Hetu: a highly efficient automatic parallel distributed deep learning system
Hetu: a highly efficient automatic parallel distributed deep learning system作者机构：School of Computer Science Peking University Center for Data Science Peking University National Engineering Laboratory for Big Data Analysis and Applications
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2023年第66卷第1期
页 面：314-315页
核心收录：
学科分类：0808[工学-电气工程] 08[工学] 081104[工学-模式识别与智能系统] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
摘 要：On July 18, 2021, the PKU-DAIR Lab1)(Data and Intelligence Research Lab at Peking University) openly released the source code of Hetu, a highly efficient and easy-to-use distributed deep learning(DL) framework. Hetu is the first distributed DL system developed by academic groups in Chinese universities, and takes into account both high availability in industry and innovation in academia. Through independent research and development, Hetu is completely decoupled from the existing DL systems and has unique characteristics. The public release of the Hetu system will help researchers and practitioners to carry out frontier MLSys(machine learning system) research and promote innovation and industrial upgrading.
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