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fix(sgl-kernel): sm90 compile flashmla failed (#24130)

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nohup
2026-05-15 16:42:33 +08:00
committed by GitHub
parent 12408ec668
commit 34cb8e2842
2 changed files with 28 additions and 16 deletions
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sgl-kernel/cmake/flashmla.cmake
+26 -16
View File
@@ -17,6 +17,8 @@ set(FLASHMLA_CUDA_FLAGS
"-Xcudafe=--diag_suppress=177" # variable was declared but never referenced
)
set(FLASHMLA_ENABLE_SM100 OFF)
# The FlashMLA kernels only work on hopper and require CUDA 12.4 or later.
# Only build FlashMLA kernels if we are building for something compatible with
# sm90a
@@ -29,6 +31,7 @@ if(${CUDA_VERSION} VERSION_GREATER 12.8)
list(APPEND FLASHMLA_CUDA_FLAGS
"-gencode=arch=compute_100a,code=sm_100a"
)
set(FLASHMLA_ENABLE_SM100 ON)
endif()
if(${CUDA_VERSION} VERSION_GREATER_EQUAL "13.0")
# Patch FlashMLA sources for SM103a support.
@@ -113,33 +116,40 @@ set(FlashMLA_SOURCES
${repo-flashmla_SOURCE_DIR}/csrc/sm90/prefill/sparse/instantiations/phase1_k576.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/prefill/sparse/instantiations/phase1_k576_topklen.cu
# sm100 dense prefill/bwd.
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/dense/fmha_cutlass_fwd_sm100.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/dense/fmha_cutlass_bwd_sm100.cu
# sm100 sparse prefill.
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head64/instantiations/phase1_k512.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head64/instantiations/phase1_k576.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head128/instantiations/phase1_k512.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head128/instantiations/phase1_k576.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd_for_small_topk/head128/instantiations/phase1_prefill_k512.cu
# sm100 sparse decode.
${repo-flashmla_SOURCE_DIR}/csrc/sm100/decode/head64/instantiations/v32.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/decode/head64/instantiations/model1.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd_for_small_topk/head128/instantiations/phase1_decode_k512.cu
${repo-flashmla_SOURCE_DIR}/csrc/extension/sm90/dense_fp8/dense_fp8_python_api.cpp
${repo-flashmla_SOURCE_DIR}/csrc/extension/sm90/dense_fp8/flash_fwd_mla_fp8_sm90.cu
${repo-flashmla_SOURCE_DIR}/csrc/extension/sm90/dense_fp8/flash_fwd_mla_metadata.cu
)
if(FLASHMLA_ENABLE_SM100)
list(APPEND FlashMLA_SOURCES
# sm100 dense prefill/bwd.
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/dense/fmha_cutlass_fwd_sm100.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/dense/fmha_cutlass_bwd_sm100.cu
# sm100 sparse prefill.
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head64/instantiations/phase1_k512.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head64/instantiations/phase1_k576.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head128/instantiations/phase1_k512.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd/head128/instantiations/phase1_k576.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd_for_small_topk/head128/instantiations/phase1_prefill_k512.cu
# sm100 sparse decode.
${repo-flashmla_SOURCE_DIR}/csrc/sm100/decode/head64/instantiations/v32.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/decode/head64/instantiations/model1.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm100/prefill/sparse/fwd_for_small_topk/head128/instantiations/phase1_decode_k512.cu
)
endif()
Python_add_library(flashmla_ops MODULE USE_SABI ${SKBUILD_SABI_VERSION} WITH_SOABI ${FlashMLA_SOURCES})
target_compile_options(flashmla_ops PRIVATE
$<$<COMPILE_LANGUAGE:CXX>:-std=c++20>
$<$<COMPILE_LANGUAGE:CUDA>:-std=c++20>
$<$<COMPILE_LANGUAGE:CUDA>:${FLASHMLA_CUDA_FLAGS}>
)
if(FLASHMLA_ENABLE_SM100)
target_compile_definitions(flashmla_ops PRIVATE FLASHMLA_ENABLE_SM100)
endif()
target_include_directories(flashmla_ops PRIVATE
${repo-flashmla_SOURCE_DIR}/csrc
${repo-flashmla_SOURCE_DIR}/csrc/kerutils/include
sgl-kernel/csrc/flashmla_extension.cc
+2
View File
@@ -36,11 +36,13 @@ TORCH_LIBRARY_FRAGMENT(sgl_kernel, m) {
"-> Tensor[]");
m.impl("fwd_kvcache_mla", torch::kCUDA, &fwd_kvcache_mla);
#ifdef FLASHMLA_ENABLE_SM100
m.def(
"dense_prefill_fwd(Tensor workspace_buffer, Tensor q, Tensor k, Tensor v, Tensor cumulative_seqlen_q, Tensor "
"cumulative_seqlen_kv, Tensor o, Tensor lse, int mask_mode_code, float softmax_scale, int max_seqlen_q, int "
"max_seqlen_kv, bool is_varlen) -> ()");
m.impl("dense_prefill_fwd", torch::kCUDA, &FMHACutlassSM100FwdRun);
#endif
m.def("sparse_prefill_fwd(Tensor q, Tensor kv, Tensor indices, float sm_scale, int d_v) -> Tensor[]");
m.impl("sparse_prefill_fwd", torch::kCUDA, &sparse_prefill_fwd);