[QST] How to understand kernel name cutlass_75_tensorop_bf16_s1688gemm_bf16_256x128_nn_align1?
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Description
What is your question?
I profiled a tensorflow model training on A30, and found this kernel name: cutlass_75_tensorop_bf16_s1688gemm_bf16_256x128_nn_align1
Does 75 here means SM75 capability? But bf16 is only supported after Ampere, why can SM75 have bf16?
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Research direction
The issue names only the CUTLASS kernel cutlass_75_tensorop_bf16_s1688gemm_bf16_256x128_nn_align1 and an A30 TensorFlow profile; no file, test, or entry point is provided. Start by locating the code or documentation that defines CUTLASS kernel-name components, then verify what 75 and bf16 represent. Done means the naming and apparent SM75/BF16 mismatch are clearly explained.
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Assessment
- Tech stack
- cpp
- Domain
- hpc, machine-learning
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100