Add "Total Machine Code Cost" of UOps to PyStats
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- Dominant language
- Python
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Description
At the sprints at PyConUS 2024, @brandtbucher suggested an improvement to pystats data. Right now, the Tier 2 stats include a count of how many times each UOp is executed, but Brandt suggested another useful table would be UOp Execution Count * Length of UOp in Machine Instructions, sorted by this metric.
In this way, UOps that are extremely common but cheap can be deprioritized, and work can be focused on improving UOps that are less common but take up more 'time' overall (with machine code length as a proxy for time).
I'm happy to take this on.
Linked PRs
- gh-119693
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the CPython Tier 2 PyStats implementation and linked PR gh-119693 first; the issue names no file or test entry point. Done means PyStats reports UOp execution count multiplied by machine-instruction length and sorts entries by that total.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 20/100