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18 Distributed Computing and Machine Learning Frameworks: Empowering Scalable and Efficient Data Processing and Model Training

Explore open source distributed computing and machine learning frameworks that empower scalable and efficient data processing and model training.

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Open Source Distributed Computing Frameworks

  • Analytics Zoo

    A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray.

    License: Unknown

    GitHub
    Website: Unknown
  • Bagua

    Bagua is a performant and flexible distributed training framework for PyTorch, providing a faster alternative to PyTorch DDP and Horovod. It supports advanced distributed training algorithms such as quantization and decentralization.

    License: MIT License

  • BigDL

    Deep learning framework on top of Spark/Hadoop to distribute data and computations across a HDFS system.

    License: Apache License 2.0

  • Colossal-AI

    A unified deep learning system for big model era, which helps users to efficiently and quickly deploy large AI model training and inference.

    License: Apache License 2.0

  • Dask

    Distributed parallel processing framework for Pandas and NumPy computations - (Video) .

    License: BSD 3-Clause "New" or "Revised" License

  • DEAP

    A novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanisms such as multiprocessing and SCOOP.

    License: GNU Lesser General Public License v3.0

  • DeepSpeed

    A deep learning optimization library (lightweight PyTorch wrapper) that makes distributed training easy, efficient, and effective.

    License: Apache License 2.0

  • einops

    Flexible and powerful tensor operations for readable and reliable code.

    License: MIT License

  • Fiber

    Distributed computing library for modern computer clusters from Uber.

    License: Apache License 2.0

  • Flashlight

    A fast, flexible machine learning library written entirely in C++ from the Facebook AI Research and the creators of Torch, TensorFlow, Eigen and Deep Speech.

    License: MIT License

  • Hivemind

    Decentralized deep learning in PyTorch.

    License: MIT License

  • Horovod

    Uber’s distributed training framework for TensorFlow, Keras, and PyTorch.

    License: Other

  • LightGBM

    LightGBM is a gradient boosting framework that uses tree based learning algorithms.

    License: MIT License

  • NumPyWren

    Scientific computing framework build on top of pywren to enable numpy-like distributed computations.

    License: No License

  • PyWren

    Answer the question of the “cloud button” for python function execution. It’s a framework that abstracts AWS Lambda to enable data scientists to execute any Python function - (Video) .

    License: Apache License 2.0

  • PyTorch Lightning

    Lightweight PyTorch research framework that allows you to easily scale your models to GPUs and TPUs and use all the latest best practices, without the engineering boilerplate - (Video) .

    License: Apache License 2.0

  • Ray

    Ray is a flexible, high-performance distributed execution framework for machine learning (VIDEO ).

    License: Apache License 2.0

  • TensorFlowOnSpark

    TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.

    License: Apache License 2.0

Last Updated: Dec 26, 2023