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[ROCm] Calibrate gfx950 decode Top-K routing by rows × compressed-context - #57844
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The existing _get_aiter_top_k_kernel() gate for the C4A (k=1024) path used
a fixed max_valid_seq_len threshold of 64K against the passed sequence length.
This threshold was miscalibrated in two ways:
1. Under CUDAGraphMode.FULL the call site passes max_model_len (typically
1M tokens) instead of the live compressed length, making the condition
always true and routing every FULL-graph decode step to native regardless
of actual context length.
2. Even with the correct live length, the one-dimensional 64K threshold is
too conservative. Measured on gfx950 (MI350X): AITER is faster than
native at C32 (192 verification rows) for live compressed contexts up to
262K tokens — well above the old 64K cutoff.
Replace the single threshold with a two-dimensional (rows, live_ctx) policy
calibrated on MI350X. Native is preserved for FULL-graph replay (max_model_len
does not match any policy entry, giving the same safe outcome as before but
for the correct reason). The DSV4.1 (topk=512, k<=384 rows) early-return
introduced upstream is preserved unchanged.
Calibration (gfx950, nightly-eed1f3d0c6, Top-K 512, logits width 524288):
20/20 correct policy decisions across rows x {32K,65K,131K,262K,524K} grid.
C32 operating grid (192 rows, live_ctx <= 262K): 1.39x aggregate speedup.
End-to-end on MI350X TP4, DeepSeek-V4.1-Flash FP4, AgentX C32, DURATION=600s:
Output throughput: 236.70 vs 237.96 tok/s/chip (-0.53%, within noise band)
p90 interactivity: 36.78 vs 34.46 tok/s/user (+6.75%, outside noise band)
The throughput delta is within the measured ±0.79% run-to-run spread.
The p90 interactivity gain is well outside the ±1.7% secondary band.
FULL-graph steps (majority at high concurrency) conservatively retain native;
the gain comes from PIECEWISE steps where live context is available.
Co-Authored-By: Claude <noreply@anthropic.com>
![claude[bot]](https://avatars.githubusercontent.com/in/1236702?s=60&v=4){kind=small}
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Purpose
Fix a miscalibrated kernel routing gate in
_get_aiter_top_k_kernel()(vllm/v1/attention/ops/rocm_aiter_mla_sparse.py) that causes the AITERtop_k_per_row_decodekernel to be bypassed in favor of native on gfx950, even when AITER is measurably faster.Two bugs in the existing gate:
Bug 1 — FULL-graph replay always forces native. The call site passes
max_model_len(1 048 576) instead of the live compressed sequence length underCUDAGraphMode.FULL. The conditionmax_valid_seq_len > _GFX950_C4A_AITER_MAX_COMPRESSED_SEQ_LENevaluates to1 048 576 > 65 536 = Truefor every FULL-graph decode step, unconditionally routing to native.Bug 2 — The 64 K threshold is wrong even with the correct live length. Measured on gfx950 (MI350X): AITER is 1.08–2.08× faster than native at C32 (192 verification rows) for live compressed contexts up to 262 144 tokens. The 64 K cutoff forces native for any context above 64 K, including the typical long-context operating point (50 K–300 K tokens).
This PR replaces the one-dimensional
max_valid_seq_len > 64Kgate with a two-dimensional(rows, live_compressed_ctx)policy calibrated on gfx950. Native is preserved conservatively forCUDAGraphMode.FULL(where live context is unavailable at replay time).Test Plan
Policy correctness (no GPU required):
Full suite on gfx950/gfx942:
Tests cover:
rows ∈ {48, 96, 192, 384}×live_ctx ∈ {32 K, 65 K, 131 K, 262 K, 524 K})CUDAGraphMode.FULLalways returns native (live_ctx=None)requires_rocm_cdna3_or_newer)Test Result
Kernel-level calibration — gfx950 MI350X,
nightly-eed1f3d0c6Method: graph-captured weakest-of-5, 200-iteration GPU clock warmup,
logits_width = 524 288,Top-K = 512. Bitwise index-set correctness verified before timing accepted.Context sweep at C32 (192 rows):
Full 20-shape policy validation:
End-to-end — MI350X 4-chip TP4, DeepSeek-V4.1-Flash FP4
Workload: AgentX agentic-coding trace replay, concurrency 32, DSpark depth 5,
DURATION=600 s. Run-to-run noise: ±0.79% throughput, ±1.7% p90 interactivity.Throughput −0.53% is within the ±0.79% noise band. p90 interactivity +6.75% is well outside the ±1.7% band. The gain is concentrated in the slow tail (requests with moderate context hitting native unnecessarily); full-context requests are unchanged.
Why throughput is not positive:
CUDAGraphMode.FULLsteps (majority at high concurrency) conservatively retain native — live context is absent from the graph replay key. The p90 gain comes fromPIECEWISEsteps. Extending the policy to FULL graphs by bucketinglive_compressed_ctxinto the capture key is a follow-on.Essential Elements of an Effective PR Description Checklist
supported_models.mdandexamplesfor a new model.