Adaptive and transparent task scheduling of GPU ‐powered clusters-Reference-Cited by-同舟云学术

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Adaptive and transparent task scheduling of GPU ‐powered clusters

Published:2020-04-24 Issue: Volume: Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Ci Qingyu¹^ORCID,Li Hourong¹,Yang Shuwei¹,Gao Jin¹

Affiliation:

1. School of Computer EngineeringWeifang University Weifang China

Funder

Ministry of Education of the People's Republic of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5793

Reference33 articles.

1. NieB. GPGPU reliability analysis: from applications to large scale systems. (Dissertation). ProQuest Dissertations Publishing;2019.

2. Belviranli Mehmet E. andJeffrey S.Vetter. FLAME: graph‐based hardware representations for rapid and precise performance modeling. Paper presented at: Proceedings of the 2019 Design Automation & Test in Europe Conference & Exhibition (DATE);2019; IEEE.

3. Feng J. Liu G. Zhang J. Zhang Z. Yu J. &Zhang Z. Workload characterization and evolutionary analyses of tianhe‐1a supercomputer. Paper presented at: Proceedings of the International Conference on Computational Science;2018; Springer Cham.

4. Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

5. Dehal R. S. Munjal C. Ansari A. A. &Kushwaha A. S. GPU computing revos lution: CUDA. Paper presented at: Proceeding of the 2018 International Conference on Advances in Computing Communication Control and Networking (ICACCCN);2018; IEEE.

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1. Smart Scheduling in Cloudlet Federation;2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC);2023-03-08

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