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@limin2021 limin2021 commented Sep 9, 2025

Summary by CodeRabbit

  • New Features
    • Added an optional NVFP4 block‑scaled GEMM path accelerated by CuTe DSL for Blackwell GPUs, with autotuning and BF16 outputs. Configurable via a new Linear constructor flag; existing behavior remains the default when disabled. Automatically gated by Python 3.12+ and runtime availability.
  • Tests
    • Introduced unit and performance tests validating correctness and benchmarking the new NVFP4 CuTe DSL path across multiple shapes.
  • Chores
    • Added a new dependency for Python 3.12+ to enable the CuTe/Cutlass DSL integration.

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 from cutlass 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"

image

model UT:
pytest -s -o log_cli=true "tests/integration/defs/accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4"
image

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 Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

  • Test cases are provided for new code paths (see test 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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Signed-off-by: Mindy Li <[email protected]>
Signed-off-by: Mindy Li <[email protected]>
Signed-off-by: Mindy Li <[email protected]>
@limin2021 limin2021 requested review from a team as code owners September 9, 2025 03:19
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coderabbitai bot commented Sep 9, 2025

📝 Walkthrough

Walkthrough

Adds 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

Cohort / File(s) Summary
Dependencies
requirements.txt
Adds dependency nvidia-cutlass-dsl==4.1.0 for Python >= 3.12.
CuTe DSL Blackwell kernel and utils
tensorrt_llm/_torch/custom_ops/cute_dsl_kernels/blackwell/dense_blockscaled_gemm_persistent.py, tensorrt_llm/_torch/custom_ops/cute_dsl_kernels/blackwell/utils.py
Introduces persistent block-scaled GEMM kernel for SM100, wrapper, run harness, scale-factor converter, and runtime pointer utilities (_Pointer, make_ptr).
Torch custom ops integration
tensorrt_llm/_torch/custom_ops/torch_custom_ops.py
Adds Python 3.12+ gated CuTe-DSL NVFP4 GEMM path, tuner-backed runner, public op cute_dsl_nvfp4_gemm_blackwell, and fake-op registrations.
Linear module wiring
tensorrt_llm/_torch/modules/linear.py
Adds flag use_cute_dsl_nvfp4_blockscaling_mm; routes NVFP4 path to new op using scalar_alpha; populates scalar_alpha in weight-loading paths.
Tests
tests/unittest/_torch/thop/parallel/test_fp4_linear.py
Adds NVFP4 CuTe-DSL functional and perf tests (Python 3.12 gated), including padding helper and scripted perf entry.

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: output
Loading
sequenceDiagram
  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
  end
Loading

Estimated code review effort

🎯 5 (Critical) | ⏱️ ~120 minutes

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@limin2021 limin2021 changed the title [][]Add cute dsl nvfp4 linear step 1 [None][feat]Add Cute DSL nvfp4 linear op Sep 9, 2025
Signed-off-by: Mindy Li <[email protected]>
Signed-off-by: Mindy Li <[email protected]>
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@limin2021 limin2021 changed the title [None][feat]Add Cute DSL nvfp4 linear op [TRTLLM-6898][feat]Add Cute DSL nvfp4 linear op Sep 9, 2025
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@limin2021 limin2021 requested a review from litaotju September 9, 2025 05:35
@limin2021 limin2021 changed the title [TRTLLM-6898][feat]Add Cute DSL nvfp4 linear op [TRTLLM-6898][feat] Add Cute DSL nvfp4 linear op Sep 9, 2025
Signed-off-by: Mindy Li <[email protected]>
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@yuxianq yuxianq merged commit b278d06 into NVIDIA:main Sep 16, 2025
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Wong4j pushed a commit to Wong4j/TensorRT-LLM that referenced this pull request Sep 20, 2025
MrGeva pushed a commit to nv-auto-deploy/TensorRT-LLM that referenced this pull request Sep 21, 2025
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