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Pass the runtime alpha tensor before the layout and problem-size arguments when compiling the SM107 pointer interface. Clarify the helper's SM107 type contract and reuse it from the Rubin benchmark instead of duplicating its compilation logic. Refs NVIDIA#18334. Signed-off-by: peaceh <103117813+peaceh-nv@users.noreply.github.com>
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Included review availability: Your plan provides up to 12 included reviews per hour; 10 remain after this review. WalkthroughThe Rubin GEMM path now compiles through its wrapper with explicit dimensions, layouts, and batch size. The Blackwell ChangesRubin GEMM compilation
Priority: ➖ Normal Estimated code review effort: 3 (Moderate) | ~20 minutes Change: Bug fix Suggested reviewers: Merge Risk: ⚪ Minimal · up to The updated GEMM compilation paths consistently pass alpha, dimensions, layouts, and batch configuration, with no concrete merge-blocking issue identified. 🚥 Pre-merge checks | ✅ 3 | ❌ 2❌ Failed checks (2 warnings)
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Move scaled_mm into the Rubin module alongside its only caller and reject kernels with incompatible call signatures before compilation. Use alpha=0.5 in the benchmark reference check and scale the reference accordingly. Validation on hecate0233 (SM107): six NVFP4 GPU cases covering FP16/BF16, GEMM/BMM and split-K; mixed-cluster rejection; ignored-alpha negative check. All applicable pre-commit checks passed. Signed-off-by: peaceh <103117813+peaceh-nv@users.noreply.github.com>
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In
`@tensorrt_llm/_torch/cute_dsl_kernels/rubin/dense_blockscaled_gemm_persistent.py`:
- Line 3730: Update scaled_mm to compile and invoke gemm_obj.wrapper rather than
the direct gemm_obj contract, passing matrix and scale-factor dimensions before
alpha_tensor in the required signature order. Update the benchmark caller
accordingly, and add a regression exercising this wrapper path with
alpha_tensor=0.5.
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Use runtime Int64 matrix and scale-factor dimensions and alpha in the wrapper signature order. Specialize the batch size at compilation and update the reference, benchmark, and split-K launches to the wrapper ABI. Allow an optional compile-time layout override so the helper preserves its layout mapping while existing custom-op wrapper calls keep their default behavior. Retain the non-unit alpha reference check. Refs NVIDIA#18334. Validation: all applicable pre-commit hooks passed. GPU tests were not rerun. Signed-off-by: peaceh <103117813+peaceh-nv@users.noreply.github.com>
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Dev Engineer Review
The Rubin
scaled_mmpath now passesalpha_tensoras an explicit compiled-kernel parameter. It also acceptsbatch_sizeand optional wrapper layouts. The Blackwellscaled_mmhelper was removed.Verify caller imports, SM107 compilation, alpha scaling, default and explicit layouts, and batched execution.
QA Engineer Review
No test changes.
Per-File QA Perspective
tensorrt_llm/_torch/cute_dsl_kernels/blackwell/dense_blockscaled_gemm_persistent.py: The publicscaled_mmhelper was removed. Verify that no caller still imports or invokes it from the Blackwell module.tensorrt_llm/_torch/cute_dsl_kernels/rubin/dense_blockscaled_gemm_persistent.py: SM107 compilation now includes runtimealpha_tensor, matrix and scale-factor dimensions, and optionalbatch_size. Verify alpha propagation, layout handling, GEMM/BMM execution, and split-K behavior.