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What is our preferred way to do memory profiling on our code?
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# Description
A manual of best practices for code profiling using existing tooling
# Objectives
- [ ] Best tools used to profile code performance
- [ ] Best practices for logging and profiling code
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### Instrument
_No response_
### What happened?
We need to profile Eureka's performance in order to assess major bottlenecks and hopefully speed things up. This is especially important for Stage 3 …
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@ruudvdent noticed that in the profiling code, we calculate totals without compensating for the area weights:
https://github.com/WAM2layers/WAM2layers/blob/ffee8b844af92a991a9cbe7d5f70a408f25498e6/…
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### What
- We have not done any profiling of the Perl code of the server, it is very likely that there are performance issues that we could solve, if we find them. Same for memory leaks: our mod_perl…
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We would definitely benefit from some benchmarking and profiling of the current code, to find bottlenecks and choke points. This issue will keep track of them.
Here are some suggestions of things t…
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The code will report error [here](https://github.com/evalplus/evalplus/blob/c05b20b24ab6783878d9ffa1ae5496e83da0e65b/evalplus/evalperf.py#L196):
```python
ref_solution = ptask["reference"][idx]
…
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I really like the output of this memory profiler.
However, I think that people who are interested in memory efficiency may also be interested in execution time. And in requiring the decorator (or so…
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Recent macro-benchmarks by @eliransin and myself, as well as benchmarks that are run periodically by QA, suggest that Alternator workloads of small read and write requests run at roughly **half the th…
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- [x] Profile the code and find the bottleneck
- [ ] Optimize code for possible speedup