agentleFS
AscendAscend/agent-skills/skills/ascendc-operator-performance-eval/SKILL.md

ascendc-operator-performance-eval

Skill43 starsChanged 8 months agoMulanPSL-2.0View on GitHub

在 ascend-kernel 的 csrc/ops/<op>/test 下维护仅含 JSONL 的 profiler 性能用例,使用 torch_npu.profiler(固定 warmup=5、active=5)采集,汇总 ASCEND_PROFILER_OUTPUT/op_statistic.csv 的 Total Time(us),输出含 DType 列的统一 Markdown 对比报告(自定义算子 vs 标杆)。不生成 perf_cases.json 与 *_profiler_results.json。参考实现见 examples/layer_norm_profiler_reference/。

The file

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.