article

Joint frequency scaling of processor and DRAM

Authors:

Vaibhav Sundriyal,

Masha SosonkinaAuthors Info & Claims

The Journal of Supercomputing, Volume 72, Issue 4

Pages 1549 - 1569

https://doi.org/10.1007/s11227-016-1680-4

Published: 01 April 2016 Publication History

Abstract

Energy efficiency and energy-proportional computing have become a central focus in modern supercomputers. Many previous energy-saving strategies have focused solely on the CPU while the DRAM subsystem has not been addressed sufficiently, even though memory consumes about 20 % of the total power in a typical server platform. This paper describes a novel runtime system that scales the frequency of both processor and DRAM-based on the performance and power models, also proposed here. Specifically, first, a performance-loss constraint is chosen for an application, then, an optimal processor---DRAM frequency pair is modeled such that the pair minimizes the energy consumption in a given timeslice. Experiments performed on SPEC CPU™ 2006, NAS NPB, and pARMS benchmarks demonstrate that the proposed runtime system may obtain total energy savings both for memory- and compute-intensive applications. In particular, as much as 22 % of energy was saved with a low performance loss of about 4.8 %.

References

[1]

Begum R, Werner D, Hempstead M, Prasad G, Challen G (2015) Energy-performance trade-offs on energy-constrained devices with multi-component DVFS. In: Workload Characterization (IISWC), 2015 IEEE International Symposium on, pp 34---43, Oct 2015

Digital Library

[2]

Borkar S (2001) The exascale challenge, 2011. Keynote speech. In: the 12th International Conference on Parallel Architectures and Compilation Techniques

[3]

Chen YJ, Yang CL, Lin PS, Lu YC (2015) Thermal/performance characterization of CMPs with 3D-stacked DRAMs under synergistic voltage-frequency control of cores and DRAMs. In: Proceedings of the 2015 Conference on Research in Adaptive and Convergent Systems, RACS, pp 430---436, New York, NY, USA, 2015. ACM

[4]

David H, Fallin C, Gorbatov E, Hanebutte UR, Mutlu O (2011) Memory power management via dynamic voltage/frequency scaling. In: Proceedings of the 8th ACM International Conference on Autonomic Computing, pp 31---40

[5]

Deng Q, Meisner D, Bhattacharjee A, Wenisch TF, Bianchini R (2012) Coscale: coordinating cpu and memory system DVFS in server systems. In: Microarchitecture (MICRO), 2012 45th Annual IEEE/ACM International Symposium on, pp 143---154, Dec 2012

Digital Library

[6]

Etinski M, Corbalan J, Labarta J, Valero M, Veidenbaum A (2009) Power-aware load balancing of large scale MPI applications. In Parallel Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on, pp 1---8, May 2009

[7]

Freeh VW, Lowenthal DK (2005) Using multiple energy gears in MPI programs on a power-scalable cluster. In: Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming, pp 164---173

[8]

Ge R, Feng X, Feng W, Cameron KW (2007) CPU MISER: A performance-directed, run-time system for power-aware clusters. In: Parallel Processing, 2007. ICPP 2007. International Conference on, pp 18, Sep. 2007

[9]

Ge R, Feng X, Song S, Chang HC, Li D, Cameron KW (2010) PowerPack: energy profiling and analysis of high-performance systems and applications. Parallel Distrib Syst IEEE Trans 21:658---671

Digital Library

[10]

Gonzales R, Horowitz M (1995) Energy dissipation in general purpose processors. IEEE J Solid State Circuits 31:1277---1284

[11]

Hackenberg D, Schone R, Ilsche T, Molka D, Schuchart J, Geyer R (2015) An energy efficiency feature survey of the intel haswell processor. In: Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International, pp 896---904, May 2015

Digital Library

[12]

Hennessy JL, Patterson DA (2011) Computer architecture: a quantitative approach (appendix B), 5th edn. Morgan Kaufmann Publishers Inc., San Francisco

[13]

Henning JL (2006) SPEC CPU2006 benchmark descriptions. SIGARCH Comput Archit News 34(4):1---17

Digital Library

[14]

Hsu CH, Feng W (2005) A power-aware run-time system for high-performance computing. In Supercomputing. In: Proceedings of the ACM/IEEE SC 2005 Conference, pp 1, Nov. 2005

[15]

Huang S, Feng W (2009) Energy-efficient cluster computing via accurate workload characterization. In: Cluster Computing and the Grid, 2009. CCGRID'09. 9th IEEE/ACM International Symposium on, pp 68---75, May 2009

Digital Library

[16]

Iancu C, Hofmeyr S, Blagojevic F, Zheng Y (2010) Oversubscription on multicore processors. In: Parallel Distributed Processing (IPDPS), 2010 IEEE International Symposium on, pp 1---11

[17]

Intel 64 and IA-32 architectures software developer's manual combined volumes 3A, 3B, and 3C: System programming guide. http://www.intel.com/content/dam/www/public/us/en/documents/manuals/64-ia-32-architectures-software-developer-manual-325462.pdf

[18]

Ioannou N, Kauschke M, Gries M, Cintra M (2011) Phase-based application-driven hierarchical power management on the single-chip cloud computer. In: Parallel Architectures and Compilation Techniques (PACT), 2011 International Conference on, pp 131---142, Oct. 2011

[19]

Kandalla K, Mancini EP, Sur S, Panda DK (2010) Designing power-aware collective communication algorithms for InfiniBand clusters. In: Parallel Processing (ICPP), 2010 39th International Conference on, pp 218---227

Digital Library

[20]

Lefurgy C, Rajamani K, Rawson F, Felter W, Kistler M, Keller TW (2003) Energy management for commercial servers. Computer 36(12):39---48

Digital Library

[21]

Li Z, Saad Y, Sosonkina M (2003) pARMS: a parallel version of the algebraic recursive multilevel solver. Numer Linear Algebra Appl 10:485---509

[22]

Lim MY, Freeh VW, Lowenthal DK (2006) Adaptive, transparent frequency and voltage scaling of communication phases in MPI programs. In: Proceedings of the 2006 ACM/IEEE conference on Supercomputing

[23]

Mills N, Mills E (2015) Taming the energy use of gaming computers. Energy Efficiency 1---18.

[24]

Mittal S (2014) A survey of techniques for improving energy efficiency in embedded computing systems. Int J Comput Aided Eng Technol (IJACET) 6:440---459

[25]

Moscibroda T, Mutlu O (2007) Memory performance attacks: Denial of memory service in multi-core systems. In: Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium, SS'07, pp 18:1---18:18, Berkeley, CA, USA, 2007. USENIX Association

[26]

Park J, Shin D, Chang N, Pedram M (2010) Accurate modeling and calculation of delay and energy overheads of dynamic voltage scaling in modern high-performance microprocessors. In: 2010 International Symposium on Low-Power Electronics and Design (ISLPED), pp 419---424

[27]

Rountree B, Lownenthal DK, de Supinski BR, Schulz M, Freeh VW, Bletsch T (2009) Adagio: making DVS practical for complex HPC applications. In: Proceedings of the 23rd international conference on Supercomputing, ICS'09, pp 460---469, New York, NY, USA, 2009. ACM

[28]

Saad Y (2003) Iterative methods for sparse linear systems, 2nd edn. SIAM, Philadelpha

[29]

Sosonkina M, Saad Y, Cai X (2004) Using the parallel algebraic recursive multilevel solver in modern physical applications. Future Gener Comput Syst 20:489---500

Digital Library

[30]

Sundriyal V, Sosonkina M (2011) Per-call energy saving strategies in all-to-all communications. In: Proceedings of the 18th European MPI Users' Group conference on Recent advances in the message passing interface, EuroMPI'11, pp 188---197, Berlin, Heidelberg, 2011. Springer-Verlag

Digital Library

[31]

Sundriyal V, Sosonkina M (2013) Initial investigation of a scheme to use instantaneous CPU power consumption for energy savings format. In: Proceedings of the 1st International Workshop on Energy Efficient Supercomputing, E2SC '13, pp 1:1---1:6, New York, NY, USA, 2013. ACM

Digital Library

[32]

Sundriyal V, Sosonkina M, Gaenko A (2012) Runtime procedure for energy savings in applications with point-to-point communications. In: Computer Architecture and High Performance Computing (SBAC-PAD), 2012 IEEE 24th International Symposium on, pp 155---162

[33]

Sundriyal V, Sosonkina M, Zhang Z (2012) Achieving energy efficiency during collective communications. Pract Exp Concurr Comput 25:2140---2156

[34]

Tiwari A., Schulz M, Arrington L (2015) Predicting optimal power allocation for CPU and DRAM domains. In: Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International, pp 951---959, May 2015

Digital Library

[35]

Vishnu A, Song S, Marquez A, Barker K, Kerbyson D, Cameron K, Balaji P (2010) Designing energy efficient communication runtime systems for data centric programming models. In: Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing, GREENCOM-CPSCOM '10, pp 229---236, Washington, DC, USA, 2010. IEEE Computer Society

Digital Library

[36]

Zhang Z, Chang JM (2014) A cool scheduler for multi-core systems exploiting program phases. Comput IEEE Trans 63(5):1061---1073

Digital Library

Cited By

Chen JManivannan MGoel BPericàs M(2023)JOSS: Joint Exploration of CPU-Memory DVFS and Task Scheduling for Energy EfficiencyProceedings of the 52nd International Conference on Parallel Processing10.1145/3605573.3605586(828-838)Online publication date: 7-Aug-2023
https://dl.acm.org/doi/10.1145/3605573.3605586
Kumar SGupta AKumar VBhalachandra Sde Supinski BHall MGamblin T(2021)CuttlefishProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3458817.3476163(1-14)Online publication date: 14-Nov-2021
https://dl.acm.org/doi/10.1145/3458817.3476163
Sundriyal VSosonkina MWestheimer B(2019)Comparing frequency scaling efficacy on different memory technologiesProceedings of the High Performance Computing Symposium10.5555/3338075.3338086(1-10)Online publication date: 29-Apr-2019
https://dl.acm.org/doi/10.5555/3338075.3338086
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Joint frequency scaling of processor and DRAM

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cover image The Journal of Supercomputing

The Journal of Supercomputing Volume 72, Issue 4

April 2016

408 pages

ISSN:0920-8542

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Copyright © Copyright © 2016 Springer Science+Business Media New York.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 April 2016

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Cited By

Chen JManivannan MGoel BPericàs M(2023)JOSS: Joint Exploration of CPU-Memory DVFS and Task Scheduling for Energy EfficiencyProceedings of the 52nd International Conference on Parallel Processing10.1145/3605573.3605586(828-838)Online publication date: 7-Aug-2023
https://dl.acm.org/doi/10.1145/3605573.3605586
Kumar SGupta AKumar VBhalachandra Sde Supinski BHall MGamblin T(2021)CuttlefishProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3458817.3476163(1-14)Online publication date: 14-Nov-2021
https://dl.acm.org/doi/10.1145/3458817.3476163
Sundriyal VSosonkina MWestheimer B(2019)Comparing frequency scaling efficacy on different memory technologiesProceedings of the High Performance Computing Symposium10.5555/3338075.3338086(1-10)Online publication date: 29-Apr-2019
https://dl.acm.org/doi/10.5555/3338075.3338086
Sundriyal VKeipert KSosonkina MGordon M(2019)Effect of frequency scaling granularity on energy-saving strategiesInternational Journal of High Performance Computing Applications10.1177/109434201877440533:4(590-601)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1177/1094342018774405
Ghaemi SAhmadpour IArdebili MFarbeh H(2019)Sleepy-LRUThe Journal of Supercomputing10.1007/s11227-019-02758-075:7(3945-3974)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11227-019-02758-0
Sundriyal VSosonkina MWestheimer BGordon MWatson LSosonkina MThacker WWeinbub J(2018)Comparisons of core and uncore frequency scaling modes in quantum chemistry application GAMESSProceedings of the High Performance Computing Symposium10.5555/3213069.3213082(1-11)Online publication date: 15-Apr-2018
https://dl.acm.org/doi/10.5555/3213069.3213082
Rezaei HAghli Moghaddam SRahmati A(2018)High-performance dynamic elastic pipelinesMicroprocessors & Microsystems10.1016/j.micpro.2017.11.00456:C(113-120)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1016/j.micpro.2017.11.004
Sundriyal VFought ESosonkina MWindus T(2017)Evaluating effects of application based and automatic energy saving strategies on NWChemProceedings of the 25th High Performance Computing Symposium10.5555/3108096.3108112(1-12)Online publication date: 23-Apr-2017
https://dl.acm.org/doi/10.5555/3108096.3108112
Chang KYağlıkçı AGhose SAgrawal AChatterjee NKashyap ALee DO'Connor MHassan HMutlu O(2017)Understanding Reduced-Voltage Operation in Modern DRAM DevicesProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/30844471:1(1-42)Online publication date: 13-Jun-2017
https://dl.acm.org/doi/10.1145/3084447
Li BLeón ECameron KHuang HWeissman JIamnitchi AIosup A(2017)COSProceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing10.1145/3078597.3078601(155-166)Online publication date: 26-Jun-2017
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