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CUDA: optimize FA for GQA + large batches (#12014)

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This commit is contained in:
Johannes Gäßler
2025-02-22 12:20:17 +01:00
committed by GitHub
parent 335eb04a91
commit 5fa07c2f93
32 changed files with 940 additions and 411 deletions
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4
ggml/src/ggml-cuda/fattn-tile-f32.cu
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@@ -296,14 +296,14 @@ void launch_fattn_tile_f32_64_128(ggml_backend_cuda_context & ctx, ggml_tensor *
constexpr int nwarps = 8;
constexpr size_t nbytes_shared = 0;
fattn_kernel_t fattn_kernel = flash_attn_tile_ext_f32<D, cols_per_block, nwarps, parallel_blocks, use_logit_softcap>;
launch_fattn<D, cols_per_block, parallel_blocks, -1>(ctx, dst, fattn_kernel, nwarps, nbytes_shared, true, true);
launch_fattn<D, cols_per_block, 1, parallel_blocks, -1>(ctx, dst, fattn_kernel, nwarps, nbytes_shared, true, true);
} break;
case 128: {
constexpr int D = 128;
constexpr int nwarps = 8;
constexpr size_t nbytes_shared = 0;
fattn_kernel_t fattn_kernel = flash_attn_tile_ext_f32<D, cols_per_block, nwarps, parallel_blocks, use_logit_softcap>;
launch_fattn<D, cols_per_block, parallel_blocks, -1>(ctx, dst, fattn_kernel, nwarps, nbytes_shared, true, true);
launch_fattn<D, cols_per_block, 1, parallel_blocks, -1>(ctx, dst, fattn_kernel, nwarps, nbytes_shared, true, true);
} break;
default: {
GGML_ABORT("FlashAttention without tensor cores only supports head sizes 64 and 128.");