major change: use luarocks to manage project

1 files changed, 493 insertions, 0 deletions

diff --git a/nerv/matrix/generic/cumatrix.c b/nerv/matrix/generic/cumatrix.c
new file mode 100644
index 0000000..b5d1a35
--- /dev/null
+++ b/nerv/matrix/generic/cumatrix.c
@@ -0,0 +1,493 @@
+#ifdef NERV_GENERIC_CUMATRIX
+#include "matrix.h"
+#include "elem_type.h"
+
+#define MATRIX_DATA_FREE(L, ptr) cuda_matrix_(free)(L, ptr)
+#define MATRIX_DATA_ALLOC(L, dptr, stride, width, height) \
+                            cuda_matrix_(alloc)(L, dptr, stride, width, height)
+#define MATRIX_DATA_WRITE(L, data, idx, val) cuda_matrix_(write)(L, data, idx, val)
+#define MATRIX_DATA_READ(L, data, idx) cuda_matrix_(read)(L, data, idx)
+#define MATRIX_INIT(L) cuda_matrix_(init)(L)
+#define MATRIX_BASE_TNAME nerv_matrix_cuda_tname
+#define NERV_GENERIC_MATRIX
+#define NERV_GENERIC_CUKERNEL
+#include "../../common.h"
+#include "../cukernel.h"
+#include "../cuda_helper.h"
+
+Matrix *nerv_matrix_(new_)(lua_State *L, long nrow, long ncol);
+void nerv_matrix_(data_free)(lua_State *L, Matrix *self);
+
+static void nerv_matrix_(add_)(lua_State *L, const Matrix *a, const Matrix *b,
+                                const Matrix *c,
+                                MATRIX_ELEM alpha, MATRIX_ELEM beta) {
+    PROFILE_START
+    CUBLAS_SAFE_SYNC_CALL(
+            NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_N, CUBLAS_OP_N,
+                a->ncol, a->nrow,
+                &alpha,
+                MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM),
+                &beta,
+                MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM),
+                MATRIX_ELEM_PTR(c), c->stride / sizeof(MATRIX_ELEM)));
+    PROFILE_STOP
+}
+
+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);
+    MATRIX_ELEM beta = luaL_checknumber(L, 5);
+    CHECK_SAME_DIMENSION(a, b);
+    CHECK_SAME_DIMENSION(a, c);
+    nerv_matrix_(add_)(L, a, b, c, alpha, beta);
+    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; */
+    /* Because matrix in Nerv is row-major, here b comes first */
+    PROFILE_START
+    CUBLAS_SAFE_SYNC_CALL(
+            NERV_CUBLAS_(gemm)(cublas_handle, tb, ta,
+                bn, am, bm,
+                &alpha,
+                MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM),
+                MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM),
+                &beta,
+                MATRIX_ELEM_PTR(c), c->stride / sizeof(MATRIX_ELEM)));
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(create)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = nerv_matrix_(new_)(L, 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 = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    CHECK_SAME_DIMENSION(a, b);
+    PROFILE_START
+    cudak_(cuda_sigmoid)(b, a);
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(sigmoid_grad)(lua_State *L) {
+    Matrix *nerr = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *err = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    Matrix *output = luaT_checkudata(L, 3, nerv_matrix_(tname));
+    CHECK_SAME_DIMENSION(nerr, err);
+    CHECK_SAME_DIMENSION(nerr, output);
+    PROFILE_START
+    cudak_(cuda_sigmoid_grad)(output, err, nerr);
+    PROFILE_STOP
+    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, *max_idx;
+    Matrix *dno;
+    CHECK_SAME_DIMENSION(a, b);
+    max = nerv_matrix_(new_)(L, a->nrow, 1);
+    max_idx = nerv_matrix_(new_)(L, a->nrow, 1);
+    dno = nerv_matrix_(new_)(L, a->nrow, 1);
+    PROFILE_START
+    cudak_(cuda_rowmax_idx)(a, max, max_idx);
+    cudak_(cuda_softmax_denominator)(a, max, dno);
+    cudak_(cuda_softmax_final)(a, max, dno, b);
+    PROFILE_STOP
+    nerv_matrix_(data_free)(L, max);
+    nerv_matrix_(data_free)(L, dno);
+    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;
+}
+
+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;
+}
+
+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));
+    Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    double beta = luaL_checknumber(L, 3);
+    if (a->ncol != b->ncol)
+        nerv_error(L, "the number of columns is not the same");
+    if (a->nrow != 1)
+        nerv_error(L, "a row vector is expected");
+    PROFILE_START
+    cudak_(cuda_add_row)(a, b, beta);
+    PROFILE_STOP
+    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;
+}
+
+static int nerv_matrix_(copy_fromd)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    int nargs = lua_gettop(L);
+    int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0;
+    int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow;
+    int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0;
+    if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow &&
+            a_begin + b_end - b_begin <= a->nrow))
+        nerv_error(L, "invalid copy interval");
+    if (a->ncol != b->ncol)
+        nerv_error(L, "matrices should be of the same dimension");
+    PROFILE_START
+    CUDA_SAFE_SYNC_CALL(
+            cudaMemcpy2D(MATRIX_ROW_PTR(a, a_begin), a->stride,
+                MATRIX_ROW_PTR(b, b_begin), b->stride,
+                sizeof(MATRIX_ELEM) * b->ncol, b_end - b_begin,
+                cudaMemcpyDeviceToDevice));
+    PROFILE_STOP
+    return 0;
+}
+
+extern const char *MATRIX_CUMATRIX_HOST_TNAME;
+static int nerv_matrix_(copy_fromh)(lua_State *L) { 
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
+    int nargs = lua_gettop(L);
+    int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0;
+    int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow;
+    int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0;
+    if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow &&
+            a_begin + b_end - b_begin <= a->nrow))
+        nerv_error(L, "invalid copy interval");
+    if (a->ncol != b->ncol)
+        nerv_error(L, "matrices should be of the same dimension");
+    PROFILE_START
+    CUDA_SAFE_SYNC_CALL(
+            cudaMemcpy2D(MATRIX_ROW_PTR(a, a_begin), a->stride,
+                MATRIX_ROW_PTR(b, b_begin), b->stride,
+                sizeof(MATRIX_ELEM) * b->ncol, b_end - b_begin,
+                cudaMemcpyHostToDevice));
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(copy_toh)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
+    int nargs = lua_gettop(L);
+    int a_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0;
+    int a_end = nargs > 3 ? luaL_checkinteger(L, 4) : a->nrow;
+    int b_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0;
+    if (!(0 <= a_begin && a_begin < a_end && a_end <= a->nrow &&
+            b_begin + a_end - a_begin <= b->nrow))
+        nerv_error(L, "invalid copy interval");
+    if (b->ncol != a->ncol)
+        nerv_error(L, "matrices should be of the same dimension");
+    PROFILE_START
+    CUDA_SAFE_SYNC_CALL(
+            cudaMemcpy2D(MATRIX_ROW_PTR(b, b_begin), b->stride,
+                MATRIX_ROW_PTR(a, a_begin), a->stride,
+                sizeof(MATRIX_ELEM) * a->ncol, a_end - a_begin,
+                cudaMemcpyDeviceToHost));
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(trans)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = nerv_matrix_(new_)(L, a->ncol, a->nrow);
+    MATRIX_ELEM alpha = 1, beta = 0;
+    /* FIXME: possible memory leak when lua error is raised */
+    PROFILE_START
+    CUBLAS_SAFE_SYNC_CALL(
+            NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_T, CUBLAS_OP_T,
+                a->nrow, a->ncol,
+                &alpha,
+                MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM),
+                &beta,
+                MATRIX_ELEM_PTR(a), a->stride / sizeof(MATRIX_ELEM),
+                MATRIX_ELEM_PTR(b), b->stride / sizeof(MATRIX_ELEM)));
+    PROFILE_STOP
+    luaT_pushudata(L, b, nerv_matrix_(tname));
+    return 1;
+}
+
+static int nerv_matrix_(mul_elem)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname));
+    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;
+}
+
+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;
+}
+
+static int nerv_matrix_(decompress)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b;
+    int orig_col = luaL_checkinteger(L, 2);
+    if (a->ncol != 1)
+        nerv_error(L, "the compressed matrix must be a column vector");
+    b = nerv_matrix_(new_)(L, a->nrow, orig_col);
+    PROFILE_START
+    cudak_(cuda_fill)(b, 0.0);
+    cudak_(cuda_decompress)(a, b);
+    PROFILE_STOP
+    luaT_pushudata(L, b, nerv_matrix_(tname));
+    return 1;
+}
+
+extern const char *nerv_matrix_host_int_tname;
+static int nerv_matrix_(copy_rows_fromh_by_idx)(lua_State *L) {
+    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;
+    if (idx->nrow != 1)
+        nerv_error(L, "index should be a vector");
+    if (a->ncol != b->ncol)
+        nerv_error(L, "source/destination dimension mismatch");
+    cudaStream_t *streams = (cudaStream_t*)malloc(sizeof(cudaStream_t) * nrow);
+    for (i = 0; i < nrow; i++)
+    {
+        int src_row = idx_ptr[b_begin + i];
+        if (!(0 <= src_row && src_row < b->nrow))
+            nerv_error(L, "invalid index");
+        CUDA_SAFE_CALL(cudaStreamCreate(streams + i));
+        CUDA_SAFE_CALL(cudaMemcpyAsync(MATRIX_ROW_PTR(a, i),
+                    MATRIX_ROW_PTR(b, src_row),
+                    b->stride,
+                    cudaMemcpyHostToDevice, streams[i]));
+    }
+    for (i = 0; i < nrow; i++)
+    {
+        CUDA_SAFE_CALL(cudaStreamSynchronize(streams[i]));
+        CUDA_SAFE_CALL(cudaStreamDestroy(streams[i]));
+    }
+    free(streams);
+    return 0;
+}
+
+static int nerv_matrix_(expand_frm)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    int context = luaL_checkinteger(L, 3);
+    if (a->nrow != b->nrow)
+        nerv_error(L, "mismatching number of frames");
+    if (a->ncol != b->ncol * (context * 2 + 1))
+        nerv_error(L, "the width should be 2 * context + 1");
+    PROFILE_START
+    cudak_(cuda_expand_frm)(b, a, context);
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(rearrange_frm)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    int step = luaL_checkinteger(L, 3);
+    CHECK_SAME_DIMENSION(a, b);
+    if (b->ncol % step)
+        nerv_error(L, "the dimension of columns is not divisible by step");
+    PROFILE_START
+    cudak_(cuda_rearrange_frm)(b, a, step);
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(scale_rows_by_col)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    if (a->nrow != b->nrow)
+        nerv_error(L, "the number of rows is not the same");
+    if (b->ncol != 1)
+        nerv_error(L, "a column vector is expected");
+    PROFILE_START
+    cudak_(cuda_scale_rows_by_col)(b, a);
+    PROFILE_STOP
+    return 0;
+}
+
+static int nerv_matrix_(scale_rows_by_row)(lua_State *L) {
+    Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+    Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+    if (a->ncol != b->ncol)
+        nerv_error(L, "the number of columns is not the same");
+    if (b->nrow != 1)
+        nerv_error(L, "a row vector is expected");
+    PROFILE_START
+    cudak_(cuda_scale_rows_by_row)(b, a);
+    PROFILE_STOP
+    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 */
+    {"copy_fromh", nerv_matrix_(copy_fromh)},
+    {"copy_fromd", nerv_matrix_(copy_fromd)},
+    {"copy_toh", nerv_matrix_(copy_toh)},
+    {"add", nerv_matrix_(add)},
+    {"mul", nerv_matrix_(mul)},
+    {"add_row", nerv_matrix_(add_row)},
+    {"fill", nerv_matrix_(fill)},
+    {"sigmoid", nerv_matrix_(sigmoid)},
+    {"sigmoid_grad", nerv_matrix_(sigmoid_grad)},
+    {"softmax", nerv_matrix_(softmax)},
+    {"mul_elem", nerv_matrix_(mul_elem)},
+    {"log_elem", nerv_matrix_(log_elem)},
+    {"copy_rows_fromh_by_idx", nerv_matrix_(copy_rows_fromh_by_idx)},
+    {"expand_frm", nerv_matrix_(expand_frm)},
+    {"rearrange_frm", nerv_matrix_(rearrange_frm)},
+    {"scale_rows_by_row", nerv_matrix_(scale_rows_by_row)},
+    {"scale_rows_by_col", nerv_matrix_(scale_rows_by_col)},
+    {NULL, NULL}
+};
+
+static void cuda_matrix_(init)(lua_State *L) {
+    luaN_append_methods(L, nerv_matrix_(extra_methods));
+}
+
+static void cuda_matrix_(free)(lua_State *L, MATRIX_ELEM *ptr) {
+    CUDA_SAFE_SYNC_CALL(cudaFree(ptr));
+}
+
+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,
+                                        int idx) {
+    MATRIX_ELEM res;
+    CUDA_SAFE_SYNC_CALL(cudaMemcpy(&res, data + idx,
+                sizeof(MATRIX_ELEM), cudaMemcpyDeviceToHost));
+    return res;
+}
+
+static void cuda_matrix_(write)(lua_State *L, MATRIX_ELEM *data,
+                                int idx, MATRIX_ELEM val) {
+    CUDA_SAFE_SYNC_CALL(cudaMemcpy(data + idx, &val,
+                sizeof(MATRIX_ELEM), cudaMemcpyHostToDevice));
+}
+
+int nerv_matrix_(get_elem)(lua_State *L) {
+    return nerv_error_method_not_implemented(L);
+}
+
+int nerv_matrix_(set_elem)(lua_State *L) {
+    return nerv_error_method_not_implemented(L);
+}
+
+#include "matrix.c"
+#endif