hygon-triton-kernel-optimizer

name

hygon-triton-kernel-optimizer

description

Capture, triage, benchmark, and optimize TorchInductor or hand-written Triton kernels on Hygon DCU gfx936/gfx938. Use when investigating torch.compile or TorchInductor Triton performance on DCU, parsing Triton autotune logs, saving generated kernels and inputs, checking AMDGCN buffer/global load-store codegen, applying tl.assume or tl.multiple_of hints, diagnosing low-bandwidth pointwise/reduction/scatter kernels, or deciding whether to tune Triton, disable torch.compile for a region, or rewrite model code.

Hygon Triton Kernel Optimizer

Purpose

Optimize or triage DCU Triton kernels generated by TorchInductor or written by hand. Use a measured workflow:

1. capture the generated kernel, input shapes, autotune configs, and cache artifacts;
2. inspect Triton metadata, pointer hints, and AMDGCN load/store instructions;
3. decide whether the kernel is worth tuning;
4. test tl.assume, tl.multiple_of, block size, warp count, and launch-shape variants;
5. if the kernel is structurally poor, avoid the generated Triton path or rewrite model code.

Keep scripts responsible for capture, parsing, artifact collection, and report generation. Use reasoning for code changes and architectural decisions.

Required Inputs

Have as many of these as possible:

• the original model or repro script that uses torch.compile;
• the target kernel name, or a profile showing the hot Triton kernel;
• log_profile.txt captured with TORCH_LOGS="+inductor" and TORCHINDUCTOR_TRACE=1;
• autotune_kernels/autotune.log and captured triton_<kernel>.py files;
• /tmp/torchinductor_root cache artifacts, especially .amdgcn, .ttir, , and generated Python files.