Optimizing argmin Performance for Floating-Point Arrays in Rust
By
return_to_monke
Crispy enough to crunch, soft enough to enjoy. A good bake.
Summary
The article discusses optimization techniques for finding the minimum value index (argmin) in large arrays of floating-point numbers, specifically focusing on Rust programming. It presents a baseline solution using iterator methods that takes 511 microseconds for a million numbers, then hints at potential performance improvements by leveraging knowledge about the data properties (positive, non-infinity, non-NaN values). The content is technical and aimed at programmers seeking performance optimization.
Key quotes
· 4 pulledConsider the following problem: you are given a dynamically large array of NN floating point numbers, and you are asked to find the index of the smallest one (commonly called arg min) as fast as possible.
For a million numbers, this runs in around 511 us. Not bad.
However, we can do better, by using what we know about the data itself.
If you know that you are working with "regular" floats, you can make argmin faster.
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