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permute/unpermute kernel for moe optimization #14568

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Merged
merged 13 commits into from
May 2, 2025
Merged

permute/unpermute kernel for moe optimization #14568

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65e8abe
implement moe permute kernel
CalebDu Mar 10, 2025
45884cf
implement moe unpermute
CalebDu Mar 10, 2025
b1fd42b
update code and fix pre-commit
CalebDu Mar 10, 2025
1abc4c2
add expert_map support for moe permute
CalebDu Mar 12, 2025
4f29dc0
add expert_map support for moe unpermute
CalebDu Mar 12, 2025
42507df
fix mismatch and add more test case
CalebDu Mar 19, 2025
6960faa
support align_block_size for contiguous group gemm in deepgemm
CalebDu Mar 26, 2025
8816812
for each local valid expert,fill padding row with expert_id in `m_ind…
CalebDu Mar 27, 2025
d453aa7
add fill_invalid_expert to workaround deepgemm unsupport -1 in m_indices
CalebDu Apr 9, 2025
3db8def
update code according bnellnm's comment:
CalebDu Apr 18, 2025
c7e5830
remove arch limit in cmake and add return `token_expert_indices` in a…
CalebDu Apr 19, 2025
840cd41
fix pre-commit failed
CalebDu Apr 29, 2025
b29bacf
1. fix call FusedMoE.select_experts failed
CalebDu May 2, 2025
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14 changes: 13 additions & 1 deletion CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,6 @@ project(vllm_extensions LANGUAGES CXX)

# CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py)
set(VLLM_TARGET_DEVICE "cuda" CACHE STRING "Target device backend for vLLM")

message(STATUS "Build type: ${CMAKE_BUILD_TYPE}")
message(STATUS "Target device: ${VLLM_TARGET_DEVICE}")

Expand Down Expand Up @@ -681,6 +680,17 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
endif()
endif()

if(VLLM_GPU_LANG STREQUAL "CUDA")
set(MOE_PERMUTE_SRC
"csrc/moe/permute_unpermute_kernels/moe_permute_unpermute_kernel.cu"
"csrc/moe/moe_permute_unpermute_op.cu")

set_gencode_flags_for_srcs(
SRCS "${MARLIN_PERMUTE_SRC}"
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@tlrmchlsmth tlrmchlsmth Apr 22, 2025

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I'm a little confused by this - should it be MOE_PERMUTE_SRC?

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@CalebDu CalebDu May 2, 2025 •
edited
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this line should be removed with bnell‘s review. I'll remove it.

CUDA_ARCHS "${MOE_PERMUTE_ARCHS}")

list(APPEND VLLM_MOE_EXT_SRC "${MOE_PERMUTE_SRC}")
endif()
message(STATUS "Enabling moe extension.")
define_gpu_extension_target(
_moe_C
Expand All @@ -689,6 +699,8 @@ define_gpu_extension_target(
SOURCES ${VLLM_MOE_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR}
INCLUDE_DIRECTORIES ${CUTLASS_TOOLS_UTIL_INCLUDE_DIR}
USE_SABI 3
WITH_SOABI)

Expand Down
3 changes: 2 additions & 1 deletion benchmarks/kernels/benchmark_grouped_gemm_cutlass.py
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Expand Up @@ -90,7 +90,8 @@ def bench_run(results: list[benchmark.Measurement], model: str,

score = torch.randn((m, num_experts), device="cuda", dtype=dtype)

topk_weights, topk_ids = fused_topk(a, score, topk, renormalize=False)
topk_weights, topk_ids, token_expert_indices = fused_topk(
a, score, topk, renormalize=False)

def run_triton_moe(a: torch.Tensor, w1: torch.Tensor, w2: torch.Tensor,
topk_weights: torch.Tensor, topk_ids: torch.Tensor,
Expand Down
4 changes: 2 additions & 2 deletions benchmarks/kernels/benchmark_moe.py
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Expand Up @@ -115,8 +115,8 @@ def run():
from vllm.model_executor.layers.fused_moe import override_config
with override_config(config):
if use_deep_gemm:
topk_weights, topk_ids = fused_topk(x, input_gating, topk,
False)
topk_weights, topk_ids, token_expert_indices = fused_topk(
x, input_gating, topk, False)
return fused_experts(
x,
w1,
Expand Down
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