char-fork/llama.cpp

git clone https://git.t4t.associates/char-fork/llama.cpp

Johannes Gäßlerllama/ggml: add LLM training support (#10544)10d2af0ea

char/aliceai-t5-moe
brancheschar/aliceai-t5-moeall refs →
2.4 KiB61 linesraw
1#include "acc.cuh"
2
3static __global__ void acc_f32(const float * x, const float * y, float * dst, const int64_t ne,
4        const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t ne13,
5        const int64_t s11, const int64_t s12, const int64_t s13, const int64_t offset) {
6    const int64_t i = blockDim.x * blockIdx.x + threadIdx.x;
7
8    if (i >= ne) {
9        return;
10    }
11
12    int64_t src1_idx = i - offset;
13
14    int64_t tmp = src1_idx;
15    const int64_t i13 = tmp / s13;
16    tmp -= i13 * s13;
17    const int64_t i12 = tmp / s12;
18    tmp -= i12 * s12;
19    const int64_t i11 = tmp / s11;
20    tmp -= i11 * s11;
21    const int64_t i10 = tmp;
22
23    float val = x[i];
24    if (src1_idx >= 0 && i10 < ne10 && i11 < ne11 && i12 < ne12 && i13 < ne13) {
25        val += y[((i13*ne12 + i12) * ne11 + i11) * ne10 + i10];
26    }
27    dst[i] = val;
28}
29
30static void acc_f32_cuda(const float * x, const float * y, float * dst, const int64_t n_elements,
31        const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t ne13,
32        const int64_t s1, const int64_t s2, const int64_t s3, const int64_t offset, cudaStream_t stream) {
33    const int num_blocks = (n_elements + CUDA_ACC_BLOCK_SIZE - 1) / CUDA_ACC_BLOCK_SIZE;
34    acc_f32<<<num_blocks, CUDA_ACC_BLOCK_SIZE, 0, stream>>>(x, y, dst, n_elements, ne10, ne11, ne12, ne13, s1, s2, s3, offset);
35}
36
37void ggml_cuda_op_acc(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
38    const ggml_tensor * src0 = dst->src[0];
39    const ggml_tensor * src1 = dst->src[1];
40
41    const float * src0_d = (const float *) src0->data;
42    const float * src1_d = (const float *) src1->data;
43    float       * dst_d  = (float       *)  dst->data;
44
45    cudaStream_t stream = ctx.stream();
46
47    GGML_ASSERT(src0->type == GGML_TYPE_F32);
48    GGML_ASSERT(src1->type == GGML_TYPE_F32);
49    GGML_ASSERT( dst->type == GGML_TYPE_F32);
50
51    GGML_ASSERT(ggml_is_contiguous(src1));
52    GGML_ASSERT(dst->nb[0] == ggml_element_size(dst));
53    GGML_ASSERT(ggml_is_contiguously_allocated(dst));
54
55    const int64_t s1     = dst->op_params[0] / sizeof(float);
56    const int64_t s2     = dst->op_params[1] / sizeof(float);
57    const int64_t s3     = dst->op_params[2] / sizeof(float);
58    const int64_t offset = dst->op_params[3] / sizeof(float);
59
60    acc_f32_cuda(src0_d, src1_d, dst_d, ggml_nelements(dst), src1->ne[0], src1->ne[1], src1->ne[2], src1->ne[3], s1, s2, s3, offset, stream);
61}