DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Making large AI models cheaper, faster and more accessible
Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.
A state-of-the-art multithreading runtime: message-passing based, fast, scalable, ultra-low overhead
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)
Orkhon: ML Inference Framework and Server Runtime
Distributed training (multi-node) of a Transformer model
Large scale 4D parallelism pre-training for 🤗 transformers in Mixture of Experts *(still work in progress)*
SC23 Deep Learning at Scale Tutorial Material
Deep Learning at Scale Training Event at NERSC
Deep learning for science school material 2025
WIP. Veloce is a low-code Ray-based parallelization library that makes machine learning computation novel, efficient, and heterogeneous.
♨️ Optimized Gaussian blur filter on CPU.
Deep Learning at Scale @ SC25