diff options
Diffstat (limited to 'matrix/generic')
| -rw-r--r-- | matrix/generic/cukernel.cu | 184 | ||||
| -rw-r--r-- | matrix/generic/cumatrix.c | 143 | ||||
| -rw-r--r-- | matrix/generic/elem_type.h | 11 | ||||
| -rw-r--r-- | matrix/generic/matrix.c | 83 | ||||
| -rw-r--r-- | matrix/generic/matrix.h | 1 | ||||
| -rw-r--r-- | matrix/generic/mmatrix.c | 41 |
6 files changed, 423 insertions, 40 deletions
diff --git a/matrix/generic/cukernel.cu b/matrix/generic/cukernel.cu new file mode 100644 index 0000000..a37ccf4 --- /dev/null +++ b/matrix/generic/cukernel.cu @@ -0,0 +1,184 @@ +#ifdef NERV_GENERIC_CUKERNEL +#include <assert.h> +#include <stdio.h> +#include "matrix.h" +#include "cuda.h" +#define CUDA_THREADS_N 16 +#define CUDA_THREADS_NN (16 * 16) +#define CEIL_DIV(a, b) (((a) + (b) - 1) / (b)) +__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_(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_sum)(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_softmax_sum)(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_max)(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) + { + 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]; +} + +extern "C" { +#include "../cukernel.h" + 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)<<<numBlocks, threadsPerBlock>>> \ + (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), b->nrow, b->ncol, + b->stride / sizeof(MATRIX_ELEM)); + } + + void cudak_(cuda_colsum)(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_sum)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ + (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; + cudak_(block_reduce_sum)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ + (res, MATRIX_ELEM_PTR(b), + stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), + ncol); + 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)<<<numBlocks, threadsPerBlock>>> \ + (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)); + } + + 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_sum)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ + (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; + cudak_(block_reduce_sum)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ + (res, MATRIX_ELEM_PTR(b), + stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), + ncol); + cudaFree(res); + } + + void cudak_(cuda_colmax)(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_max)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ + (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; + cudak_(block_reduce_max)<<<grid, block, block.x * sizeof(MATRIX_ELEM)>>> \ + (res, MATRIX_ELEM_PTR(b), + stride / sizeof(MATRIX_ELEM), b->stride / sizeof(MATRIX_ELEM), + ncol); + cudaFree(res); + } +} +#endif diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c new file mode 100644 index 0000000..f0ef99d --- /dev/null +++ b/matrix/generic/cumatrix.c @@ -0,0 +1,143 @@ +#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 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 int nerv_matrix_(add)(lua_State *L) { + Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); + Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); + Matrix *c; + long nrow, ncol; + if (!(a->nrow == b->nrow && a->ncol == b->ncol)) + nerv_error(L, "Matrices should be of the same dimension"); + nrow = a->nrow; + ncol = a->ncol; + c = nerv_matrix_(new_)(nrow, ncol); + MATRIX_ELEM alpha = 1.0f, beta = 1.0f; + NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_N, CUBLAS_OP_N, + ncol, 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)); + luaT_pushudata(L, c, nerv_matrix_(tname)); + return 1; +} + +static int nerv_matrix_(mul)(lua_State *L) { + Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); + Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); + Matrix *c; + if (a->ncol != b->nrow) + nerv_error(L, "Wrong dimension of multipliers"); + c = nerv_matrix_(new_)(a->nrow, b->ncol); + MATRIX_ELEM alpha = 1.0f, beta = 0.0f; + NERV_CUBLAS_(gemm)(cublas_handle, CUBLAS_OP_N, CUBLAS_OP_N, + b->ncol, a->nrow, b->nrow, + &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)); + luaT_pushudata(L, c, 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_colmax)(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_(colsum)(lua_State *L) { + Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); + Matrix *b = nerv_matrix_(new_)(a->nrow, 1); + cudak_(cuda_colsum)(a, b); + luaT_pushudata(L, b, nerv_matrix_(tname)); + return 1; +} + +static int nerv_matrix_(colmax)(lua_State *L) { + Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); + Matrix *b = nerv_matrix_(new_)(a->nrow, 1); + cudak_(cuda_colmax)(a, b); + luaT_pushudata(L, b, nerv_matrix_(tname)); + return 1; +} + +static const luaL_Reg nerv_matrix_(extra_methods)[] = { + {"__add__", nerv_matrix_(add)}, + {"__mul__", nerv_matrix_(mul)}, + {"sigmoid", nerv_matrix_(sigmoid)}, + {"softmax", nerv_matrix_(softmax)}, + {"colsum", nerv_matrix_(colsum)}, + {"colmax", nerv_matrix_(colmax)}, + {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 diff --git a/matrix/generic/elem_type.h b/matrix/generic/elem_type.h new file mode 100644 index 0000000..8f80306 --- /dev/null +++ b/matrix/generic/elem_type.h @@ -0,0 +1,11 @@ +#ifdef MATRIX_USE_FLOAT + +#define MATRIX_ELEM float +#define MATRIX_ELEM_PTR(self) ((self)->data.f) + +#elif defined(MATRIX_USE_DOUBLE) + +#define MATRIX_ELEM double +#define MATRIX_ELEM_PTR(self) ((self)->data.d) + +#endif diff --git a/matrix/generic/matrix.c b/matrix/generic/matrix.c index 9ced397..f0f81a9 100644 --- a/matrix/generic/matrix.c +++ b/matrix/generic/matrix.c @@ -3,59 +3,61 @@ #include "matrix.h" extern const char *nerv_matrix_tname; -extern const char *nerv_float_matrix_(tname); +extern const char *nerv_matrix_(tname); -void nerv_float_matrix_(data_free)(Matrix *self) { +void nerv_matrix_(data_free)(Matrix *self) { if (--(*self->data_ref) == 0) - MATRIX_DATA_FREE(self->data.f); + MATRIX_DATA_FREE(MATRIX_ELEM_PTR(self)); } -void nerv_float_matrix_(data_retain)(Matrix *self) { +void nerv_matrix_(data_retain)(Matrix *self) { (*self->data_ref)++; } -Matrix *nerv_float_matrix_(new_)(long nrow, long ncol) { +Matrix *nerv_matrix_(new_)(long nrow, long ncol) { Matrix *self = (Matrix *)malloc(sizeof(Matrix)); self->nrow = nrow; self->ncol = ncol; self->nmax = self->nrow * self->ncol; - MATRIX_DATA_ALLOC(&self->data.f, &self->stride, sizeof(float) * self->ncol, self->nrow); + MATRIX_DATA_ALLOC(&MATRIX_ELEM_PTR(self), &self->stride, + sizeof(MATRIX_ELEM) * self->ncol, self->nrow); self->data_ref = (long *)malloc(sizeof(long)); *self->data_ref = 0; - nerv_float_matrix_(data_retain)(self); + nerv_matrix_(data_retain)(self); return self; } -int nerv_float_matrix_(new)(lua_State *L) { - luaT_pushudata(L, nerv_float_matrix_(new_)(luaL_checkinteger(L, 1), +int nerv_matrix_(new)(lua_State *L) { + luaT_pushudata(L, nerv_matrix_(new_)(luaL_checkinteger(L, 1), luaL_checkinteger(L, 2)), - nerv_float_matrix_(tname)); + nerv_matrix_(tname)); return 1; } -int nerv_float_matrix_(destroy)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_float_matrix_(tname)); - nerv_float_matrix_(data_free)(self); +int nerv_matrix_(destroy)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); + nerv_matrix_(data_free)(self); return 0; } -int nerv_float_matrix_(get_elem)(lua_State *L); -int nerv_float_matrix_(set_elem)(lua_State *L); +int nerv_matrix_(get_elem)(lua_State *L); +int nerv_matrix_(set_elem)(lua_State *L); -static Matrix *nerv_float_matrix_(getrow)(Matrix *self, int row) { +static 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; - prow->data.f = (float *)((char *)self->data.f + row * self->stride); + MATRIX_ELEM_PTR(prow) = \ + (MATRIX_ELEM *)((char *)MATRIX_ELEM_PTR(self) + row * self->stride); prow->data_ref = self->data_ref; - nerv_float_matrix_(data_retain)(self); + nerv_matrix_(data_retain)(self); return prow; } -static int nerv_float_matrix_(newindex)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_float_matrix_(tname)); +static int nerv_matrix_(newindex)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); if (lua_isnumber(L, 2)) { int idx = luaL_checkinteger(L, 2); @@ -63,7 +65,8 @@ static int nerv_float_matrix_(newindex)(lua_State *L) { { if (idx < 0 || idx >= self->ncol) nerv_error(L, "index must be within range [0, %d)", self->ncol); - MATRIX_DATA_WRITE(self->data.f, idx, luaL_checknumber(L, 3)); + MATRIX_DATA_WRITE(MATRIX_ELEM_PTR(self), idx, + luaL_checknumber(L, 3)); } else nerv_error(L, "cannot assign a scalar to row vector"); @@ -78,8 +81,8 @@ static int nerv_float_matrix_(newindex)(lua_State *L) { } -static int nerv_float_matrix_(index)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_float_matrix_(tname)); +static int nerv_matrix_(index)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); if (lua_isnumber(L, 2)) { int idx = luaL_checkinteger(L, 2); @@ -87,13 +90,13 @@ static int nerv_float_matrix_(index)(lua_State *L) { { if (idx < 0 || idx >= self->ncol) nerv_error(L, "index must be within range [0, %d)", self->ncol); - lua_pushnumber(L, MATRIX_DATA_READ(self->data.f, idx)); + lua_pushnumber(L, MATRIX_DATA_READ(MATRIX_ELEM_PTR(self), idx)); } else { if (idx < 0 || idx >= self->nrow) nerv_error(L, "index must be within range [0, %d)", self->nrow); - luaT_pushudata(L, nerv_float_matrix_(getrow)(self, idx), nerv_float_matrix_(tname)); + luaT_pushudata(L, nerv_matrix_(getrow)(self, idx), nerv_matrix_(tname)); } lua_pushboolean(L, 1); return 2; @@ -105,33 +108,33 @@ static int nerv_float_matrix_(index)(lua_State *L) { } } -static int nerv_float_matrix_(ncol)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_float_matrix_(tname)); +static int nerv_matrix_(ncol)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); lua_pushinteger(L, self->ncol); return 1; } -static int nerv_float_matrix_(nrow)(lua_State *L) { - Matrix *self = luaT_checkudata(L, 1, nerv_float_matrix_(tname)); +static int nerv_matrix_(nrow)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); lua_pushinteger(L, self->nrow); return 1; } -static const luaL_Reg nerv_float_matrix_(methods)[] = { - {"get_elem", nerv_float_matrix_(get_elem)}, - {"set_elem", nerv_float_matrix_(set_elem)}, - {"ncol", nerv_float_matrix_(ncol)}, - {"nrow", nerv_float_matrix_(nrow)}, - {"__index__", nerv_float_matrix_(index)}, - {"__newindex__", nerv_float_matrix_(newindex)}, +static const luaL_Reg nerv_matrix_(methods)[] = { + {"get_elem", nerv_matrix_(get_elem)}, + {"set_elem", nerv_matrix_(set_elem)}, + {"ncol", nerv_matrix_(ncol)}, + {"nrow", nerv_matrix_(nrow)}, + {"__index__", nerv_matrix_(index)}, + {"__newindex__", nerv_matrix_(newindex)}, {NULL, NULL} }; -void nerv_float_matrix_(init)(lua_State *L) { - luaT_newmetatable(L, nerv_float_matrix_(tname), nerv_matrix_tname, - nerv_float_matrix_(new), nerv_float_matrix_(destroy), NULL); - luaL_register(L, NULL, nerv_float_matrix_(methods)); +void nerv_matrix_(init)(lua_State *L) { + luaT_newmetatable(L, nerv_matrix_(tname), nerv_matrix_tname, + nerv_matrix_(new), nerv_matrix_(destroy), NULL); + luaL_register(L, NULL, nerv_matrix_(methods)); #ifdef MATRIX_INIT MATRIX_INIT(L); #endif diff --git a/matrix/generic/matrix.h b/matrix/generic/matrix.h index 264859b..276ca5c 100644 --- a/matrix/generic/matrix.h +++ b/matrix/generic/matrix.h @@ -1,6 +1,7 @@ #ifndef NERV_GENERIC_MATRIX_H #define NERV_GENERIC_MATRIX_H +#include <stddef.h> typedef struct Matrix { size_t stride; /* size of a row */ long ncol, nrow, nmax; /* dimension of the matrix */ diff --git a/matrix/generic/mmatrix.c b/matrix/generic/mmatrix.c new file mode 100644 index 0000000..ac71c3d --- /dev/null +++ b/matrix/generic/mmatrix.c @@ -0,0 +1,41 @@ +#ifdef NERV_GENERIC_MMATRIX +#include "matrix.h" +#include "elem_type.h" +#define MATRIX_DATA_FREE(ptr) free(ptr) +#define MATRIX_DATA_ALLOC(dptr, stride, width, height) \ + host_matrix_(alloc)(dptr, stride, width, height) +#define MATRIX_DATA_STRIDE(ncol) (sizeof(float) * (ncol)) +#define MATRIX_DATA_WRITE(data, idx, val) (data[idx] = val) +#define MATRIX_DATA_READ(data, idx) (data[idx]) +#define NERV_GENERIC_MATRIX +#include "../../common.h" + +const char *nerv_matrix_(tname) = "nerv.FloatMMatrix"; + +static void host_matrix_(alloc)(float **dptr, size_t *stride, + long width, long height) { + *dptr = (float *)malloc(width * height); + *stride = width; +} + +int nerv_matrix_(get_elem)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); + int idx = luaL_checkinteger(L, 2); + if (idx < 0 || idx >= self->nmax) + nerv_error(L, "index must be within range [0, %d)", self->nmax); + lua_pushnumber(L, self->data.f[idx]); + return 1; +} + +int nerv_matrix_(set_elem)(lua_State *L) { + Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); + int idx = luaL_checkinteger(L, 2); + float v = luaL_checknumber(L, 3); + if (idx < 0 || idx >= self->nmax) + nerv_error(L, "index must be within range [0, %d)", self->nmax); + self->data.f[idx] = v; + return 0; +} + +#include "matrix.c" +#endif |