[ROCm] Cache fp32 upcast of static e8m0 weight scale in AITER scaled_mm - #47773
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The e8m0 weight scale is static, but `apply_block_scaled_mm` re-runs the `<<23` bit-shift upcast plus `.contiguous()` on it every decode step for every layer. On DeepSeek-V4 FP4 (MI355X) this shows up as ~3.5% GPU time in `aten::__lshift__` + `direct_copy` in profiles. Cache the fp32 upcast keyed by the weight scale's storage pointer. The per-step activation scale (As) is left untouched and is never cached. Signed-off-by: jiacao-amd <jiahui.cao@amd.com>
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…kScaledMMKernel Move the e8m0 -> fp32 upcast of the static weight scale from the per-step apply_block_scaled_mm hot path into process_weights_after_loading, where it runs once at model load. As (activation scale) remains dynamic and is still handled at call time. Signed-off-by: jiacao-amd <jiahui.cao@amd.com>
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Hi @tjtanaa @dllehr-amd can you take a look at this PR? |
AndreasKaratzas
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Hey @jiacao-amd Nice catch! I'm mostly good with the work, just a small cleanup with the imports. As an aside, have you looked at other scale shapes besides the e8m0fnu? I know the current impl didn't, but for uint8 or others we don't do anything but send it to fp32.
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@dllehr-amd Good question, I traced the quant path that can select this kernel, and the block weight scale is only registered as float8_e8m0fnu or float32. So upcast e8m0 here should be enough. |
Move _upcast_e8m0_to_fp32 and FP8BlockParams to the top-level import block and drop the redundant local replace_parameter import, addressing review feedback. Signed-off-by: jiacao-amd <jiahui.cao@amd.com>
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Thanks @jiacao-amd This looks good to me!
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Purpose
The e8m0 weight scale in the AITER block-scaled GEMM path is static, but
apply_block_scaled_mmre-runs the<<23bit-shift fp32 upcast plus.contiguous()on it every decode step, for every layer, even though thevalue never changes.
On DeepSeek-V4 FP4 (MI355X / gfx950) this shows up in profiles as ~3.5% of GPU
time split across
aten::__lshift__anddirect_copy.This PR overrides
process_weights_after_loadinginAiterFp8BlockScaledMMKernelto convert the e8m0 weight scale to fp32 once at model load time via
replace_parameter. The per-step activation scale (As) is dynamic and remainshandled in
apply_block_scaled_mmunchanged.Test Plan
__lshift__/direct_copyops disappear from the decode profile.Test Result
Throughput / latency (8× MI355X, DeepSeek-V4-Pro FP4)
8× MI355X (gfx950), TP=8 · DeepSeek-V4-Pro (FP4 MoE + FP8 attention), KV-cache fp8 · default fused AITER MoE · random ISL/OSL 1024/1024, num-prompts = 10×concurrency. Off → on = same base without / with this patch.
Performance
Note: median TTFT at c16 is dominated by request-queue scheduling noise (±38% run-to-run with no code change, confirmed via 3-pass repeatability on a warm server); TPOT and throughput are stable across repetitions.
Accuracy — gsm8k 5-shot, full 1319 samples (exact_match)