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Rollback flashmla to older version [1/2] #21430

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Merged
Fridge003 merged 1 commit into from
Mar 26, 2026
+11 −56
Merged

Rollback flashmla to older version [1/2] #21430

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58 changes: 11 additions & 47 deletions sgl-kernel/cmake/flashmla.cmake
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ include(FetchContent)
FetchContent_Declare(
repo-flashmla
GIT_REPOSITORY https://github.com/sgl-project/FlashMLA
GIT_TAG 9804b12079e4c873514d3457aa588d3ccf40da28
GIT_TAG be055fb7df0090fde45f08e9cb5b8b4c0272da73
GIT_SHALLOW OFF
)
FetchContent_Populate(repo-flashmla)
Expand Down Expand Up @@ -34,9 +34,8 @@ if(${CUDA_VERSION} VERSION_GREATER_EQUAL "13.0")
# Patch FlashMLA sources for SM103a support.
# These patches are only needed (and only valid) with CUDA 13+.

# Patch utils.h: widen IS_SM100 to cover the full SM100 family.
# Newer FlashMLA versions use csrc/utils.h.
set(FLASHMLA_UTILS_FILE "${repo-flashmla_SOURCE_DIR}/csrc/utils.h")
# Patch flashmla_utils.h: widen IS_SM100 to cover the full SM100 family
set(FLASHMLA_UTILS_FILE "${repo-flashmla_SOURCE_DIR}/csrc/flashmla_utils.h")
file(READ "${FLASHMLA_UTILS_FILE}" FLASHMLA_UTILS_CONTENT)
string(REPLACE
"#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ == 1000)
Expand All @@ -45,7 +44,7 @@ if(${CUDA_VERSION} VERSION_GREATER_EQUAL "13.0")
#define IS_SM100 1"
FLASHMLA_UTILS_CONTENT "${FLASHMLA_UTILS_CONTENT}")
file(WRITE "${FLASHMLA_UTILS_FILE}" "${FLASHMLA_UTILS_CONTENT}")
message(STATUS "Patched utils.h for SM103a support")
message(STATUS "Patched flashmla_utils.h for SM103a support")

# Patch cutlass/arch/config.h: add SM103 architecture defines.
# The new block is inserted right before the existing "// SM101 and SM101a"
Expand Down Expand Up @@ -88,61 +87,26 @@ endif()

set(FlashMLA_SOURCES
"csrc/flashmla_extension.cc"

# Compatibility shim for sgl-kernel torch.ops API.
${repo-flashmla_SOURCE_DIR}/csrc/python_api.cpp

# Decode metadata/combine kernels.
${repo-flashmla_SOURCE_DIR}/csrc/smxx/decode/get_decoding_sched_meta/get_decoding_sched_meta.cu
${repo-flashmla_SOURCE_DIR}/csrc/smxx/decode/combine/combine.cu

# sm90 dense decode.
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/dense/instantiations/fp16.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/dense/instantiations/bf16.cu

# sm90 sparse decode.
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/sparse_fp8/instantiations/model1_persistent_h64.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/sparse_fp8/instantiations/model1_persistent_h128.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/sparse_fp8/instantiations/v32_persistent_h64.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/sparse_fp8/instantiations/v32_persistent_h128.cu

# sm90 sparse prefill.
${repo-flashmla_SOURCE_DIR}/csrc/smxx/get_mla_metadata.cu
${repo-flashmla_SOURCE_DIR}/csrc/smxx/mla_combine.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/dense/splitkv_mla.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/decode/sparse_fp8/splitkv_mla.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/prefill/sparse/fwd.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/prefill/sparse/instantiations/phase1_k512.cu
${repo-flashmla_SOURCE_DIR}/csrc/sm90/prefill/sparse/instantiations/phase1_k512_topklen.cu
${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/decode/sparse_fp8/splitkv_mla.cu
${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/sm100/prefill/sparse/fwd.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
)

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}>
)
target_compile_options(flashmla_ops PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:${FLASHMLA_CUDA_FLAGS}>)
target_include_directories(flashmla_ops PRIVATE
${repo-flashmla_SOURCE_DIR}/csrc
${repo-flashmla_SOURCE_DIR}/csrc/kerutils/include
${repo-flashmla_SOURCE_DIR}/csrc/sm90
${repo-flashmla_SOURCE_DIR}/csrc/extension/sm90/dense_fp8/
${repo-flashmla_SOURCE_DIR}/csrc/cutlass/include
Expand Down
9 changes: 0 additions & 9 deletions sgl-kernel/python/sgl_kernel/flash_mla.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,9 +35,6 @@ def get_mla_metadata(
tile_scheduler_metadata: (num_sm_parts, TileSchedulerMetaDataSize), dtype torch.int32.
num_splits: (batch_size + 1), dtype torch.int32.
"""
if _flashmla_import_error is not None:
raise _IMPORT_ERROR from _flashmla_import_error

if is_fp8_kvcache and topk is None:
return torch.ops.sgl_kernel.get_mla_decoding_metadata_dense_fp8.default(
cache_seqlens,
Expand Down Expand Up @@ -89,9 +86,6 @@ def flash_mla_with_kvcache(
out: (batch_size, seq_len_q, num_heads_q, head_dim_v).
softmax_lse: (batch_size, num_heads_q, seq_len_q), torch.float32.
"""
if _flashmla_import_error is not None:
raise _IMPORT_ERROR from _flashmla_import_error

if softmax_scale is None:
softmax_scale = q.shape[-1] ** (-0.5)
if indices is not None:
Expand Down Expand Up @@ -155,9 +149,6 @@ def flash_mla_sparse_fwd(
- max_logits: [s_q, h_q], float
- lse: [s_q, h_q], float, 2-based log-sum-exp
"""
if _flashmla_import_error is not None:
raise _IMPORT_ERROR from _flashmla_import_error

results = torch.ops.sgl_kernel.sparse_prefill_fwd.default(
q, kv, indices, sm_scale, d_v
)
Expand Down
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