[Bugfix][Hardware][NVIDIA] Add VLLM_DISABLE_CUTEDSL kill-switch for CuTeDSL kernels

[pavelzak]

Purpose

Add a VLLM_DISABLE_CUTEDSL environment kill-switch for CuTeDSL kernels.

On GB10 (SM12.1), CuTeDSL kernels fail with internal compiler errors (e.g. the DSV4 fused_indexer_q_cutedsl indexer kernel), while the non-CuTeDSL fallbacks work fine. Today there is no way to opt out of CuTeDSL when the cutlass package is installed — availability probes only check importability, so every affected code path has to be patched by hand.

Changes:

• vllm/envs.py: register VLLM_DISABLE_CUTEDSL (default off), documented as an escape hatch for platforms where CuTeDSL kernels fail to compile.
• import_utils.has_cutedsl(): return False when the switch is set — single central gate.
• DSV4 compressor: fall back to the Triton two-stage compressor for head_dim=512 on CUDA when CuTeDSL is unavailable/disabled (it is the only non-CuTeDSL compressor for that head dim).
• cute_dsl/ll_bf16.is_available(): consult has_cutedsl() before probing the cutlass import, so the cached probe honors the switch.

Not a duplicate: no open PR adds a CuTeDSL opt-out (searched cutedsl disable, VLLM_DISABLE_CUTEDSL); existing VLLM_DISABLED_KERNELS only filters quantization kernel classes by name and does not gate CuTeDSL availability probes.

Test Plan

• python -m py_compile on all four touched files.
• End-to-end: 2× DGX Spark (GB10, SM12.1), TP=2, serving DeepSeek-V4-Flash-0731 with VLLM_DISABLE_CUTEDSL=1: verify the Triton two-stage compressor is selected, ll_bf16 reports unavailable, and no CuTeDSL compilation is attempted.
• Default-path regression: without the env var, behavior is byte-identical (has_cutedsl() still just probes the cutlass module).

Test Result

• Before: DSV4 startup on GB10 dies in CuTeDSL internal compiler errors with no opt-out.
• After: VLLM_DISABLE_CUTEDSL=1 serves DeepSeek-V4-Flash-0731 stably on 2× DGX Spark GB10 TP=2 via the non-CuTeDSL fallbacks; unset, nothing changes.

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AI assistance was used for this PR (rebasing from a v0.26.0-based production branch onto main, plus moving the env read into vllm/envs.py per project convention); every changed line was reviewed and validated end-to-end by the submitter on the hardware above.

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[jeejeelee]

What error did you encounter? We think adding an env variable isn't the right direction, and we should try to fix the kernel error

[pavelzak]

Thanks @jeejeelee. I revisited this on the same hardware and could not reproduce the reported compilation failure with a matched dependency set. The PR’s blanket claim of GB10 incompatibility was too broad.

I tested on two DGX Sparks (GB10, SM12.1), serving DeepSeek-V4-Flash-0731 with TP=2 on my existing v0.26-based Spark branch. The working test configuration used CuTeDSL 4.6.2 with matching component packages, Quack 0.6.4, and apache-tvm-ffi 0.1.11.

With vLLM’s CuTeDSL helpers enabled:

• FP8 indexer: all 10 cases passed against Triton: token counts 1, 7, 32, 257, and 1023, with FP32 and BF16 RoPE tables. Quantized query bytes and output weights matched exactly.
• Packed FP8 compressor: all six cases passed for head dimension 512 and compression ratios 4/128, including boundary conditions, invalid slots, and C128 decode/prefill/mixed paths. Cache bytes matched Triton exactly.
• BF16 router warmup: completed all 17 distinct compile/cache-load keys, including split-K variants. This does not validate BF16 GEMM execution; the normal router guard still excludes GB10.
• Full serving: startup, profiling, and CUDA graph capture completed on both nodes. All 12 sequential/concurrent generation smoke checks passed, including a 3,225-token prompt.

During reproduction, I encountered dependency/API mismatches involving cpasync.ReductionKind and TVM FFI’s map_dataclass_to_tuple argument. Aligning the packages resolved those failures. However, the saved historical traceback lacks the actual compiler diagnostic, so I cannot establish that these caused the original failure.

Performance testing also found a separate prefill regression in the experimental dependency/cache environment, present with the helpers both enabled and disabled. That needs separate investigation.

Given these results, I’m withdrawing the broad GB10 incompatibility claim and closing this PR. I no longer have a reproducible kernel compilation failure that justifies adding this global availability override. Any follow-up should start with a minimal reproducer and address the specific failure.