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llama.cpp
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Fix data race in CUDA's "cpy" kernel (influences GGML's DUP, CONT operations). (#20507) 

* Fix datarace in CUDA's "cpy" kernel.

* Remove extra barrier by using more of shared memory.
This commit is contained in:
Rail Chabdarov 2026-03-14 06:19:44 +01:00 committed by GitHub
parent 3b439504ba
commit 5a32a9b8a5
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GPG Key ID: B5690EEEBB952194
1 changed files with 6 additions and 3 deletions
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9
ggml/src/ggml-cuda/cpy.cu
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@ -56,7 +56,8 @@ static __global__ void cpy_scalar_transpose(const char * cx, char * cdst, const
const int tx = blockIdx.y * CUDA_CPY_TILE_DIM_2D + threadIdx.x; // transpose block offset
const int ty = blockIdx.x * CUDA_CPY_TILE_DIM_2D + threadIdx.y;
__shared__ float tile[CUDA_CPY_TILE_DIM_2D][CUDA_CPY_TILE_DIM_2D+1];
__shared__ float tile[2][CUDA_CPY_TILE_DIM_2D][CUDA_CPY_TILE_DIM_2D+1];
int cur_tile_buf = 0;
#pragma unroll
for (int i = 0; i < CUDA_CPY_BLOCK_NM; ++i) {
@ -70,7 +71,7 @@ static __global__ void cpy_scalar_transpose(const char * cx, char * cdst, const
if(x < ne01 && y + j < ne00){
const int row = threadIdx.y+j;
const int col = threadIdx.x * sizeof(float)/sizeof(T);
T *tile2 = reinterpret_cast<T*>(tile[row]);
T *tile2 = reinterpret_cast<T*>(tile[cur_tile_buf][row]);
tile2[col] = src[imat*n + (y+j)*ne01 + x];
}
}
@ -81,10 +82,12 @@ static __global__ void cpy_scalar_transpose(const char * cx, char * cdst, const
for (int j = 0; j < CUDA_CPY_TILE_DIM_2D; j += CUDA_CPY_BLOCK_ROWS) {
if (ty + j < ne01 && tx < ne00) {
const int col = (threadIdx.y+j)*sizeof(float)/sizeof(T);
const T *tile2 = reinterpret_cast<const T*>(tile[threadIdx.x]);
const T *tile2 = reinterpret_cast<const T*>(tile[cur_tile_buf][threadIdx.x]);
dst[imat*n + (ty+j)*ne00 + tx] = tile2[col];
}
}
cur_tile_buf = (cur_tile_buf + 1) % 2;
}
GGML_UNUSED_VARS(ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11,