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[TRTLLM-6898][feat] Add Cute DSL nvfp4 linear op#7632
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Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
coderabbitaibot commentedSep 9, 2025 • edited
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📝 WalkthroughWalkthroughAdds a new Blackwell SM100 CuTe-DSL persistent block-scaled GEMM kernel and utilities, integrates a Python 3.12+ gated FP4/FP8 GEMM path into Torch custom ops, wires it into Linear via a new flag and scalar alpha handling, updates dependencies, and introduces unit/perf tests for the new path. Changes
Sequence Diagram(s)sequenceDiagram autonumber actor User participant Linear as Linear (NVFP4) participant Ops as torch_custom_ops participant Tuner as AutoTuner/TunableRunner participant Kernel as KernelWrapper participant GPU as Device Kernel User->>Linear: forward(input) alt use_cute_dsl_nvfp4_blockscaling_mm Linear->>Ops: cute_dsl_nvfp4_gemm_blackwell(input, weight, scales, alpha_s) Ops->>Ops: Check Python>=3.12 & HAS_CUTLASS_DSL alt Available Ops->>Tuner: get_valid_tactics() Tuner->>Kernel: compile/select tactic Kernel->>GPU: launch(m, n, k, pointers, epilogue) GPU-->>Kernel: result Kernel-->>Ops: BF16 tensor Ops-->>Linear: BF16 tensor else Unavailable Ops-->>Linear: raise RuntimeError end else legacy path Linear->>Ops: nvfp4_gemm(..., alpha) Ops-->>Linear: result end Linear-->>User: outputsequenceDiagram autonumber participant Ops as torch_custom_ops (init) participant Env as Runtime Ops->>Env: import cutlass DSL (Python>=3.12) alt Success Env-->>Ops: loaded Ops-->>Ops: HAS_CUTLASS_DSL=True else Failure Env-->>Ops: not available Ops-->>Ops: HAS_CUTLASS_DSL=False endEstimated code review effort🎯 5 (Critical) | ⏱️ ~120 minutes Tip 👮 Agentic pre-merge checks are now available in preview!Pro plan users can now enable pre-merge checks in their settings to enforce checklists before merging PRs.
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✨ Finishing Touches
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limin2021 commentedSep 9, 2025
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Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
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Summary by CodeRabbit
Description
[TRTLLM-6898][feat]Add Cute DSL nvfp4 linear op-step1
(1) install nvidia-cutlass-dsl 4.1.0 pkg. (require python >= 3.12)
(2) add nvfp4_bs_gemm into trtllm linear op.
(3) I copy the nvfp4 cute_dsl kernel fromcutlass dsl examples, and add scalar parameter support to adapt to trtllm's linear op's interface.
Test Coverage
op UT:
pytest -s -o log_cli=true tests/unittest/_torch/thop/parallel/test_fp4_linear.py -k "test_fp4_linear"model UT:

pytest -s -o log_cli=true "tests/integration/defs/accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4"Perf
to add perf data here.
TODO;
add pdl, and other optimizations for this kernel.
PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR FollowsTRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (seetest instructions)
Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
The reviewers assigned automatically/manually are appropriate for the PR.
Please check this after reviewing the above items as appropriate for this PR.
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