cuda : support non-pow-2 number of experts
This commit is contained in:
parent
8c2f7b8169
commit
4531b029ee
1 changed files with 44 additions and 16 deletions
|
@ -8,32 +8,41 @@ static inline __device__ void ggml_cuda_swap(T & a, T & b) {
|
||||||
}
|
}
|
||||||
|
|
||||||
template<ggml_sort_order order>
|
template<ggml_sort_order order>
|
||||||
static __global__ void k_argsort_f32_i32(const float * x, int * dst, const int ncols) {
|
static __global__ void k_argsort_f32_i32(const float * x, int * dst, int * dst_pad, const int ncols, int ncols_pad) {
|
||||||
// bitonic sort
|
// bitonic sort
|
||||||
int col = threadIdx.x;
|
int col = threadIdx.x;
|
||||||
int row = blockIdx.y;
|
int row = blockIdx.y;
|
||||||
|
|
||||||
if (col >= ncols) return;
|
if (col >= ncols_pad) {
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
const float * x_row = x + row * ncols;
|
const float * x_row = x + row * ncols;
|
||||||
int * dst_row = dst + row * ncols;
|
int * dst_row = dst_pad + row * ncols_pad;
|
||||||
|
|
||||||
// initialize indices
|
// initialize indices
|
||||||
if (col < ncols) {
|
dst_row[col] = col;
|
||||||
dst_row[col] = col;
|
|
||||||
}
|
|
||||||
__syncthreads();
|
__syncthreads();
|
||||||
|
|
||||||
for (int k = 2; k <= ncols; k *= 2) {
|
for (int k = 2; k <= ncols_pad; k *= 2) {
|
||||||
for (int j = k / 2; j > 0; j /= 2) {
|
for (int j = k / 2; j > 0; j /= 2) {
|
||||||
int ixj = col ^ j;
|
int ixj = col ^ j;
|
||||||
if (ixj > col) {
|
if (ixj > col) {
|
||||||
if ((col & k) == 0) {
|
if ((col & k) == 0) {
|
||||||
if (order == GGML_SORT_ORDER_ASC ? x_row[dst_row[col]] > x_row[dst_row[ixj]] : x_row[dst_row[col]] < x_row[dst_row[ixj]]) {
|
if (dst_row[col] >= ncols ||
|
||||||
|
(dst_row[ixj] < ncols && (order == GGML_SORT_ORDER_ASC ?
|
||||||
|
x_row[dst_row[col]] > x_row[dst_row[ixj]] :
|
||||||
|
x_row[dst_row[col]] < x_row[dst_row[ixj]]))
|
||||||
|
) {
|
||||||
ggml_cuda_swap(dst_row[col], dst_row[ixj]);
|
ggml_cuda_swap(dst_row[col], dst_row[ixj]);
|
||||||
}
|
}
|
||||||
} else {
|
} else {
|
||||||
if (order == GGML_SORT_ORDER_ASC ? x_row[dst_row[col]] < x_row[dst_row[ixj]] : x_row[dst_row[col]] > x_row[dst_row[ixj]]) {
|
if (dst_row[ixj] >= ncols ||
|
||||||
|
(dst_row[col] < ncols && (order == GGML_SORT_ORDER_ASC ?
|
||||||
|
x_row[dst_row[col]] < x_row[dst_row[ixj]] :
|
||||||
|
x_row[dst_row[col]] > x_row[dst_row[ixj]]))
|
||||||
|
) {
|
||||||
ggml_cuda_swap(dst_row[col], dst_row[ixj]);
|
ggml_cuda_swap(dst_row[col], dst_row[ixj]);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
@ -41,18 +50,37 @@ static __global__ void k_argsort_f32_i32(const float * x, int * dst, const int n
|
||||||
__syncthreads();
|
__syncthreads();
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// copy the result to dst without the padding
|
||||||
|
if (col < ncols) {
|
||||||
|
dst[row * ncols + col] = dst_row[col];
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
static void argsort_f32_i32_cuda(const float * x, int * dst, const int ncols, const int nrows, ggml_sort_order order, cudaStream_t stream) {
|
static int next_power_of_2(int x) {
|
||||||
// bitonic sort requires ncols to be power of 2
|
int n = 1;
|
||||||
GGML_ASSERT((ncols & (ncols - 1)) == 0);
|
while (n < x) {
|
||||||
|
n *= 2;
|
||||||
|
}
|
||||||
|
return n;
|
||||||
|
}
|
||||||
|
|
||||||
const dim3 block_dims(ncols, 1, 1);
|
static void argsort_f32_i32_cuda(ggml_backend_cuda_context & ctx, const float * x, int * dst, const int ncols, const int nrows, ggml_sort_order order, cudaStream_t stream) {
|
||||||
|
// bitonic sort requires ncols to be power of 2
|
||||||
|
const int ncols_pad = next_power_of_2(ncols);
|
||||||
|
|
||||||
|
ggml_cuda_pool_alloc<int> dst_padded_alloc;
|
||||||
|
int * dst_padded = dst;
|
||||||
|
if (ncols_pad > ncols) {
|
||||||
|
dst_padded = dst_padded_alloc.alloc(ctx.pool(), nrows * ncols_pad);
|
||||||
|
}
|
||||||
|
|
||||||
|
const dim3 block_dims(ncols_pad, 1, 1);
|
||||||
const dim3 block_nums(1, nrows, 1);
|
const dim3 block_nums(1, nrows, 1);
|
||||||
if (order == GGML_SORT_ORDER_ASC) {
|
if (order == GGML_SORT_ORDER_ASC) {
|
||||||
k_argsort_f32_i32<GGML_SORT_ORDER_ASC><<<block_nums, block_dims, 0, stream>>>(x, dst, ncols);
|
k_argsort_f32_i32<GGML_SORT_ORDER_ASC><<<block_nums, block_dims, 0, stream>>>(x, dst, dst_padded, ncols, ncols_pad);
|
||||||
} else if (order == GGML_SORT_ORDER_DESC) {
|
} else if (order == GGML_SORT_ORDER_DESC) {
|
||||||
k_argsort_f32_i32<GGML_SORT_ORDER_DESC><<<block_nums, block_dims, 0, stream>>>(x, dst, ncols);
|
k_argsort_f32_i32<GGML_SORT_ORDER_DESC><<<block_nums, block_dims, 0, stream>>>(x, dst, dst_padded, ncols, ncols_pad);
|
||||||
} else {
|
} else {
|
||||||
GGML_ASSERT(false);
|
GGML_ASSERT(false);
|
||||||
}
|
}
|
||||||
|
@ -73,5 +101,5 @@ void ggml_cuda_op_argsort(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
|
||||||
|
|
||||||
enum ggml_sort_order order = (enum ggml_sort_order) dst->op_params[0];
|
enum ggml_sort_order order = (enum ggml_sort_order) dst->op_params[0];
|
||||||
|
|
||||||
argsort_f32_i32_cuda(src0_d, (int *)dst_d, ncols, nrows, order, stream);
|
argsort_f32_i32_cuda(ctx, src0_d, (int *)dst_d, ncols, nrows, order, stream);
|
||||||
}
|
}
|
||||||
|
|
Loading…
Add table
Add a link
Reference in a new issue