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[Perf][Kernel] Fused SiLU+Mul+Quant kernel for NVFP4 cutlass_moe (#31832)

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Signed-off-by: mgoin <mgoin64@gmail.com>
Signed-off-by: Michael Goin <mgoin64@gmail.com>
This commit is contained in:
Michael Goin
2026-01-09 09:40:33 -05:00
committed by GitHub
parent 8e27663b6a
commit 34cd32fe30
8 changed files with 278 additions and 95 deletions
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9
vllm/model_executor/layers/fused_moe/cutlass_moe.py
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@@ -549,7 +549,8 @@ def run_cutlass_moe_fp4(
num_topk,
)
c1 = _resize_cache(workspace13, (m * topk, n * 2))
c2 = _resize_cache(workspace2, (m * topk, n))
# Note: c2 workspace is no longer needed since SiLU is fused with quantization.
# c3 reuses workspace13 after c1 is consumed.
c3 = _resize_cache(workspace13, (m * topk, k))
ops.cutlass_fp4_moe_mm(
c1,
@@ -563,9 +564,9 @@ def run_cutlass_moe_fp4(
blockscale_offsets[:-1],
)
del rep_a_fp4, rep_a_blockscale
torch.ops._C.silu_and_mul(c2, c1)
int_fp4, int_blockscale = ops.scaled_fp4_experts_quant(
c2, a2_gscale, expert_offsets, blockscale_offsets, num_topk
# Fused SiLU+Mul+NVFP4 quantization
int_fp4, int_blockscale = ops.silu_and_mul_scaled_fp4_experts_quant(
c1, a2_gscale, expert_offsets, blockscale_offsets, num_topk
)
ops.cutlass_fp4_moe_mm(