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Optimal scheduling of in-situ analysis for large-scale scientific simulations

Authors:

Preeti Malakar,

Venkatram Vishwanath,

Christopher Knight,

Sven Leyffer, and

Michael E. PapkaAuthors Info & Claims

SC '15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

November 2015

Article No.: 52, Pages 1 - 11

https://doi.org/10.1145/2807591.2807656

Published: 15 November 2015 Publication History

Abstract

Today's leadership computing facilities have enabled the execution of transformative simulations at unprecedented scales. However, analyzing the huge amount of output from these simulations remains a challenge. Most analyses of this output is performed in post-processing mode at the end of the simulation. The time to read the output for the analysis can be significantly high due to poor I/O bandwidth, which increases the end-to-end simulation-analysis time. Simulation-time analysis can reduce this end-to-end time. In this work, we present the scheduling of in-situ analysis as a numerical optimization problem to maximize the number of online analyses subject to resource constraints such as I/O bandwidth, network bandwidth, rate of computation and available memory. We demonstrate the effectiveness of our approach through two application case studies on the IBM Blue Gene/Q system.

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Cited By

Loring BBethel EWeber GMahoney M(2023)Extensions to the SENSEI In situ Framework for Heterogeneous ArchitecturesProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624161(868-874)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624161
Honore VDo TPottier LDa Silva RDeelman ESuter F(2022)SIM-SITU: A Framework for the Faithful Simulation of in situ Processing2022 IEEE 18th International Conference on e-Science (e-Science)10.1109/eScience55777.2022.00032(182-191)Online publication date: Oct-2022
https://doi.org/10.1109/eScience55777.2022.00032
Wang ZDorier MParashar M(2022)Research Perspectives Toward Autonomic Optimization of In Situ Analysis and Visualization2022 IEEE/ACM International Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV)10.1109/ISAV56555.2022.00007(7-13)Online publication date: Nov-2022
https://doi.org/10.1109/ISAV56555.2022.00007
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cover image ACM Conferences

SC '15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

November 2015

985 pages

ISBN:9781450337236

DOI:10.1145/2807591

General Chair:
Jackie Kern
University of Illinois at Urbana-Champaign, Urbana, Illinois
,
Program Chair:
Jeffrey S. Vetter
Oak Ridge National Laboratory and Georgia Institute of Technology, Oak Ridge, Tennessee

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 November 2015

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SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis

November 15 - 20, 2015

Texas, Austin

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SC '15 Paper Acceptance Rate 79 of 358 submissions, 22%;

Overall Acceptance Rate 1,516 of 6,373 submissions, 24%

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Cited By

Loring BBethel EWeber GMahoney M(2023)Extensions to the SENSEI In situ Framework for Heterogeneous ArchitecturesProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624161(868-874)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624161
Honore VDo TPottier LDa Silva RDeelman ESuter F(2022)SIM-SITU: A Framework for the Faithful Simulation of in situ Processing2022 IEEE 18th International Conference on e-Science (e-Science)10.1109/eScience55777.2022.00032(182-191)Online publication date: Oct-2022
https://doi.org/10.1109/eScience55777.2022.00032
Wang ZDorier MParashar M(2022)Research Perspectives Toward Autonomic Optimization of In Situ Analysis and Visualization2022 IEEE/ACM International Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV)10.1109/ISAV56555.2022.00007(7-13)Online publication date: Nov-2022
https://doi.org/10.1109/ISAV56555.2022.00007
Huang DQin ZLiu QPodhorszki NKlasky S(2022)Identifying Challenges and Opportunities of In-Memory Computing on Large HPC SystemsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.02.002Online publication date: Feb-2022
https://doi.org/10.1016/j.jpdc.2022.02.002
Malakar PVishwanath VKnight CMunson TPapka M(2022)Resource-Aware Optimal Scheduling of In Situ AnalysisIn Situ Visualization for Computational Science10.1007/978-3-030-81627-8_9(183-202)Online publication date: 5-May-2022
https://doi.org/10.1007/978-3-030-81627-8_9
Foster IAinsworth MBessac JCappello FChoi JDi SDi ZGok AGuo HHuck KKelly CKlasky SKleese van Dam KLiang XMehta KParashar MPeterka TPouchard LShu TTugluk Ovan Dam HWan LWolf MWozniak JXu WYakushin IYoo SMunson T(2021)Online data analysis and reduction: An important Co-design motif for extreme-scale computersThe International Journal of High Performance Computing Applications10.1177/10943420211023549(109434202110235)Online publication date: 12-Jun-2021
https://doi.org/10.1177/10943420211023549
Larsen MHarrison CTurton TSane SBrink SChilds H(2021)Trigger Happy: Assessing the Viability of Trigger-Based In Situ Analysis2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV)10.1109/LDAV53230.2021.00010(22-31)Online publication date: Oct-2021
https://doi.org/10.1109/LDAV53230.2021.00010
Mehta KAllen BWolf MLogan JSuchyta ESinghal SChoi JTakahashi KHuck KYakushin ISussman AMunson TFoster IKlasky S(2021)A codesign framework for online data analysis and reductionConcurrency and Computation: Practice and Experience10.1002/cpe.651934:14Online publication date: 26-Aug-2021
https://doi.org/10.1002/cpe.6519
Qiao ZLiu QPodhorszki NKlasky SChen J(2020)Taming I/O Variation on QoS-Less HPC Storage: What Can Applications Do?SC20: International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SC41405.2020.00015(1-13)Online publication date: Nov-2020
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Kress JLarsen MChoi JKim MWolf MPodhorszki NKlasky SChilds HPugmire D(2020)Comparing Time-to-Solution for In Situ Visualization Paradigms at Scale2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV)10.1109/LDAV51489.2020.00009(22-26)Online publication date: Oct-2020
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