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[TRTLLM-6898][feat] Add Cute DSL nvfp4 linear op#7632

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@limin2021
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@limin2021limin2021 commentedSep 9, 2025
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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 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"

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 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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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>
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
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coderabbitaibot commentedSep 9, 2025
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📝 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 dependencynvidia-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 opcute_dsl_nvfp4_gemm_blackwell, and fake-op registrations.
Linear module wiring
tensorrt_llm/_torch/modules/linear.py
Adds flaguse_cute_dsl_nvfp4_blockscaling_mm; routes NVFP4 path to new op usingscalar_alpha; populatesscalar_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
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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
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Estimated code review effort

🎯 5 (Critical) | ⏱️ ~120 minutes

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@limin2021limin2021 changed the title[][]Add cute dsl nvfp4 linear step 1[None][feat]Add Cute DSL nvfp4 linear opSep 9, 2025
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
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@limin2021limin2021 changed the title[None][feat]Add Cute DSL nvfp4 linear op[TRTLLM-6898][feat]Add Cute DSL nvfp4 linear opSep 9, 2025
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@limin2021limin2021 changed the title[TRTLLM-6898][feat]Add Cute DSL nvfp4 linear op[TRTLLM-6898][feat] Add Cute DSL nvfp4 linear opSep 9, 2025
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@yuxianqyuxianq merged commitb278d06 intoNVIDIA:mainSep 16, 2025
5 checks passed
Wong4j pushed a commit to Wong4j/TensorRT-LLM that referenced this pull requestSep 20, 2025
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
MrGeva pushed a commit to nv-auto-deploy/TensorRT-LLM that referenced this pull requestSep 21, 2025
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
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@coderabbitaicoderabbitai[bot]coderabbitai[bot] left review comments

@litaotjulitaotjulitaotju approved these changes

@chzblychchzblychchzblych approved these changes

@liji-nvliji-nvliji-nv approved these changes

@yuxianqyuxianqyuxianq approved these changes

@Kefeng-DuanKefeng-DuanKefeng-Duan approved these changes

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