAFE_SYNC_CALL(call, status) \ + do { \ + cublasStatus_t err = (call); \ + if (err != CUBLAS_STATUS_SUCCESS) \ + NERV_EXIT_STATUS(status, MAT_CUBLAS_ERR, cublasGetErrorString(err)); \ + cudaDeviceSynchronize(); \ + } while (0) + +#define CUDA_SAFE_CALL_RET(call, status) \ + do { \ + cudaError_t err = (call); \ + if (err != cudaSuccess) \ + { \ + NERV_SET_STATUS(status, MAT_CUDA_ERR, cudaGetErrorString(err)); \ + return 0; \ + } \ + } while (0) + +#define CUDA_SAFE_CALL(call, status) \ + do { \ + cudaError_t err = (call); \ + if (err != cudaSuccess) \ + NERV_EXIT_STATUS(status, MAT_CUDA_ERR, cudaGetErrorString(err)); \ + } while (0) + +#define CUDA_SAFE_SYNC_CALL(call, status) \ + do { \ + CUDA_SAFE_CALL(call, status); \ + cudaDeviceSynchronize(); \ + } while (0) + +#define CUDA_SAFE_SYNC_CALL_RET(call, status) \ + do { \ + CUDA_SAFE_CALL_RET(call, status); \ + cudaDeviceSynchronize(); \ + } while (0) + +#define CHECK_SAME_DIMENSION(a, b, status) \ + do { \ + if (!(a->nrow == b->nrow && a->ncol == b->ncol)) \ + NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0); \ + } while (0) + +#define CHECK_SAME_DIMENSION_RET(a, b, status) \ + do { \ + if (!(a->nrow == b->nrow && a->ncol == b->ncol)) \ + { \ + NERV_SET_STATUS(status, MAT_MISMATCH_DIM, 0); \ + return 0; \ + } \ + } while (0) + +static const char *cublasGetErrorString(cublasStatus_t err) { + switch (err) + { + case CUBLAS_STATUS_SUCCESS: + return "CUBLAS_STATUS_SUCCESS"; + case CUBLAS_STATUS_NOT_INITIALIZED: + return "CUBLAS_STATUS_NOT_INITIALIZED"; + case CUBLAS_STATUS_ALLOC_FAILED: + return "CUBLAS_STATUS_ALLOC_FAILED"; + case CUBLAS_STATUS_INVALID_VALUE: + return "CUBLAS_STATUS_INVALID_VALUE"; + case CUBLAS_STATUS_ARCH_MISMATCH: + return "CUBLAS_STATUS_ARCH_MISMATCH"; + case CUBLAS_STATUS_MAPPING_ERROR: + return "CUBLAS_STATUS_MAPPING_ERROR"; + case CUBLAS_STATUS_EXECUTION_FAILED: + return "CUBLAS_STATUS_EXECUTION_FAILED"; + case CUBLAS_STATUS_INTERNAL_ERROR: + return "CUBLAS_STATUS_INTERNAL_ERROR"; +/* case CUBLAS_STATUS_NOT_SUPPORTED: + return "CUBLAS_STATUS_NOT_SUPPORTED"; + case CUBLAS_STATUS_LICENSE_ERROR: + return "CUBLAS_STATUS_LICENSE_ERROR"; */ + } + return ""; +} + +#define PROFILE_START \ + do { \ + cudaEventRecord(profile_start, 0); +#define PROFILE_STOP \ + cudaEventRecord(profile_stop, 0); \ + cudaEventSynchronize(profile_stop); \ + float milliseconds = 0; \ + cudaEventElapsedTime(&milliseconds, profile_start, profile_stop); \ + accu_profile(__func__, milliseconds / 1000); \ + } while (0); + +#define PROFILE_END +#endif diff --git a/nerv/lib/matrix/cukernel.cu b/nerv/lib/matrix/cukernel.cu new file mode 100644 index 0000000..a19030a --- /dev/null +++ b/nerv/lib/matrix/cukernel.cu @@ -0,0 +1,17 @@ +#define NERV_GENERIC_CUKERNEL + +#define cudak_(NAME) cudak_float_ ## NAME +#define MATRIX_USE_FLOAT +#include "generic/elem_type.h" +#include "generic/cukernel.cu" +#undef cudak_ +#undef MATRIX_USE_FLOAT +#undef MATRIX_ELEM +#undef MATRIX_ELEM_PTR +#undef MATRIX_ELEM_FMT +#undef MATRIX_ELEM_WRITE_FMT + +#define cudak_(NAME) cudak_double_ ## NAME +#define MATRIX_USE_DOUBLE +#include "generic/elem_type.h" +#include "generic/cukernel.cu" diff --git a/nerv/lib/matrix/cukernel.h b/nerv/lib/matrix/cukernel.h new file mode 100644 index 0000000..8a1494f --- /dev/null +++ b/nerv/lib/matrix/cukernel.h @@ -0,0 +1,20 @@ +#ifdef NERV_GENERIC_CUKERNEL +void cudak_(cuda_mul_elem)(const Matrix *a, const Matrix *b, Matrix *c); +void cudak_(cuda_log_elem)(const Matrix *a, Matrix *b); +void cudak_(cuda_sigmoid)(const Matrix *a, Matrix *b); +void cudak_(cuda_sigmoid_grad)(const Matrix *output, const Matrix *err, Matrix *nerr); +void cudak_(cuda_rowsum)(const Matrix *a, Matrix *b); +void cudak_(cuda_rowmax)(const Matrix *a, Matrix *b); +void cudak_(cuda_rowmax_idx)(const Matrix *a, Matrix *b, Matrix *idx); +void cudak_(cuda_colsum)(const Matrix *a, Matrix *b); +void cudak_(cuda_colsame)(const Matrix *a, const Matrix *ref, Matrix *b); +void cudak_(cuda_softmax_denominator)(const Matrix *a, const Matrix *max, Matrix *b); +void cudak_(cuda_softmax_final)(const Matrix *a, const Matrix *max, const Matrix *deno, Matrix *b); +void cudak_(cuda_add_row)(const Matrix *a, Matrix *b, double beta); +void cudak_(cuda_fill)(Matrix *a, double val); +void cudak_(cuda_expand_frm)(const Matrix *a, Matrix *b, int context); +void cudak_(cuda_rearrange_frm)(const Matrix *a, Matrix *b, int step); +void cudak_(cuda_scale_rows_by_row)(const Matrix *a, Matrix *b); +void cudak_(cuda_scale_rows_by_col)(const Matrix *a, Matrix *b); +void cudak_(cuda_decompress)(const Matrix *a, Matrix *b); +#endif diff --git a/nerv/lib/matrix/cumatrix.c b/nerv/lib/matrix/cumatrix.c new file mode 100644 index 0000000..9641197 --- /dev/null +++ b/nerv/lib/matrix/cumatrix.c @@ -0,0 +1,69 @@ +#define NERV_GENERIC_CUMATRIX +#include "../../common.h" +#include "cuda_helper.h" +#include +#define PROFILE_HASHMAP_SIZE 123457 +static cublasHandle_t cublas_handle; +static cudaEvent_t profile_start, profile_stop; +static HashMap *profile; + +void nerv_cumatrix_print_profile() { + size_t i; + fprintf(stderr, "*** [nerv cumatrix profile] **\n"); + for (i = 0; i < profile->size; i++) + { + HashNode *ptr; + for (ptr = profile->bucket[i]; ptr; ptr = ptr->next) + { + fprintf(stderr, "%s:\t%.6f\n", ptr->key, *(float *)ptr->val); + } + } +} + +void nerv_cumatrix_clear_profile() { + hashmap_clear(profile); +} + +void accu_profile(const char *name, float delta) { + float *val = hashmap_getval(profile, name); + if (!val) + { + val = malloc(sizeof(float)); + *val = 0; + hashmap_setval(profile, name, val); + } + *val += delta; +} + +void nerv_cumatrix_init() { + cublasCreate(&cublas_handle); + cudaEventCreate(&profile_start); + cudaEventCreate(&profile_stop); + profile = hashmap_create(PROFILE_HASHMAP_SIZE, bkdr_hash, strcmp); +} + +#define MATRIX_USE_FLOAT +#define cuda_matrix_(NAME) cuda_matrix_float_##NAME +#define nerv_matrix_(NAME) nerv_matrix_cuda_float_##NAME +#define cudak_(NAME) cudak_float_ ## NAME +#define NERV_CUBLAS_(NAME) cublasS##NAME +#define MATRIX_CUMATRIX_HOST_TNAME nerv_matrix_host_float_tname +#include "generic/cumatrix.c" +#undef NERV_CUBLAS_ +#undef cudak_ +#undef nerv_matrix_ +#undef cuda_matrix_ +#undef MATRIX_USE_FLOAT +#undef MATRIX_ELEM +#undef MATRIX_ELEM_PTR +#undef MATRIX_ELEM_FMT +#undef MATRIX_ELEM_WRITE_FMT +#undef MATRIX_CUMATRIX_HOST_TNAME + +#define MATRIX_USE_DOUBLE +#define cuda_matrix_(NAME) cuda_matrix_double_##NAME +#define nerv_matrix_(NAME) nerv_matrix_cuda_double_##NAME +#define cudak_(NAME) cudak_double_ ## NAME +#define NERV_CUBLAS_(NAME) cublasD##NAME +#define MATRIX_CUMATRIX_HOST_TNAME nerv_matrix_host_double_tname +#include "generic/cumatrix.c" diff --git a/nerv/lib/matrix/cumatrix.h b/nerv/lib/matrix/cumatrix.h new file mode 100644 index 0000000..9f71507 --- /dev/null +++ b/nerv/lib/matrix/cumatrix.h @@ -0,0 +1,6 @@ +#ifndef NERV_CUMATRIX_H +#define NERV_CUMATRIX_H +void nerv_cumatrix_print_profile(); +void nerv_cumatrix_clear_profile(); +void nerv_cumatrix_init(); +#endif 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 +#include +#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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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) \ + <<>> \ + (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) \ + <<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>>(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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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)<<>> \ + (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 diff --git a/nerv/lib/matrix/generic/cumatrix.c b/nerv/lib/matrix/generic/cumatrix.c new file mode 100644 index 0000000..11aacec --- /dev/null +++ b/nerv/lib/matrix/generic/cumatrix.c @@ -0,0 +1,403 @@ +#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 diff --git a/nerv/lib/matrix/generic/cumatrix.h b/nerv/lib/matrix/generic/cumatrix.h new file mode 100644 index 0000000..9a4f87e --- /dev/null +++ b/nerv/lib/matrix/generic/cumatrix.h @@ -0,0 +1,50 @@ +#include "../../../common.h" + +void nerv_matrix_(add)(Matrix *c, const Matrix *a, const Matrix *b, + MATRIX_ELEM alpha, MATRIX_ELEM beta, + Status *status); +void nerv_matrix_(mul)(Matrix *c, const Matrix *a, const Matrix *b, + MATRIX_ELEM alpha, MATRIX_ELEM beta, + int ta, int tb, Status *status); +void nerv_matrix_(sigmoid)(Matrix *a, const Matrix *b, Status *status); +void nerv_matrix_(sigmoid_grad)(Matrix *nerr, const Matrix *err, + const Matrix *output, Status *status); + +Matrix *nerv_matrix_(softmax)(Matrix *b, const Matrix *a, Status *status); +Matrix *nerv_matrix_(rowsum)(Matrix *a, Status *status); +Matrix *nerv_matrix_(colsum)(Matrix *a, Status *status); +Matrix *nerv_matrix_(colsame)(Matrix *a, const Matrix *ref, + Status *status); +Matrix *nerv_matrix_(rowmax)(Matrix *a, Status *status); +void nerv_matrix_(rowmax_idx)(Matrix *a, Matrix **b, Matrix **idx, + Status *status); +void nerv_matrix_(add_row)(Matrix *b, const Matrix *a, double beta, + Status *status); +void nerv_matrix_(fill)(Matrix *self, double val, Status *status); +void nerv_matrix_(copy_fromd)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status); +void nerv_matrix_(copy_fromh)(Matrix *a, const Matrix *b, + int a_begin, int b_begin, int b_end, + Status *status); +void nerv_matrix_(copy_toh)(Matrix *a, const Matrix *b, + int a_begin, int a_end, int b_begin, + Status *status); +Matrix *nerv_matrix_(trans)(Matrix *a, Status *status); +void nerv_matrix_(mul_elem)(Matrix *c, const Matrix *a, const Matrix *b, + Status *status); + +void nerv_matrix_(log_elem)(Matrix *b, const Matrix *a, Status *status); + +Matrix *nerv_matrix_(decompress)(const Matrix *a, int orig_col, Status *status); +void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b, + const Matrix *idx, int b_begin, Status *status); + +void nerv_matrix_(expand_frm)(Matrix *a, const Matrix *b, + int context, Status *status); +void nerv_matrix_(rearrange_frm)(Matrix *a, const Matrix *b, + int step, Status *status); +void nerv_matrix_(scale_rows_by_col)(Matrix *a, const Matrix *b, + Status *status); +void nerv_matrix_(scale_rows_by_row)(Matrix *a, const Matrix *b, + Status *status); diff --git a/nerv/lib/matrix/generic/elem_type.h b/nerv/lib/matrix/generic/elem_type.h new file mode 100644 index 0000000..bffe940 --- /dev/null +++ b/nerv/lib/matrix/generic/elem_type.h @@ -0,0 +1,22 @@ +#ifdef MATRIX_USE_FLOAT + +#define MATRIX_ELEM float +#define MATRIX_ELEM_FMT "%f" +#define MATRIX_ELEM_WRITE_FMT "%.8f" +#define MATRIX_ELEM_PTR(self) ((self)->data.f) + +#elif defined(MATRIX_USE_DOUBLE) + +#define MATRIX_ELEM double +#define MATRIX_ELEM_FMT "%lf" +#define MATRIX_ELEM_WRITE_FMT "%.8lf" +#define MATRIX_ELEM_PTR(self) ((self)->data.d) + +#elif defined(MATRIX_USE_INT) + +#define MATRIX_ELEM long +#define MATRIX_ELEM_FMT "%ld" +#define MATRIX_ELEM_WRITE_FMT "%ld" +#define MATRIX_ELEM_PTR(self) ((self)->data.i) + +#endif diff --git a/nerv/lib/matrix/generic/matrix.c b/nerv/lib/matrix/generic/matrix.c new file mode 100644 index 0000000..91577e1 --- /dev/null +++ b/nerv/lib/matrix/generic/matrix.c @@ -0,0 +1,57 @@ +#ifdef NERV_GENERIC_MATRIX +#include "../../../common.h" +#include "matrix.h" +/* FIXME: malloc failure detection */ + +static void nerv_matrix_(data_free)(Matrix *self, Status *status) { + assert(*self->data_ref > 0); + if (--(*self->data_ref) == 0) + { + /* free matrix data */ + MATRIX_DATA_FREE(MATRIX_ELEM_PTR(self), status); + free(self->data_ref); + free(self); + } + else NERV_SET_STATUS(status, MAT_NORMAL, 0); +} + +static void nerv_matrix_(data_retain)(Matrix *self) { + (*self->data_ref)++; +} + +Matrix *nerv_matrix_(create)(long nrow, long ncol, Status *status) { + Matrix *self = (Matrix *)malloc(sizeof(Matrix)); + self->nrow = nrow; + self->ncol = ncol; + self->nmax = self->nrow * self->ncol; + MATRIX_DATA_ALLOC(&MATRIX_ELEM_PTR(self), &self->stride, + sizeof(MATRIX_ELEM) * self->ncol, self->nrow, + status); + if (status->err_code != MAT_NORMAL) + { + free(self); + return NULL; + } + self->data_ref = (long *)malloc(sizeof(long)); + *self->data_ref = 0; + nerv_matrix_(data_retain)(self); + NERV_SET_STATUS(status, MAT_NORMAL, 0); + return self; +} + +void nerv_matrix_(destroy)(Matrix *self, Status *status) { + nerv_matrix_(data_free)(self, status); +} + +Matrix *nerv_matrix_(getrow)(Matrix *self, int row) { + Matrix *prow = (Matrix *)malloc(sizeof(Matrix)); + prow->ncol = self->ncol; + prow->nrow = 1; + prow->stride = self->stride; + prow->nmax = prow->ncol; + MATRIX_ELEM_PTR(prow) = MATRIX_ROW_PTR(self, row); + prow->data_ref = self->data_ref; + nerv_matrix_(data_retain)(prow); + return prow; +} +#endif diff --git a/nerv/lib/matrix/generic/matrix.h b/nerv/lib/matrix/generic/matrix.h new file mode 100644 index 0000000..9d44e6d --- /dev/null +++ b/nerv/lib/matrix/generic/matrix.h @@ -0,0 +1,4 @@ +#include "../matrix.h" +Matrix *nerv_matrix