short-paper

Simulation of Auction Mechanism Model for Energy-Efficient High Performance Computing

Authors:

Kazutomo YoshiiAuthors Info & Claims

SIGSIM-PADS '20: Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

Pages 99 - 104

https://doi.org/10.1145/3384441.3395991

Published: 15 June 2020 Publication History

Abstract

High performance computing (HPC) systems are large-scale computing systems with thousands of compute nodes. Massive energy consumption is a critical issue for HPC systems. In this paper, we develop an auction mechanism model for energy consumption reduction in an HPC system. Our proposed model includes an optimized resource allocation scheme for HPC jobs based on processor frequency and a Vickery-Clarke-Groove (VCG)-based forward auction model to enable energy reduction participation from HPC users. The model ensures truthful participation from HPC users, where users benefit from revealing their true valuation of energy reduction. We implement a job scheduler simulator and our mechanism model on a parallel discrete-event simulation engine. Through trace-based simulation, we demonstrate the effectiveness of our auction mechanism model. Simulation shows that our model can achieve overall energy reduction for an HPC system, while ensuring truthful participation from the users.

References

[1]

Kishwar Ahmed and Jason Liu. 2019. Simulation of Energy-Efficient Demand Response for High Performance Computing Systems. In 2019 Winter Simulation Conference (WSC). Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 2560--2571.

[2]

Kishwar Ahmed, Jason Liu, and Xingfu Wu. 2017. An Energy Efficient Demand-Response Model for High Performance Computing Systems. In Proceedings of the 2017 IEEE 25th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 175--186.

[3]

Kishwar Ahmed, Jason Liu, and Kazutomo Yoshii. 2018. Enabling Demand Response for HPC Systems through Power Capping and Node Scaling. In Proceedings of the 2018 IEEE 16th International Conference on High Performance Computing and Communications (HPCC). Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 789--796.

[4]

Aniti, Lori. 2019. Demand-side management programs save energy and reduce peak demand. https://www.eia.gov/todayinenergy/detail.php?id=38872#. accessed 17textsuperscriptth February 2020.

[5]

Axel Auweter, Arndt Bode, Matthias Brehm, Luigi Brochard, Nicolay Hammer, Herbert Huber, Raj Panda, Francois Thomas, and Torsten Wilde. 2014. A Case Study of Energy Aware Scheduling on SuperMUC. In International Supercomputing Conference. Springer, New York, NY, 394--409.

Digital Library

[6]

Wenlei Bao, Changwan Hong, Sudheer Chunduri, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, and P Sadayappan. 2016. Static and dynamic frequency scaling on multicore CPUs. ACM Transactions on Architecture and Code Optimization (TACO), Vol. 13, 4 (2016), 51.

[7]

Thang Cao, Yuan He, and Masaaki Kondo. 2016. Demand-Aware Power Management for Power-Constrained HPC Systems. In Cluster, Cloud and Grid Computing (CCGrid), 2016 16th IEEE/ACM International Symposium on. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 21--31.

[8]

Stéphane Caron and George Kesidis. 2010. Incentive-based energy consumption scheduling algorithms for the smart grid. In 2010 First IEEE International Conference on Smart Grid Communications. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 391--396.

[9]

Yanjiao Chen, Jin Zhang, Qian Zhang, and Juncheng Jia. 2012. A reverse auction framework for access permission transaction to promote hybrid access in femtocell network. In 2012 Proceedings IEEE INFOCOM. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 2761--2765.

[10]

Wei Dong, Swati Rallapalli, Rittwik Jana, Lili Qiu, KK Ramakrishnan, Leo Razoumov, Yin Zhang, and Tae Won Cho. 2013. iDEAL: Incentivized dynamic cellular offloading via auctions. IEEE/ACM Transactions on Networking, Vol. 22, 4 (2013), 1271--1284.

Digital Library

[11]

Maja Etinski, Julita Corbalan, Jesus Labarta, and Mateo Valero. 2012. Parallel job scheduling for power constrained HPC systems. Parallel Comput., Vol. 38, 12 (2012), 615--630.

Digital Library

[12]

Vincent W Freeh, Feng Pan, Nandini Kappiah, David K Lowenthal, and Robert Springer. 2005. Exploring the energy-time tradeoff in MPI programs on a power-scalable cluster. In Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 10--pp.

Digital Library

[13]

Rong Ge, Xizhou Feng, Wu-chun Feng, and Kirk W Cameron. 2007. CPU MISER: A performance-directed, run-time system for power-aware clusters. In Parallel Processing, 2007. ICPP 2007. International Conference on. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 18--18.

Digital Library

[14]

Yiannis Georgiou, David Glesser, Krzysztof Rzadca, and Denis Trystram. 2015. A Scheduler-Level Incentive Mechanism for Energy Efficiency in HPC. In Proceedings of the Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 617--626.

Digital Library

[15]

Sha Hua, Xuejun Zhuo, and Shivendra S Panwar. 2013. A truthful auction based incentive framework for femtocell access. In 2013 IEEE Wireless Communications and Networking Conference (WCNC). Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 2271--2276.

[16]

Curtis L Janssen, Helgi Adalsteinsson, Scott Cranford, Joseph P Kenny, Ali Pinar, David A Evensky, and Jackson Mayo. 2012. A simulator for large-scale parallel computer architectures. Technology Integration Advancements in Distributed Systems and Computing, Vol. 1, 2 (2012), 57--73.

Digital Library

[17]

Feng Liu and Jon B Weissman. 2015. Elastic Job Bundling: An Adaptive Resource Request Strategy for Large-Scale Parallel Applications. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. Association for Computing Machinery, New York, NY, 33.

Digital Library

[18]

Liu, Jason. 2019. Simulus - A Discrete-Event Simulator in Python. https://simulus.readthedocs.io/en/latest/#. accessed 15textsuperscriptth November 2019.

[19]

Ludwig, and Dolz. 2014. Total Cost of Ownership in High Performance Computing. https://wr.informatik.uni-hamburg.de/_media/teaching/sommersemester_2014/tco-14-anna-lena_pdf.pdf. accessed 7textsuperscriptth April 2019.

[20]

Parallel Systems Lab. 2010. Python Scheduler Simulator. https://code.google.com/archive/p/pyss/. accessed 10textsuperscriptth April 2017.

[21]

Rice University. 2019. High performance computing user fees. https://docs.rice.edu/confluence/display/CD/User+Fees. accessed 17th February 2020.

[22]

Barry Rountree, David K Lownenthal, Bronis R De Supinski, Martin Schulz, Vincent W Freeh, and Tyler Bletsch. 2009. Adagio: making DVS practical for complex HPC applications. In Proceedings of the 23rd international conference on Supercomputing. Association for Computing Machinery, New York, NY, 460--469.

Digital Library

[23]

W. Tang, Z. Lan, N. Desai, and D. Buettner. 2009. Fault-Aware, Utility-Based Job Scheduling on Blue, Gene/P Systems. In Proceedings of the 2009 IEEE International Conference on Cluster Computing and Workshops. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 1--10.

[24]

W. Tang, D. Ren, Z. Lan, and N. Desai. 2012. Adaptive Metric-Aware Job Scheduling for Production Supercomputers. In Proceedings of the 2012 41st International Conference on Parallel Processing Workshops. Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 107--115. https://doi.org/10.1109/ICPPW.2012.17

[25]

TOP500.org. 2019. Top 500 list. https://www.top500.org/list/2019/11/. accessed 14textsuperscriptth January 2020.

[26]

Dejun Yang, Xi Fang, and Guoliang Xue. 2012a. Truthful auction for cooperative communications with revenue maximization. In 2012 IEEE International Conference on Communications (ICC). Institute of Electrical and Electronics Engineers, Inc., Piscataway, New Jersey, 4888--4892.

[27]

Dejun Yang, Guoliang Xue, Xi Fang, and Jian Tang. 2012b. Crowdsourcing to smartphones: Incentive mechanism design for mobile phone sensing. In Proceedings of the 18th annual international conference on Mobile computing and networking. Association for Computing Machinery, New York, NY, 173--184.

Digital Library

Cited By

Hong YZheng ZWang Z(2024)A Multi-Dimensional Reverse Auction Mechanism for Volatile Federated Learning in the Mobile Edge Computing SystemsElectronics10.3390/electronics1316315413:16(3154)Online publication date: 9-Aug-2024
https://doi.org/10.3390/electronics13163154
Solórzano ASato KYamamoto KShoji FBrandt JSchwaller BWalton SGreen JTiwari D(2024)Toward Sustainable HPC: In-Production Deployment of Incentive-Based Power Efficiency Mechanism on the Fugaku SupercomputerProceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis10.1109/SC41406.2024.00030(1-16)Online publication date: 17-Nov-2024
https://dl.acm.org/doi/10.1109/SC41406.2024.00030
Xu JTang BCui HYe B(2024)An Uncertainty-Aware Auction Mechanism for Federated LearningAlgorithms and Architectures for Parallel Processing10.1007/978-981-97-0811-6_1(1-18)Online publication date: 27-Feb-2024
https://doi.org/10.1007/978-981-97-0811-6_1
Show More Cited By

Index Terms

Simulation of Auction Mechanism Model for Energy-Efficient High Performance Computing
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies
    2. Simulation types and techniques
      1. Discrete-event simulation
2. Hardware
  1. Power and energy
    1. Power estimation and optimization
      1. Enterprise level and data centers power issues

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Published In

cover image ACM Conferences

SIGSIM-PADS '20: Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

June 2020

204 pages

ISBN:9781450375924

DOI:10.1145/3384441

General Chair:
Jason Liu
Florida International University, USA
,
Program Chairs:
Philippe Giabbanelli
Miami University, USA
,
Christopher Carothers
Rensselaer Polytechnic Institute, USA

Copyright © 2020 ACM.

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Published: 15 June 2020

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SIGSIM-PADS '20

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SIGSIM-PADS '20: SIGSIM Principles of Advanced Discrete Simulation

June 15 - 17, 2020

FL, Miami, Spain

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Overall Acceptance Rate 398 of 779 submissions, 51%

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Cited By

Hong YZheng ZWang Z(2024)A Multi-Dimensional Reverse Auction Mechanism for Volatile Federated Learning in the Mobile Edge Computing SystemsElectronics10.3390/electronics1316315413:16(3154)Online publication date: 9-Aug-2024
https://doi.org/10.3390/electronics13163154
Solórzano ASato KYamamoto KShoji FBrandt JSchwaller BWalton SGreen JTiwari D(2024)Toward Sustainable HPC: In-Production Deployment of Incentive-Based Power Efficiency Mechanism on the Fugaku SupercomputerProceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis10.1109/SC41406.2024.00030(1-16)Online publication date: 17-Nov-2024
https://dl.acm.org/doi/10.1109/SC41406.2024.00030
Xu JTang BCui HYe B(2024)An Uncertainty-Aware Auction Mechanism for Federated LearningAlgorithms and Architectures for Parallel Processing10.1007/978-981-97-0811-6_1(1-18)Online publication date: 27-Feb-2024
https://doi.org/10.1007/978-981-97-0811-6_1
Bustos ACascajo ARubio-Montero AGarcía-Bustamante EMoriñigo JSingh DCarretero JMayo-Garcia R(2022)Energy Consumption Studies of WRF Executions with the LIMITLESS MonitorHigh Performance Computing10.1007/978-3-031-04209-6_2(19-33)Online publication date: 12-Apr-2022
https://doi.org/10.1007/978-3-031-04209-6_2
Ahmed KYoshii KTasnim S(2021)Parallel application power and performance prediction modeling using simulationProceedings of the Winter Simulation Conference10.5555/3522802.3522980(1-12)Online publication date: 13-Dec-2021
https://dl.acm.org/doi/10.5555/3522802.3522980
Ahmed KYoshii KTasnim S(2021)Parallel Application Power and Performance Prediction Modeling Using Simulation2021 Winter Simulation Conference (WSC)10.1109/WSC52266.2021.9715340(1-12)Online publication date: 12-Dec-2021
https://doi.org/10.1109/WSC52266.2021.9715340
Ahmed KTasnim SYoshii K(2020)Energy-Efficient Heterogeneous Computing of Parallel Applications via Power Capping2020 International Conference on Computational Science and Computational Intelligence (CSCI)10.1109/CSCI51800.2020.00231(1237-1242)Online publication date: Dec-2020
https://doi.org/10.1109/CSCI51800.2020.00231

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