GARLSched: Generative adversarial deep reinforcement learning task scheduling optimization for large-scale high performance computing systems

Efficient task scheduling has become increasingly complex as the number and type of tasks proliferate and the size of computing resource grows in large-scale distributed high-performance computing (HPC) systems. At present, deep reinforcement learning (DRL) methods have achieved certain success in s...

Celý popis

Podrobná bibliografie

Vydáno v:	Future generation computer systems Ročník 135; s. 259 - 269
Hlavní autoři:	Li, Jingbo, Zhang, Xingjun, Wei, Jia, Ji, Zeyu, Wei, Zheng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.10.2022
Témata:	Deep reinforcement learning Distributed systems Expert guidance High performance computing Task scheduling Task scheduling Deep reinforcement learning Expert guidance High performance computing Distributed systems
ISSN:	0167-739X, 1872-7115
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!