Making large AI models cheaper, faster and more accessible

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.

飞桨大模型开发套件，提供大语言模型、跨模态大模型、生物计算大模型等领域的全流程开发工具链。

LiBai(李白): A Toolbox for Large-Scale Distributed Parallel Training

Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.

Distributed Keras Engine, Make Keras faster with only one line of code.

Ternary Gradients to Reduce Communication in Distributed Deep Learning (TensorFlow)

Large scale 4D parallelism pre-training for 🤗 transformers in Mixture of Experts *(still work in progress)*

Multi-GPU training for Keras

Distributed training (multi-node) of a Transformer model

SC23 Deep Learning at Scale Tutorial Material

WIP. Veloce is a low-code Ray-based parallelization library that makes machine learning computation novel, efficient, and heterogeneous.

Fast and easy distributed model training examples.

Understanding the effects of data parallelism and sparsity on neural network training

A decentralized and distributed framework for training DNNs

Batch Partitioning for Multi-PE Inference with TVM (2020)

Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation

A SYCL-like kernel compiler for Python

Official Repository for the paper: Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation