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CUDA: faster non-contiguous concat (llama/10760)

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* faster uncontiguous concat

* Use a lambda to avoid code duplication

Co-authored-by: Diego Devesa <slarengh@gmail.com>

* Update ggml/src/ggml-cuda/concat.cu

* add constexpr  and static assert

---------

Co-authored-by: Diego Devesa <slarengh@gmail.com>
This commit is contained in:
a3sh 2024-12-13 02:09:50 +08:00 committed by Georgi Gerganov
parent 1193e494a9
commit abe3102cb7
1 changed files with 39 additions and 14 deletions
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53
ggml/src/ggml-cuda/concat.cu
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@ -94,7 +94,9 @@ static void concat_f32_cuda(const float * x, const float * y, float * dst, int n
}
// non-contiguous kernel (slow)
static __global__ void concat_f32_non_cont(
template <int dim>
static __global__ void __launch_bounds__(CUDA_CONCAT_BLOCK_SIZE)
concat_f32_non_cont(
const char * src0,
const char * src1,
char * dst,
@ -121,22 +123,28 @@ static __global__ void concat_f32_non_cont(
uint64_t nb0,
uint64_t nb1,
uint64_t nb2,
uint64_t nb3,
int32_t dim) {
uint64_t nb3){
static_assert(dim >= 0 && dim <= 3);
const int64_t i3 = blockIdx.z;
const int64_t i2 = blockIdx.y;
const int64_t i1 = blockIdx.x;
int64_t o[4] = {0, 0, 0, 0};
o[dim] = dim == 0 ? ne00 : (dim == 1 ? ne01 : (dim == 2 ? ne02 : ne03));
const float * x;
for (int i0 = threadIdx.x; i0 < ne0; i0 += blockDim.x) {
for (int64_t i0 = threadIdx.x; i0 < ne0; i0 += blockDim.x) {
if (i0 < ne00 && i1 < ne01 && i2 < ne02 && i3 < ne03) {
x = (const float *)(src0 + (i3 )*nb03 + (i2 )*nb02 + (i1 )*nb01 + (i0 )*nb00);
} else {
x = (const float *)(src1 + (i3 - o[3])*nb13 + (i2 - o[2])*nb12 + (i1 - o[1])*nb11 + (i0 - o[0])*nb10);
if constexpr (dim == 0) {
x = (const float *) (src1 + i3 * nb13 + i2 * nb12 + i1 * nb11 + (i0 - ne00) * nb10);
} else if constexpr (dim == 1) {
x = (const float *) (src1 + i3 * nb13 + i2 * nb12 + (i1 - ne01) * nb11 + i0 * nb10);
} else if constexpr (dim == 2) {
x = (const float *) (src1 + i3 * nb13 + (i2 - ne02) * nb12 + i1 * nb11 + i0 * nb10);
} else if constexpr (dim == 3) {
x = (const float *) (src1 + (i3 - ne03) * nb13 + i2 * nb12 + i1 * nb11 + i0 * nb10);
}
}
float * y = (float *)(dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
@ -182,15 +190,32 @@ void ggml_cuda_op_concat(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
}
} else {
dim3 grid_dim(dst->ne[1], dst->ne[2], dst->ne[3]);
concat_f32_non_cont<<<grid_dim, CUDA_CONCAT_BLOCK_SIZE, 0, stream>>>(
(const char *)src0->data,
(const char *)src1->data,
( char *)dst->data,
auto launch_kernel = [&](auto dim) {
concat_f32_non_cont<dim><<<grid_dim, CUDA_CONCAT_BLOCK_SIZE, 0, stream>>>(
(const char *) src0->data, (const char *) src1->data, (char *) dst->data,
src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3],
src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3],
src1->ne[0], src1->ne[1], src1->ne[2], src1->ne[3],
src1->nb[0], src1->nb[1], src1->nb[2], src1->nb[3],
dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], dim);
dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3]);
};
switch (dim) {
case 0:
launch_kernel(std::integral_constant<int, 0>{});
break;
case 1:
launch_kernel(std::integral_constant<int, 1>{});
break;
case 2:
launch_kernel(std::integral_constant<int, 2>{});
break;
case 3:
launch_kernel(std::integral_constant<int, 3>{});
break;
default:
GGML_ABORT("Invalid dim: %d", dim);
break;
}
}
}