Efficient Mask-Aware Distributed Attention for Long-Context Training
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Distributed Task Queue (development branch)
《Designing Data-Intensive Application》DDIA 第一版 / 第二版 中文翻译
A hyperparameter optimization framework
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
Build, Manage and Deploy AI/ML Systems
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Open-source implementation of AlphaEvolve
Distributed Asynchronous Hyperparameter Optimization in Python
Centralized network visibility and continuous asset discovery. Monitor devices, detect change, and stay aware across distributed networks.
Real-time monitor and web admin for Celery distributed task queue
Introduce technologies on blockchain and distributed ledger, from theory to practice with bitcoin, ethereum and hyperledger.
《深入理解 AI Infra:量化分析与系统设计》(李博杰 著)开源书稿:从硬件约束和模型架构出发,量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验
Democratizing Reinforcement Learning for LLMs
A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
A fast and reliable background task processing library for Python 3.
Achieve state of the art inference performance with modern accelerators on Kubernetes
Symbolic Learning in Python and Julia
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
A high-performance distributed training framework for Reinforcement Learning
Lingvo
OpenTelemetry Python API and SDK
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Distributed self-replicating programs in Python
Machine learning metrics for distributed, scalable PyTorch applications.
Distributed task queue with full async support
VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo
Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
pytest plugin for distributed testing and loop-on-failures testing modes.
Python Stream Processing. A Faust fork
Ansible playbooks to deploy Ceph, the distributed filesystem.
An open, distributed platform as a service
A distributed task scheduler for Dask
A library for event sourcing in Python.
DLRover: An Automatic Distributed Deep Learning System
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
A crowdsourced distributed cluster for AI art and text generation
SGLang-Omni is a high-performance serving framework for audio models (TTS, ASR) and unified multimodal models.
Examples of programs built using Modal
Redis for humans. 🌎🌍🌏
Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
Docker Swarm mode rocks! Ideas, tools and recipes. Get a production-ready, distributed, HTTPS served, cluster in minutes, not weeks.
🚀 Pytorch Distributed native training library for LLMs/VLMs with OOTB Hugging Face support
A Distributed Attention Towards Linear Scalability for Ultra-Long Context, Heterogeneous Data Training
The complete post-training stack for LLMs, plus RL for any problem. SFT, DPO and multi-turn agentic RL, with evolutionary hyperparameter optimization built in.
Operating System for Enterprise Blockchain
Examples for https://github.com/optuna/optuna
Halo is an open-source framework built by White Circle for training large language and multimodal models
Unleash the power of cloud
brozzler - distributed browser-based web crawler
A universal, distributed and secure messaging protocol for Reticulum
Distributed version-control for geospatial and tabular data
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, Gaudi NPU, Google TPU, GraphCore IPU and other NPUs.
An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale