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Advanced practice

·173 words·
Guide Advanced Omics Parallel High Performance Machine Learning Deep Learning IO Python PyTorch Rust
Table of Contents

Algorithms and High Performance Computing Practice
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Python
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Packages
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  1. NumPy: The fundamental package for scientific computing with Python.
  2. Numba: A just-in-time compiler for numerical functions in Python.
  3. Polars: A blazingly fast DataFrame library for manipulating structured data.
  4. Dask: A Python library for parallel and distributed computing.
  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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Documentation
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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.

Chenhua Wu
Author
Chenhua Wu
A Master’s student at NWAFU.