Evaluating HPC Job Run Time Predictions Using Application Input Parameters

Author:

Lamar Kenneth1ORCID,Goponenko Alexander2ORCID,Aaziz Omar3ORCID,Allan Benjamin A4ORCID,Brandt James M4ORCID,Dechev Damian1ORCID

Affiliation:

1. University of Central Florida, Orlando, Florida, USA

2. University of Central Florida, Orlando, Florida, United States of America

3. Sandia National Laboratories, Albuquerque, New Mexico, United States of America

4. Sandia National Laboratories, Albuquerque, New Mexico, USA

Publisher

ACM

Reference23 articles.

1. Modeling Expected Application Runtime for Characterizing and Assessing Job Performance

2. Anthony Michael Agelastos Mahesh Rajan Nathan Wichmann Randy Baker Stefan P. Domino Erik W. Draeger Sarah Anderson Jacob Balma S. Behling Mike Berry Pierre Carrier Mike Davis Kim McMahon D. Sandness Kevin Thomas S. Warren and T. Zhu. 2017. Performance on Trinity Phase 2 (a Cray XC40 utilizing Intel Xeon Phi processors) with Acceptance Applications and Benchmarks. (5 2017). https://www.osti.gov/biblio/1457905 Anthony Michael Agelastos Mahesh Rajan Nathan Wichmann Randy Baker Stefan P. Domino Erik W. Draeger Sarah Anderson Jacob Balma S. Behling Mike Berry Pierre Carrier Mike Davis Kim McMahon D. Sandness Kevin Thomas S. Warren and T. Zhu. 2017. Performance on Trinity Phase 2 (a Cray XC40 utilizing Intel Xeon Phi processors) with Acceptance Applications and Benchmarks. (5 2017). https://www.osti.gov/biblio/1457905

3. SW Runtime Estimation using Automata Theory and Deep Learning on HPC

4. Co design center for Particle Applications. 2017. ExaMiniMD. https://github.com/ECP-copa/ExaMiniMD. Co design center for Particle Applications. 2017. ExaMiniMD. https://github.com/ECP-copa/ExaMiniMD.

5. Joseph Emeras , Sébastien Varrette , Mateusz Guzek , and Pascal Bouvry . 2017 . Evalix: Classification and Prediction of Job Resource Consumption on HPC Platforms. In Job Scheduling Strategies for Parallel Processing , Narayan Desai and Walfredo Cirne (Eds.). Springer International Publishing , Cham , 102--122. Joseph Emeras, Sébastien Varrette, Mateusz Guzek, and Pascal Bouvry. 2017. Evalix: Classification and Prediction of Job Resource Consumption on HPC Platforms. In Job Scheduling Strategies for Parallel Processing, Narayan Desai and Walfredo Cirne (Eds.). Springer International Publishing, Cham, 102--122.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. JEM: An AI-based engine workflow to predict simulation’s execution time on HPC cluster;2024 International Conference on Control, Automation and Diagnosis (ICCAD);2024-05-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3