model-parallelism

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.

A GPipe implementation in PyTorch

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

Slicing a PyTorch Tensor Into Parallel Shards

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

A curated list of awesome projects and papers for distributed training or inference

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

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

Distributed training (multi-node) of a Transformer model

SC23 Deep Learning at Scale Tutorial Material

Distributed training of DNNs • C++/MPI Proxies (GPT-2, GPT-3, CosmoFlow, DLRM)

Deep Learning at Scale Training Event at NERSC

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.

PyTorch implementation of 3D U-Net with model parallel in 2GPU for large model

Adaptive Tensor Parallelism for Foundation Models

Performance Estimates for Transformer AI Models in Science

Official implementation of DynPartition: Automatic Optimal Pipeline Parallelism of Dynamic Neural Networks over Heterogeneous GPU Systems for Inference Tasks