[squibloads]

Purpose

Fixes #1327.

The bug. On SM70, _prefill_logits_cublas scores prefill queries against index keys that are missing their per-key scale. Without it, e4m3 values reach 448, so a single 128-wide q . k can exceed fp16's 65504. The GEMM wrote an fp16 score tile, which overflowed to inf. Where the mixed-sign head weights then summed +inf and -inf in the epilogue, the result was NaN.

On GLM-5.3-Flash, about 20-25% of the valid layer-3 scores of a 2.8K-token prompt were non-finite. That corrupted top-k pool selection for every prompt longer than index_topk. Measurements are in #1327.

The fix. This PR writes the tile in fp32 (torch.mm(..., out_dtype=torch.float32)), and indexer_prefill_tile_mb now budgets 4 bytes per score. The epilogue already loads scores with .to(tl.float32), so it is unchanged. Two comments that described the fp16 tile are updated.

Test Plan

• python -m pytest -p no:cacheprovider -q tests/kernels/test_deepseek_v4_sm70_indexer.py on one V100-SXM2-32GB.
  • Image: a 1Cat build at c59b3c4. Its vllm/models/deepseek_v4/sm70/indexer.py is byte-identical to main at 4d57473db.
  • This branch's indexer.py and test file are mounted over the image's copies. pytest 7.4.4 is on PYTHONPATH.
• I ran the same file against the unchanged main indexer.py, to show that the new test catches the bug.
• ruff 0.14.0 (check and format --check) and typos 1.43.5 on both changed files.

New test: test_prefill_cublas_scores_survive_unscaled_key_magnitudes.

• Inputs: half the keys are the e4m3 maximum (448, scale 2^-8), and two query heads are 2.0. That gives q . k = 114688 before scaling, against heads weighted +1 and -1.
• Asserts: the scores are finite and match the fp32 reference.

Path coverage

Path / provider	Format	Key conditions (shape, TP/EP, graph, capability)	Expected selection / fallback	Evidence (source / static / executed / measured)	Unverified scope
SM70 indexer prefill, cuBLAS route (_prefill_logits_cublas)	E4M3 index keys, fp16 queries	prefill seeing > index_topk keys; indexer_prefill_cublas on (default); SM70	Same route; the GEMM output is now fp32. Triton prefill and every decode route unchanged	executed (unit test, V100); measured (GLM-5.3-Flash TP4 end to end, #1327)	DeepSeek-V4 end to end; SM75

Acceleration and benchmark contract (required for performance changes)

This is a correctness fix; route selection does not change.

• Default enabled or opt-in: default; no new switch.
• Required CLI options and environment switches: none.
• KV cache dtype used for the benchmark: fp8 (E4M3).
• Wheel SHA or source commit:
  • Unit test: 1Cat c59b3c4 image plus this branch's indexer.py.
  • End to end: philbert440/glm-5.3-v100 card build (ec60883ad + GLM PR stack), with this same change applied to its copy of the function.
• PYTHONPATH, source overlays, or external native libraries used:
  • Unit test: source overlay of indexer.py and the test file; host pytest on PYTHONPATH.
  • End to end: source overlay of indexer.py, plus the local patches listed in [Bug]: [SM70] Indexer prefill scores overflow fp16 in _prefill_logits_cublas (inf/NaN), corrupting sparse-attention key selection for prompts > index_topk #1327.
• User-entry route-hit, speed, and output-quality evidence: see Test Result.
• Existing kernel/backend registry and capability-rejection reasons: unchanged.
• Per-engine configuration and deprecated-variable compatibility: unchanged. indexer_prefill_tile_mb keeps its meaning as a MiB cap, so a tile now holds half as many keys.
• New/changed environment metadata and generated reference check: none.
• Route snapshot command and intentional changed rows: none.
• SM70 registered variables / unregistered reads / model-parameter restrictions, before -> after: unchanged.

Test Result

Unit tests, one V100:

unchanged main indexer.py: 1 failed, 26 passed
  FAILED test_prefill_cublas_scores_survive_unscaled_key_magnitudes
  (at `assert torch.isfinite(actual).all()`)
this branch:               27 passed

ruff check, ruff format --check and typos all pass.

Function timing. One V100, 2304 queries x 32 heads x 128, CUDA-event mean:

keys	fp16 tile (main)	fp32 tile (this PR)
3,000	3.83 ms	2.92 ms
12,000	13.62 ms	11.25 ms
32,000	35.99 ms	29.38 ms

End to end. GLM-5.3-Flash on 4x V100, TP4, same seeded prompts.

• These runs also sort each row's top_k_per_row_prefill picks ([Bug]: [SM70] Indexer prefill scores overflow fp16 in _prefill_logits_cublas (inf/NaN), corrupting sparse-attention key selection for prompts > index_topk #1327). That sort changes only summation order, not which pools are selected.
• The prefill numbers include the sort.

	before	after
find 1 of 8 codes in natural text, ~26K / ~54K / ~92K tokens	2/4, 1/4, 0/4	4/4, 4/4, 4/4
record lookup, 12-30K tokens	18/24	24/24
prefill tok/s, 15-16K tokens	2,148	2,125
prefill tok/s, 48-50K tokens	2,060	2,052

Notes

• Not a duplicate. I searched open and closed PRs and issues for _prefill_logits_cublas, "indexer overflow", "indexer fp32 prefill" and "indexer score tile". None changes this route's output dtype. [Perf][SM70][DeepSeek-V4] Keep the cuBLAS decode indexer above 131,072 tokens of context #1222 changed the decode cuBLAS indexer, not prefill.
• AI assistance was used to find this bug, write the change and the test, and run the measurements above.

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
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