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GreenPar: Scheduling Parallel High Performance Applications in Green Datacenters

Published: 08 June 2015 Publication History

Abstract

We propose GreenPar, a scheduler for parallel high-perormance applications in datacenters partially powered by on-site generation of renewable ("green'') energy. GreenPar schedules the workload to maximize the green energy consumption and minimize the grid ("brown'') energy consumption, while respecting a performance service-level agreement (SLA). When green energy is available, GreenPar increases the resource allocations of active jobs to reduce runtimes. When using brown energy, GreenPar reduces resource allocations within the constraints imposed by the performance SLA to conserve energy. GreenPar makes its decisions based on the speedup profile of each job. We have implemented GreenPar in a real solar-powered datacenter. Our results show that GreenPar can increase the green energy consumption and reduce both the average job runtime and the brown energy consumption, compared to schedulers that are oblivious to on-site green energy.

References

[1]
AISO.net. Web Hosting as Nature Intended, 2012. http://www.aiso.net.
[2]
S. Akoush, R. Sohan, A. Rice, A. Moore, and A. Hopper. Free Lunch: Exploiting Renewable Energy for Computing. In Workshop on hot topics in operating systems (HotOS), 2011.
[3]
B. Aksanli, J. Venkatesh, L. Zhang, and T. Rosing. Utilizing Green Energy Prediction to Schedule Mixed Batch and Service Jobs in Data Centers. In Workshop on Power-Aware Computing and Systems (HotPower), 2011.
[4]
S. Albers and H. Fujiwara. Energy-Efficient Algorithms for Flow Time Minimization. In Symposium on Theoretical Aspects of Computer Science (STACS), 2006.
[5]
Amazon EC2 Pricing. http://aws.amazon.com/ec2, Retrieved on February 2013.
[6]
Apple Inc. Apple Environmental Responsibility Report. https://www.apple.com/environment/reports/docs/apple_environmental_responsibility_report_0714.pdf, 2014.
[7]
P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R. Neugebauer, I. Pratt, and A. Warfield. Xen and the Art of Virtualization. In Symposium on Operating Systems Principles (SOSP), 2003.
[8]
A. Bouteiller, F. Cappello, T. Hérault, G. Krawezik, P. Lemarinier, and F. Magniette. MPICH-V2: a Fault Tolerant MPI for Volatile Nodes based on Pessimistic Sender Based Message Logging. In Supercomputing (SC), 2003.
[9]
J. Corbalan and J. Labarta. Improving Processor Allocation Through Run-time Measured Efficiency. In International Parallel and Distributed Processing Symposium (IPDPS), 2001.
[10]
Data Center Knowledge. Data Centers Scale Up Their Solar Power, 2012. http://www.datacenterknowledge.com/archives/2012/05/14/data-centers-scale-up-their-solarpower.
[11]
Delft University of Technology. The Grid Workloads Archive. http://gwa.ewi.tudelft.nl/pmwiki/pmwiki.php?n=Workloads.Gwa-t-2.
[12]
T. Desell, K. El Maghraoui, and C. A. Varela. Malleable Applications for Scalable High Performance Computing. Cluster Computing, 10(3), 2007.
[13]
Energy Information Administration. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, by State. http://www.eia.gov/electricity/monthly/epm_table_grapher.cfm?t=epmt_5_6_b, Retrieved on January 2013.
[14]
D. Feitelson. Parallel Workload Archive. http://www.cs.huji.ac.il/labs/parallel/workload/l_anl_int/index.html.
[15]
R. Ge and K. Cameron. Power-aware Speedup. In International Parallel and Distributed Processing Symposium (IPDPS), 2007.
[16]
I. Goiri, W. Katsak, K. Le, T. D. Nguyen, and R. Bianchini. Parasol and GreenSwitch: Managing Datacenters Powered by Renewable Energy. In International Conference on Architectural Support for Programming Languages and Operating System (ASPLOS), 2013.
[17]
I. Goiri, K. Le, M. E. Haque, R. Beauchea, T. D. Nguyen, J. Guitart, J. Torres, and R. Bianchini. GreenSlot: Scheduling Energy Consumption in Green Datacenters. In Supercomputing (SC), 2011.
[18]
I. Goiri, K. Le, T. D. Nguyen, J. Guitart, J. Torres, and R. Bianchini. GreenHadoop: Leveraging Green Energy in Data-Processing Frameworks. In European Conference on Computer Systems (EuroSys), 2012.
[19]
Green House Data. An Economically Responsible Data Center, 2012. http://www.greenhousedata.com.
[20]
GreenQloud, 2013. http://greenqloud.com.
[21]
Grid'5000. Grid'5000 Experimentation Platform. www.grid5000.fr.
[22]
Gurobi Optimization Inc. Gurobi Optimization. http://www.gurobi.com.
[23]
M. E. Haque, K. Le, I. Goiri, R. Bianchini, and T. D. Nguyen. Providing Green SLAs in High Performance Computing Clouds. In International Green Computing Conference (IGCC), 2013.
[24]
S. Hazelhurst. Scientific Computing Using Virtual High-performance Computing: A Case Study Using the Amazon Elastic Computing Cloud. In Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists (SAICSIT), 2008.
[25]
Q. Huang, S. Su, J. Li, P. Xu, K. Shuang, and X. Huang. Enhanced Energy-Efficient Scheduling for Parallel Applications in Cloud. In Symposium on Cluster, Cloud, and Grid Computing (CCGRID), 2012.
[26]
W. Huang, J. Liu, B. Abali, and D. K. Panda. A Case for High Performance Computing with Virtual Machines. In International Conference on Supercomputing (ICS), 2006.
[27]
K. Kant, M. Murugan, and D. H.C.Du. Willow: A Control System for Energy and Thermal Adaptive Computing. In International Parallel and Distributed Processing Symposium (IPDPS), 2011.
[28]
J. Koomey. Growth in Data Center Electricity Use 2005 to 2010, 2011. Analytic Press.
[29]
A. Krioukov, C. Goebel, S. Alspaugh, Y. Chen, D. Culler, and R. Katz. Integrating Renewable Energy Using Data Analytics Systems: Challenges and Opportunities. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, March 2011.
[30]
K. Le, O. Bilgir, R. Bianchini, M. Martonosi, and T. D. Nguyen. Capping the Brown Energy Consumption of Internet Services at Low Cost. In International Green Computing Conference (IGCC), 2010.
[31]
C. Li, A. Qouneh, and T. Li. iSwitch: Coordinating and Optimizing Renewable Energy Powered Server Clusters. In International Symposium on Computer Architectur (ISCA), 2012.
[32]
C. Li, R. Wang, T. Li, D. Qian, and J. Yuan. Managing green datacenters powered by hybrid renewable energy systems. In International Conference on Autonomic Computing (ICAC), 2014.
[33]
D. Li, B. De Supinski, M. Schulz, K. Cameron, and D. Nikolopoulos. Hybrid MPI/OpenMP power-aware computing. In International Parallel and Distributed Processing Symposium (IPDPS), 2010.
[34]
Z. Liu, Y. Chen, C. Bash, A. Wierman, D. Gmach, Z. Wang, M. Marwah, and C. Hyser. Renewable and Cooling Aware Workload Management for Sustainable Data Centers. In International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), 2012.
[35]
NASA Advanced Supercomputing Division, Retrieved on December 2013. www.nas.nasa.gov/publications/npb.html.
[36]
T. D. Nguyen, R. Vaswani, and J. Zahorjan. Using Runtime Measured Workload Characteristics in Parallel Processor Scheduling. In Job Scheduling Strategies for Parallel Processing (JSSPP), 1996.
[37]
A. Porterfield, S. Olivier, S. Bhalachandra, and J. Prins. Power Measurement and Concurrency Throttling for Energy Reduction in OpenMP Programs. In International Parallel and Distributed Processing Symposium Workshops PhD Forum (IPDPSW), 2013.
[38]
B. Rountree, D. K. Lowenthal, S. Funk, V. W. Freeh, B. R. de Supinski, and M. Schulz. Bounding Energy Consumption in Large-Scale MPI Programs. In Supercomputing (SC), 2007.
[39]
M. Shantharam, Y. Youn, and P. Raghavan. Speedup-Aware Co-Schedules for Efficient Workload Management. Parallel Processing Letters, 23(02), 2013.
[40]
N. Sharma, J. Gummeson, D. Irwin, and P. Shenoy. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems. In International Conference on Sensor Mesh and Ad Hoc Communications and Networks (SECON), 2010.
[41]
C. Stewart and K. Shen. Some Joules Are More Precious Than Others: Managing Renewable Energy in the Datacenter. In Workshop on Power Aware Computing and Systems (HotPower), 2009.
[42]
G. Utrera, J. Corbalan, and J. Labarta. Implementing Malleability on MPI Jobs. In International Conference on Parallel Architectures and Compilation Techniques (PACT), 2004.

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  • (2022)Infrastructure Aware Heterogeneous-Workloads Scheduling for Data Center Energy Cost MinimizationIEEE Transactions on Cloud Computing10.1109/TCC.2020.297704010:2(972-983)Online publication date: 1-Apr-2022
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cover image ACM Conferences
ICS '15: Proceedings of the 29th ACM on International Conference on Supercomputing
June 2015
446 pages
ISBN:9781450335591
DOI:10.1145/2751205
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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Publication History

Published: 08 June 2015

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Author Tags

  1. datacenters
  2. energy-aware scheduling
  3. renewable energy

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  • Research-article

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ICS'15
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ICS'15: 2015 International Conference on Supercomputing
June 8 - 11, 2015
California, Newport Beach, USA

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ICS '15 Paper Acceptance Rate 40 of 160 submissions, 25%;
Overall Acceptance Rate 629 of 2,180 submissions, 29%

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Cited By

View all
  • (2024)CloudSimPer: Simulating Geo-Distributed Datacenters Powered by Renewable Energy MixIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2024.335753235:4(531-547)Online publication date: Apr-2024
  • (2022)Harnessing Task Usage Prediction and Latency Sensitivity for Scheduling Workloads in Wind-Powered Data CentersEnergies10.3390/en1512446915:12(4469)Online publication date: 19-Jun-2022
  • (2022)Infrastructure Aware Heterogeneous-Workloads Scheduling for Data Center Energy Cost MinimizationIEEE Transactions on Cloud Computing10.1109/TCC.2020.297704010:2(972-983)Online publication date: 1-Apr-2022
  • (2022)GreenPacker: renewable- and fragmentation-aware VM placement for geographically distributed green data centersThe Journal of Supercomputing10.1007/s11227-021-03891-578:1(1434-1457)Online publication date: 1-Jan-2022
  • (2021)GreenHetero: Adaptive Power Allocation for Heterogeneous Green Datacenters2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS51616.2021.00024(160-170)Online publication date: Jul-2021
  • (2019)MILP formulations for spatio-temporal thermal-aware scheduling in Cloud and HPC datacentersCluster Computing10.1007/s10586-019-02931-3Online publication date: 27-Apr-2019
  • (2018)Performance & Energy Tradeoffs for Dependent Distributed Applications Under System-wide Power CapsProceedings of the 47th International Conference on Parallel Processing10.1145/3225058.3225098(1-11)Online publication date: 13-Aug-2018
  • (2018)JouleMR: Towards Cost-Effective and Green-Aware Data Processing FrameworksIEEE Transactions on Big Data10.1109/TBDATA.2017.26550374:2(258-272)Online publication date: 1-Jun-2018
  • (2018)GreenSprint: Effective Computational Sprinting in Green Data Centers2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS.2018.00078(690-699)Online publication date: May-2018
  • (2017)GPaaScalerProceedings of the10th International Conference on Utility and Cloud Computing10.1145/3147213.3147227(79-89)Online publication date: 5-Dec-2017
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