[ROCm][Perf] Enable torch.compile / Inductor fusion passes on GLM-4 MTP draft

[omirosh]

Purpose

Glm4MoeMTP is not decorated with @support_torch_compile. As a result, the MTP draft forward executes as eager Python and misses every Inductor fusion pass that the target forward enjoys - most notably the AITER allreduce + RMSNorm fusion, RMSNorm + quant fusion, and silu+mul+fp8-quant fusion.

Adding the decorator brings MTP behaviour in line with the canonical DeepSeekMTP pattern (vllm/model_executor/models/deepseek_mtp.py, L185) and makes the draft eligible for the same compile-time fusions as the target.

Changes

Single-file, two-line wiring in vllm/model_executor/models/glm4_moe_mtp.py, mirroring deepseek_mtp.py:

• Add from vllm.compilation.decorators import support_torch_compile.
• Decorate the top-level Glm4MoeMTP class with @support_torch_compile.

No changes to the forward signature, the loader, or Glm4MoeMultiTokenPredictor. dynamic_arg_dims is inferred from the existing forward annotations (the four Tensor | None / IntermediateTensors | None args become dim-0 dynamic), exactly as for DeepSeekMTP.

Test Plan

• Model: zai-org/GLM-4.7-FP8
• Hardware: 1x MI355X node, TP=4 + EP
• AITER: >= v0.1.13.post1 ([ROCm] Upgrade AITER to v0.1.13.post1 #44265)
• Accuracy: lm_eval --tasks gsm8k --num_fewshot 5
• Throughput: vllm bench serve --dataset-name random sweep over (ISL, OSL, MC) in {1000/100, 5000/500, 10000/1000} x {4, 16, 64}
• Two arms: (A) Glm4MoeMTP without @support_torch_compile (baseline / eager draft), (B) with the decorator (this PR). All other knobs identical.

Server invocation (MTP=2 spec tokens, attention-backend ROCM_AITER_UNIFIED_ATTN)

VLLM_ROCM_USE_AITER=1 \
VLLM_ROCM_USE_AITER_MOE=1 \
VLLM_ROCM_SHUFFLE_KV_CACHE_LAYOUT=1 \
VLLM_ROCM_USE_AITER_RMSNORM=0 \
VLLM_ROCM_QUICK_REDUCE_QUANTIZATION=INT4 \
vllm serve zai-org/GLM-4.7-FP8 \
  --tensor-parallel-size 4 --enable-expert-parallel --trust-remote-code \
  --no-enable-prefix-caching --async-scheduling \
  --max-num-batched-tokens 32768 --max-model-len 131072 \
  --attention-backend ROCM_AITER_UNIFIED_ATTN \
  --kv-cache-dtype fp8 --gpu-memory-utilization 0.95 \
  --performance-mode throughput \
  --speculative-config '{"method":"mtp","num_speculative_tokens":2,"attention_backend":"ROCM_AITER_UNIFIED_ATTN"}' \
  --reasoning-parser glm45 --tool-call-parser glm47 --enable-auto-tool-choice

Test Result

Accuracy (gsm8k, 5-shot, exact_match), MTP, num_speculative_tokens=2

compile_mtp	flexible-extract	strict-match
off (A)	0.9128 +/- 0.0078	0.9014 +/- 0.0082
on (B)	0.9121 +/- 0.0078	0.8999 +/- 0.0083

All deltas inside 1 sigma. No accuracy regression.

Throughput (B = compile, A = no-compile)

ISL	OSL	MC	TPOT mean (ms) (delta%)	TPOT p99 (ms) (delta%)	Output tok/s (delta%)	Total tok/s (delta%)
1000	100	4	21.69 -> 22.21 (+2.4%)	27.80 -> 27.67 (-0.5%)	169.9 -> 161.0 (-5.3%)	1869.3 -> 1770.9 (-5.3%)
1000	100	16	31.37 -> 30.61 (-2.4%)	40.00 -> 40.39 (+1.0%)	454.0 -> 466.3 (+2.7%)	4994.3 -> 5129.4 (+2.7%)
1000	100	64	56.91 -> 55.84 (-1.9%)	72.79 -> 70.69 (-2.9%)	969.3 -> 993.7 (+2.5%)	10662.4 -> 10930.3 (+2.5%)
5000	500	4	17.85 -> 17.71 (-0.8%)	26.56 -> 26.06 (-1.9%)	208.1 -> 211.2 (+1.5%)	2289.3 -> 2322.9 (+1.5%)
5000	500	16	28.52 -> 26.81 (-6.0%)	59.49 -> 40.82 (-31.4%)	482.3 -> 536.1 (+11.2%)	5305.3 -> 5897.2 (+11.2%)
5000	500	64	58.14 -> 57.18 (-1.6%)	79.88 -> 79.77 (-0.1%)	974.1 -> 984.7 (+1.1%)	10714.6 -> 10832.1 (+1.1%)
10000	1000	4	16.79 -> 15.77 (-6.1%)	27.31 -> 22.49 (-17.7%)	224.8 -> 231.4 (+2.9%)	2472.5 -> 2545.2 (+2.9%)
10000	1000	16	24.43 -> 24.50 (+0.3%)	37.74 -> 41.65 (+10.4%)	582.1 -> 573.3 (-1.5%)	6403.5 -> 6306.6 (-1.5%)
10000	1000	64	60.59 -> 58.17 (-4.0%)	84.38 -> 85.87 (+1.8%)	933.6 -> 974.2 (+4.3%)	10269.8 -> 10716.5 (+4.3%)

Aggregate (geomean B/A over 9 cells):

Metric	direction	geomean	delta%
Output tok/s	higher better	1.021	+2.1%
Mean TPOT	lower better	0.977	-2.3%
P99 TPOT	lower better	0.946	-5.4%
Mean TTFT	lower better	0.915	-8.5%

Spec-decode acceptance (averaged over the 9-cell sweep)

compile_mtp	Mean acceptance length	Avg draft acceptance rate
off (A)	1.402	20.08%
on (B)	1.419	20.95%

Acceptance is unchanged within noise -- confirming the decorator does not affect spec-decoding semantics, only the kernel composition of the draft forward.

Verdict

• Real, modest, accuracy-neutral win -- +2.1% output throughput, -2.3% mean TPOT, -5.4% P99 TPOT, -8.5% mean TTFT (geomean across 9 cells). 7 of 9 cells improve on throughput.
• No accuracy regression (gsm8k deltas inside 1 sigma).

In addition to the immediate uplift, this decorator unblocks subsequent draft-side Inductor fusion work (e.g. cherry-picking vLLM #42749 + #43676 to add the four-op qk-norm + RoPE + KV-cache + quant fusion onto the MTP path).

[mergify]

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