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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
High performance distributed framework for training deep learning recommendation models based on PyTorch.
| Date | Stars |
|---|---|
| 2026-07-31 | 413 |
| 2026-08-06 | 413 |
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<p align="center"> <img width="150px" src="https://user-images.githubusercontent.com/18649508/141604792-b256023d-c751-46d8-bab5-29a207d714ba.png"/> </p> <hr/> <p align="center"> <a href="https://persiaml-tutorials.pages.dev" rel="nofollow"><img src="https://camo.githubusercontent.com/5f2d7c7e08b25fa4f95ce11be89982f25bb81bdef3e15f90b765aa91db371ff6/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7475746f7269616c732d70617373696e672d677265656e" alt="tutorials" data-canonical-src="https://img.shields.io/badge/tutorials-passing-green" style="max-width: 100%;"></a> <a href="https://persiaml.pages.dev" rel="nofollow"><img src="https://camo.githubusercontent.com/bf535e4ed96252a7731419446fe108bb36ce4b91e4960630ceccf31558329193/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f646f63756d656e746174696f6e2d70617373696e672d677265656e" alt="Documentation Status" data-canonical-src="https://img.shields.io/badge/documentation-passing-green" style="max-width: 100%;"></a> <a href="https://badge.fury.io/py/persia" rel="nofollow"><img src="https://camo.githubusercontent.com/d6f9832aba04a67bbb6643eb81bd6be2173e12e51150553f30f16b629f40dc73/68747470733a2f2f62616467652e667572792e696f2f70792f7065727369612e737667" alt="PyPI version" data-canonical-src="https://badge.fury.io/py/persia.svg" style="max-width: 100%;"></a> <a href="https://pypi.org/project/persia/"><img src="https://pepy.tech/badge/persia" alt="PyPI downloads"></a> <a href="https://hub.docker.com/u/persiaml"><img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/persiaml/persia-cuda-runtime"></a> <a href="https://github.com/PersiaML/Persia/blob/main/LICENSE" rel="nofollow"><img src="https://img.shields.io/github/license/PersiaML/Persia" alt="license" style="max-width: 100%;"></a> </p> <div align="center"> <a href="https://github.com/PersiaML/Persia/stargazers"><img src="https://reporoster.com/stars/PersiaML/Persia" /><a/> </div> *WARNING: THIS PROJECT IS CURRENTLY NOT MAINTAINED, DUE TO COMPANY REORGANIZATION.* **PERSIA** (**P**arallel r**E**commendation t**R**aining **S**ystem with hybr**I**d **A**cceleration) is developed by [AI platform@Kuaishou Technology](https://www.kuaishou.com/en), collaborating with ETH. It is a PyTorch-based (the first public one to our best knowledge) system for training large scale deep learning recommendation models on commodity hardwares. It is capable of training recommendation models with up to 100 trillion parameters. To the best of our knowledge, this is the largest model size in recommendation systems so far. Empirical study on public datasets indicate PERSIA's significant advantage over several other existing training systems in recommendation [1]. Its efficiency and robustness have also been validated by multiple applications with 100 million level DAU at Kuaishou. *Disclaimer: The program is usable and has served several important businesses. However, the official English documentation and tutorials are still under heavy construction and they are a bit raw now. We encourage adventurers to try out PERSIA and contribute!* ## News * [Training Deep Learning-based recommender models of 100 trillion parameters over Google Cloud](https://archive.ph/8ay0C) * [突破百万亿参数规模，追求极致的效率和性价比：华人团队开源首个异构并行推荐系统训练框架 PERSIA](https://archive.ph/Mixk0) (In Chinese. Title: Breaking through the trillion parameter scale in pursuit of ultimate efficiency and cost effectiveness: Chinese team open source PERSIA, the first heterogeneous parallel recommendation system) * [参数量卷到一百万亿！华人团队开源史上最大的推荐训练系统 PERSIA](https://archive.md/FbocB) (In Chinese. Title: PERSIA, the Largest Recommended Training System in the History of Open Source by Far) * AI Engines in the "Short-video" Era: Eating 100 Trillion Parameters, Invited talk, Facebook, 2021. * 单机训练速度提升 640 倍！独家解读快手商业广告模型 GPU 训练平台 PERSIA (In Chinese. Title: 640x Faster GPU Based Learning System for Ad Recommendation) * [[AI Front]](https://archive.is/2ii2L) [[中国日报]](https://archive.is/N8fK2) [[InfoQ
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:bd00e01dbbbdae1f, topic:deep-learning, topic:pytorch
matched fp:bd00e01dbbbdae1f, topic:distributed-computing