python / python/cpython

`_remote_debugging`: `RemoteUnwinder(..., jit=True)`

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extension-modules topic-JIT topic-profiling type-feature
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描述

Feature or enhancement

Proposal:

:)

The idea here is to expose JIT internals a bit more in the Tachyon profiler.

The questions that could be answered trivially:

  • Is JIT actually used? How often?
  • Which executor is hot?
  • What change made the largest difference (diff_flamegraph), in terms of % spent in JIT? Per line?

A bit harder:

  • Which UOPs actually eat time?
  • Which stensils are good?
  • What guards or deopts are bad?
  • What is the trace shape?

The very minimal change that I'm thinking about here is just adding --jit flag (active for --jsonl and maybe for --live but it's a catnip), and adding JitInfo to ThreadInfo.

That's how it could look:

JitInfo(
  executor_id,
  flags
)

This will requires extending debug offsets, obviously.

We could potentially expose native_pc, native_offset, uop_index, exit_index etc. The question would be how to expose metadata for it without balooning JitInfo, and how far we can get without blocking and native unwinding. :)

I'm pretty much open to any other ideas.

There will be definitely some performance impact (more VM reads), but hidden behind the --enable-experimental-jit flag should be bearable, and we could be more playful, going back and forth.

If you think it makes sense, I'd be willing to take a shot, but this will take multiple PRs.

Has this already been discussed elsewhere?

No response given

Links to previous discussion of this feature:

No response

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研究方向

先追蹤 _remote_debuggingRemoteUnwinder(..., jit=True) 以及現有的 ThreadInfo 流程。比較針對 --jsonl 以及可能的 --live 所提議的 --jit 行為,接著檢查偵錯偏移量的處理方式。完成的要求是確定在 --enable-experimental-jit 後面公開 JitInfo 及其 metadata 的範圍,同時考量效能影響。

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評估

技術堆疊
python
領域
devtools, performance
Issue 類型
功能
難度
5/5
預估耗時
一週以上
活躍度
冷清
描述清晰度
需要釐清
新手友好度
25/100

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