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Use Cache Hinting for fused_moe kernel (#15511)

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Wes 2025-03-26 17:21:34 -06:00 committed by GitHub
parent 9d119a86ae
commit 7a888271f5
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1 changed files with 12 additions and 4 deletions
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16
vllm/model_executor/layers/fused_moe/fused_moe.py
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@ -189,7 +189,11 @@ def fused_moe_kernel_gptq_awq(
mask=token_mask[:, None] & mask=token_mask[:, None] &
(offs_k[None, :] < K - k * BLOCK_SIZE_K), (offs_k[None, :] < K - k * BLOCK_SIZE_K),
other=0.0) other=0.0)
b = tl.load(b_ptrs) b = tl.load(
b_ptrs,
cache_modifier=".cg",
eviction_policy="evict_last",
)
if use_int4_w4a16: if use_int4_w4a16:
b = (b >> b_shifter) & 0xF b = (b >> b_shifter) & 0xF
@ -391,9 +395,13 @@ def fused_moe_kernel(
mask=token_mask[:, None] & mask=token_mask[:, None] &
(offs_k[None, :] < K - k * BLOCK_SIZE_K), (offs_k[None, :] < K - k * BLOCK_SIZE_K),
other=0.0) other=0.0)
b = tl.load(b_ptrs, b = tl.load(
mask=offs_k[:, None] < K - k * BLOCK_SIZE_K, b_ptrs,
other=0.0) mask=offs_k[:, None] < K - k * BLOCK_SIZE_K,
other=0.0,
cache_modifier=".cg",
eviction_policy="evict_last",
)
# We accumulate along the K dimension. # We accumulate along the K dimension.
if use_int8_w8a16: if use_int8_w8a16:
accumulator = tl.dot(a, b.to(compute_type), acc=accumulator) accumulator = tl.dot(a, b.to(compute_type), acc=accumulator)