算法与高性能计算实践

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Python

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Packages

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1. pandas: A Python package that provides fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive.
2. NumPy: The fundamental package for scientific computing with Python.
3. Dask: A Python library for parallel and distributed computing.
4. Numba: A just-in-time compiler for numerical functions in Python.
5. PyTorch: An optimized tensor library for deep learning using GPUs and CPUs.
6. PyTorch Lightning: The deep learning framework to pretrain, finetune and deploy AI models.
7. PyTorch Geometric: A library built upon PyTorch to easily write and train Graph Neural Networks for a wide range of applications related to structured data.

Rust

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Official website

Documentation

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Link

Crates

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1. rayon: Rayon is a data-parallelism library for Rust.
2. ndarray: An n-dimensional array for general elements and for numerics. Lightweight array views and slicing; views support chunking and splitting.
3. bio: This library provides Rust implementations of algorithms and data structures useful for bioinformatics.
4. noodles: Bioinformatics I/O libraries.
5. serde: A generic serialization/deserialization framework.
6. bincode: A binary serialization / deserialization strategy for transforming structs into bytes and vice versa.

Julia

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Official website

Documentation

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Link

Packages

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1. MLJ.jl: A Julia machine learning framework.
2. Flux.jl: A 100% pure-Julia stack and provides lightweight abstractions on top of Julia’s native GPU and AD support.