Distributed-Systems-Guide
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| Distributed-Systems-Guide | bagua | |
|---|---|---|
| 1 | 6 | |
| 22 | 865 | |
| - | 0.2% | |
| 4.2 | 4.8 | |
| over 2 years ago | 9 months ago | |
| Python | ||
| - | MIT License |
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Distributed-Systems-Guide
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Useful Tools and Resources for Distributing Computing
A useful list of Tools, Programs, and Resources for Distributing Computing.
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What are some alternatives?
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machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
storj - Ongoing Storj v3 development. Decentralized cloud object storage that is affordable, easy to use, private, and secure.
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
awesome-tensor-compilers - A list of awesome compiler projects and papers for tensor computation and deep learning.
optuna - A hyperparameter optimization framework
tune - An abstraction layer for parameter tuning
PERSIA - High performance distributed framework for training deep learning recommendation models based on PyTorch.
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
modin - Modin: Scale your Pandas workflows by changing a single line of code
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.