deepseek_v4: route unclean MQA logits through the SM12x Triton kernel

[calvarado2004]

What

_fp8_mqa_logits_sm12x only routed to fp8_mqa_logits_triton when
clean_logits=True. The sparse-attn-indexer prefill path always calls with
clean_logits=False, so every prefill ran the pure-torch fallback instead.
At large seq_len_kv the fallback degenerates to head_chunk_size=1 (the
64 MiB score budget divides to zero), turning a single 8K-token chunk into
thousands of tiny fp32 matmuls per layer.

Measured effect on 2× DGX Spark (SM121, CUDA 13.3): a 450K-token prompt
monopolized the engine for 35+ minutes without completing one chunk (KV-block
allocation frozen, GPU pinned at 96%, py-spy showing the worker inside
_fp8_mqa_logits_torch).

Why the one-line gate change is safe

The Triton kernel writes -inf outside [ks, ke) unconditionally
(sm12x_mqa.py, the tl.where(seq_mask & store_mask, logits, -inf) store) —
a strict superset of the clean_logits=False contract. The downstream
top_k_per_row_prefill consumes the same cu_seqlen bounds, so cleaned logits
are valid for both callers. Only the clean_logits condition is dropped;
FP4-Q and non-3D shapes still fall back.

Validation

• Numerics: Triton vs torch reference, windowed shapes — identical -inf
  masks, max relative diff 6.4e-7, 28× faster at [1024 × 131072 × 64h]
  (far larger at jumbo shapes, where the torch path collapses to
  single-head chunks).
• End-to-end on 2× GB10: a 468,540-token needle prompt completes in 498 s
  with correct retrieval where it previously never finished; a high-effort
  reasoning prompt that degenerated into repetition/gibberish now solves
  cleanly (finish=stop, 9,938 tokens, correct answer).
• New regression test tests/kernels/attention/test_sm12x_mqa_logits.py:
  a CPU dispatch-contract test (both clean_logits values must reach the
  Triton kernel — passing) and a CUDA numerics test mirroring the check
  above.

Duplicate-work check

No open vllm-project issue or PR covers the SM12x MQA prefill gate
(searched fp8_mqa_logits, sm12x mqa, indexer-prefill terms; the hits are
ROCm-side analogues — vllm-project#48576, vllm-project#41963, vllm-project#52109). The bf16 rework discussed in
vllm-project#41063 targets _fp8_mqa_logits_topk_torch (decode), not this prefill
dispatch.

Disclosure

AI-assisted (Claude); I reviewed every changed line and ran the tests and
end-to-end validation on my two DGX Sparks.

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[jasl]

Thanks — the safety argument holds up. I checked the "Triton cleans
unconditionally, so it's a strict superset" claim rather than taking it on
trust, and the mask boundaries are identical to the torch path, so routing
clean_logits=False there is sound. The dispatch test also patches the right
binding: the production import is function-local, so getattr re-runs per call
and the monkeypatch genuinely takes effect. Good test.

Before merging I'd like to reconcile one thing, because I can't make the stated
mechanism fit on the default config.

On codex/ds4-sm120-min-enable the indexer prefill loop takes a fused fast path
before it ever reaches the line you changed:

sparse_attn_indexer.py:545   if (
                     546       dcp_world_size <= 1
                     547       and chunk.local_total_seq_lens > 0
                     548       and not current_platform.is_xpu()
                     549       and fp8_fp4_mqa_topk_indices(...)
                     557   ):
                     558       continue
                     576   logits = fp8_fp4_mqa_logits(..., clean_logits=False)   # your line

fp8_fp4_mqa_topk_indices bails only when not (is_cuda and is_device_capability_family(120) and q[1] is None) (deep_gemm.py:555), and on
SM121 with an FP8 indexer cache all three hold, so the SM12x implementation runs
to its final return True. decode_context_parallel_size defaults to 1
(parallel.py:342) and our production launcher doesn't set it.

So on a default SM12x serve, line 576 looks unreachable — which would make the
patched dispatch inert there, and would mean prefill was already going through
fp8_mqa_logits_triton via the fused path rather than through
_fp8_mqa_logits_torch.

That doesn't square with your evidence, and your evidence is specific: py-spy
inside _fp8_mqa_logits_torch, a 450K prompt not completing in 35 minutes. I
believe the symptom. I just can't yet explain how that call site was reached.

Two questions, and I think the answer changes what we should merge:

1. What was decode_context_parallel_size on the run you measured?
2. Which base SHA did you reproduce the 35-minute stall on? The fused fast path
   landed in f8f18ce66b (2026-05-06), so anything older wouldn't have it.

If DCP > 1, then the patch is correct and the fix is real — I'd only ask that
the description be narrowed from "every prefill" to the DCP > 1 prefill path,
since that's the configuration it actually changes, and it's the one neither
test covers.

If DCP was 1 on a recent base, then the fused fast path returned False for
those chunks, and that is the bug worth chasing — this patch would route
around it and we'd lose the thread on why. chunk.local_total_seq_lens == 0
(line 547/560) is the branch I'd look at first.

Minor, whichever way it goes — the new test file trips three pre-commit hooks:

• F401 unused import at line 16 (sm12x_deep_gemm_fallbacks; line 17 already
  imports the two names actually used)
• I001 import block unsorted
• ruff format rewrites ~5 statements (the file is wrapped at ~79 cols, repo
  default is 88)

The two CI jobs on this PR are workflow housekeeping, so they wouldn't have
caught those.