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Model Parallelism Techniques · Awesome GitHub Repositories

5 repos

Awesome GitHub RepositoriesModel Parallelism Techniques

Methods for partitioning neural network layers, tensors, or parameters across hardware to overcome memory and compute constraints.

Explore 5 awesome GitHub repositories matching networking & communication · Model Parallelism Techniques. Refine with filters or upvote what's useful.

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  2. Networking & Communication
  3. Distributed Systems and Peer-to-Peer
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  5. Model Parallelism Techniques

Awesome Model Parallelism Techniques GitHub Repositories

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  • tensorflow/tensorflow

    tensorflow/tensorflow

    193,864GitHubView on GitHub↗

    TensorFlow is a comprehensive machine learning framework designed for the construction, training, and deployment of complex mathematical models. It utilizes a graph-based execution model that represents operations as directed acyclic graphs, enabling automatic differentiation and efficient parallel processing. The syst

    C++deep-learningdeep-neural-networksdistributed
  • pytorch/pytorch

    pytorch/pytorch

    97,601GitHubView on GitHub↗

    PyTorch is a machine learning framework centered on a GPU-ready tensor library that supports multi-dimensional array operations across both CPU and accelerator hardware. It provides a foundational infrastructure for mathematical computation and dynamic neural network construction, utilizing a tape-based automatic diffe

    Pythonautograddeep-learninggpu
  • tensorflow/models

    tensorflow/models

    77,684GitHubView on GitHub↗

    This repository serves as a centralized collection of state-of-the-art deep learning architectures and reference implementations designed for research and application development. It provides a comprehensive toolkit for computer vision and natural language processing, offering pre-built models and training pipelines fo

    Python
  • d2l-ai/d2l-zh

    d2l-ai/d2l-zh

    75,708GitHubView on GitHub↗

    This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners

    Pythonbookchinesecomputer-vision
  • openai/codex

    openai/codex

    61,152GitHubView on GitHub↗

    Codex is an automated programming tool and generative code assistant designed to interpret developer intent through a natural language interface. It functions as a machine learning model trained on public code repositories to provide intelligent code completion, suggestions, and refactoring within development environme

    Rust

Explore sub-tags

  • Distributed Parameter ShardingMethods that partition large-scale model tensors across multiple compute nodes to facilitate parallel processing.
  • Distributed Parameter SynchronisationProtocols that coordinate gradient updates across multiple accelerators using collective communication.
  • Model Parallelism StrategiesStrategies for splitting large neural network layers across multiple hardware accelerators to manage memory requirements.
Parameter Servers
Architectures that support large-scale deep learning through techniques like asynchronous computation and multi-device parallelization.
  • Pipeline Parallelism StrategiesDistributed strategies that allow models to be partitioned across multiple stages for parallel execution.