首页|A Survey on Task Scheduling of CPU-GPU Heterogeneous Cluster

A Survey on Task Scheduling of CPU-GPU Heterogeneous Cluster

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This paper reviews task scheduling frameworks,methods,and evaluation metrics of central processing unit-graphics processing unit (CPU-GPU) heterogeneous clusters. Task scheduling of CPU-GPU heterogeneous clusters can be carried out on the system level,node-level,and device level. Most task-scheduling technologies are heuristic based on the experts' experience,while some technologies are based on statistic methods using machine learning,deep learning,or reinforcement learning. Many metrics have been adopted to evaluate and com-pare different task scheduling technologies that try to optimize different goals of task scheduling. Although statistic task scheduling has reached fewer research achievements than heuristic task scheduling,the statistic task scheduling still has significant research potential.

CPU-GPU heterogeneous clustertask schedulingheuristic task schedulingstatistic task schedulingparallelization

ZHOU Yiheng、ZENG Wei、ZHENG Qingfang、LIU Zhilong、CHEN Jianping

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University of Shanghai for Science and Technology,Shanghai 200093,China

National Key Laboratory for Multimedia Information Processing,School of Computer Science,Peking University,Beijing 100871,China

State Key Laboratory of Mobile Network and Mobile Multimedia Technology,Shenzhen 518055,China

ZTE Corporation,Shenzhen 518057,China

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2024

中兴通讯技术(英文版)
中兴通讯股份有限公司,安徽省科技情报研究所

中兴通讯技术(英文版)

影响因子:0.036
ISSN:1673-5188
年,卷(期):2024.22(3)