numexpr
hyperfine
numexpr | hyperfine | |
---|---|---|
4 | 74 | |
2,143 | 20,020 | |
0.7% | - | |
8.2 | 8.1 | |
about 1 month ago | 8 days ago | |
Python | Rust | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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numexpr
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Making Python 100x faster with less than 100 lines of Rust
You can just slap numexpr on top of it to compile this line on the fly.
https://github.com/pydata/numexpr
- Extending Python with Rust
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[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?
Are you doing any costly chained NumPy operations in your preprocessing? E.g. max(abs(large_ary)), this produces multiple copies of your data, https://github.com/pydata/numexpr can greatly reduce time spent with such operations
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Selection in pandas using query
What is not entirely obvious here is that under the hood you can install a nice library called numexpr (docs, src) that exists to make calculations with large NumPy (and pandas) objects potentially much faster. When you use query or eval, this expression is passed into numexpr and optimized using its bag of tricks. Expected performance improvement can be between .95x and up to 20x, with average performance around 3-4x for typical use cases. You can read details in the docs, but essentially numexpr takes vectorized operations and makes them work in chunks that optimize for cache and CPU branch prediction. If your arrays are really large, your cache will not be hit as often. If you break your large arrays into very small pieces, your CPU won’t be as efficient.
hyperfine
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Measuring startup and shutdown overhead of several code interpreters
Check out the official hyperfine Github repo
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Bun - The One Tool for All Your JavaScript/Typescript Project's Needs?
And then I used hyperfine to run the benchmarks on my MacBook Pro 14 M2 Max, and here are the results:
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Faster tetranucleotide (k-mer) frequencies!
Search "benchmarking tools for linux" and decide that hyperfine is good for what I'm doing. Run Jennifer's new python script against my refactored perl and find that the python is 1.26 times faster for k=3 and 1.47 times faster for k=4. For the Covid-19 sequence, these are both on the order of hundreds of milliseconds.
- Hyperfine: A command-line benchmarking tool
- FLaNK Weekly 08 Jan 2024
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Show HN: Inshellisense – IDE style shell autocomplete
> It is very possible to write sub 100ms procedures in TS, […]
I will not disagree with this statement because I don’t have a way to test inshellisense right now. Could you (or anyone with a working Node + NPM installation) please install inshellisense and post the actual numbers? Perhaps using a tool like hyperfine (https://github.com/sharkdp/hyperfine).
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Firefox has surpassed Chrome on Speedometer
Yeah, while it's not as thorough as these tools, the method is at least reproducible and sane, and with ~10 or so samples, you get an interval with a nice confidence.
Another through method will be hyperfine[0], yet I wanted to provide a method which requires no installation and can be done in a whim, without jumps and hoops, with the tools already at hand.
[0]: https://github.com/sharkdp/hyperfine
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How to optimize your config? What are mistakes to avoid when optimizing your config?
That is native and inbuild but I would suggest below options instead 1. Using lazy's Profile tab instead https://github.com/folke/lazy.nvim 2. Using a dedicated plugin to do this https://github.com/dstein64/vim-startuptime. 3. Using an external program hyperfine is one that I use https://github.com/sharkdp/hyperfine
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How to remove all <br> from all of my .html files
Fair enough, although might I recommend using hyperfine for your testing? ;p
What are some alternatives?
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
criterion.rs - Statistics-driven benchmarking library for Rust
pygfx - A python render engine running on wgpu.
fd - A simple, fast and user-friendly alternative to 'find'
greptimedb - An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore
jnumpy - Writing Python C extensions in Julia within 5 minutes.
awesome-mac - Now we have become very big, Different from the original idea. Collect premium software in various categories.
jsmpeg - MPEG1 Video Decoder in JavaScript
kubeconform - A FAST Kubernetes manifests validator, with support for Custom Resources!
poly-match - Source for the "Making Python 100x faster with less than 100 lines of Rust" blog post
quinn - Async-friendly QUIC implementation in Rust