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Hi @Beliavsky, that's a great question -- right now Codon can call NumPy and Pandas through Python, but won't compile/optimize any of those calls, so the performance will be the same as in Python. We are working on a Codon-native NumPy implementation that's fully compiled with added optimizations like fusion etc. The performance benefits of that will be application-specific: if you're just doing one huge matrix inverse, for example, then all the time is being spent in BLAS/LAPACK anyway so there won't be much difference, but for more complex operations--especially ones that can be fused or done more efficiently between library calls--we can potentially get much better performance. The other nice thing about that is it can be used with Codon's parallelism / GPU backend. After that, we do plan to look into Pandas, but no ETA yet -- will share more details as we make progress! |
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Will codon typically improve the performance of Python programs that heavily use NumPy or Pandas?
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