nach oben

The Journal of Supercomputing

Erschienen in:

01.09.2013

Modeling energy consumption for master–slave applications

verfasst von: F. Almeida, V. Blanco, A. Cabrera, J. Ruiz

Erschienen in: The Journal of Supercomputing | Ausgabe 3/2013

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

With energy costs now accounting for nearly 30 % of a datacenter’s operating expenses, energy consumption has become an important issue when designing and executing a parallel algorithm. This paper analyzes the energy consumption of MPI applications following the master–slave paradigm. The analytical model is derived for this paradigm and is validated over a master–slave matrix-multiplication. This analytical model is parameterized through architectural and algorithmic parameters, and it is capable of predicting the energy consumption for a given instance of the problem over a given architecture. We use an external, metered, power distribution unit that allows to easily measure the power consumption of computing nodes without the needing of dedicated hardware.

Vorheriger Artikel Skeletal based programming for dynamic programming on MultiGPU systems

Nächster Artikel uBench: exposing the impact of CUDA block geometry in terms of performance

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Alonso P, Dolz MF, Igual FD, Mayo R, Quintana-Ortí ES Saving energy in the lu factorization with partial pivoting on multi-core processors. In: Stotzka et al [20], pp 353–358

Bedard D, Lim MY, Fowler RJ, Porterfield A (2010) Powermon: fine-grained and integrated power monitoring for commodity computer systems. In: Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon), March 2010, pp 479–484 CrossRef

Castillo M, Fernández JC, Mayo R, Quintana-Ortí ES, Roca V Analysis of strategies to save energy for message-passing dense linear algebra kernels. In: Stotzka et al [20], pp 346–352

Chou C-Y, Chang H-Y, Wang S-T, Tcheng S-C (2006) Modeling message-passing overhead on nchc formosa pc cluster. In: Chung YC, Moreira JE (eds) GPC. Lecture notes in computer science, vol 3947. Springer, Berlin, pp 299–307

Davis J, Rivoire S, Goldszmidt M, Ardestani E (2011) Accounting for variability in large-scale cluster power models. In: The second exascale evaluation and research techniques workshop, Held in conjunction with ASPLOS 2011

Enos J, Steffen CP, Fullop J, Showerman MT, Shi G, Esler K, Kindratenko VV, Stone JE, Phillips JC (2010) Quantifying the impact of gpus on performance and energy efficiency in hpc clusters. In: Green computing conference. IEEE Press, New York, pp 317–324 CrossRef

Freeh VW, Lowenthal DK, Pan F, Kappiah N, Springer R, Rountree B, Femal ME (2007) Analyzing the energy-time trade-off in high-performance computing applications. IEEE Trans Parallel Distrib Syst 18(6):835–848 CrossRef

Hähnel M, Döbel B, Völp M, Härtig H (2012) Measuring energy consumption for short code paths using rapl. In: GreenMetrics 2012 workshop, in conjunction with ACM sigmetrics/performance 2012, ACM sigmetrics, London, UK, 11 June 2012. ACM, New York

Hockney RW (1994) The communication challenge for mpp: intel paragon and meiko cs-2. Parallel Comput 20(3):389–398

10.

Keys L, Rivoire S, Davis JD (2010) The search for energy-efficient building blocks for the data center. In: Varbanescu AL, Molnos AM, van Nieuwpoort R (eds) ISCA workshops. Lecture notes in computer science, vol 6161. Springer, Berlin, pp 172–182

11.

Lim MY, Porterfield A, Fowler RJ (2010) Softpower: fine-grain power estimations using performance counters. In: Hariri S, Keahey K (eds) HPDC. ACM, New York, pp 308–311

12.

Lim MY, Freeh VW, Lowenthal DK (2011) Adaptive, transparent cpu scaling algorithms leveraging inter-node mpi communication regions. Parallel Comput 37(10–11):667–683 CrossRef

13.

Martinez DR, Cabaleiro JC, Pena TF, Rivera FF, Blanco V (2010) Performance modeling of mpi applications using model selection techniques. In: Danelutto M, Bourgeais J, Gross T (eds) 18th euromicro conference on parallel, distributed and network–based processing, PDP2010, Pisa, Italy, February 2010. IEEE Computer Society, Los Alamitos, pp 95–102

14.

Martínez DR, Albín JL, Pena TF, Cabaleiro JC, Rivera FF, Blanco V (2011) Using accurate AIC-based performance models to improve the scheduling of parallel applications. J Supercomput 58(3):332–340. doi:10.1007/s11227-011-0589-1 CrossRef

15.

MPICH-a portable implementation of MPI, November 2005

16.

Mullen KM, van Stokkum IHM (2010) nnls: the Lawson–Hanson algorithm for non-negative least squares (nnls), April 2010

17.

Nurmi D, Mandal A, Brevik J, Koelbel C, Wolski R, Kennedy K (2006) Evaluation of a workflow scheduler using integrated performance modelling and batch queue wait time prediction. In: Proceedings of the ACM/IEEE SC2006 conference on high performance networking and computing, Tampa, FL, USA, 11–17 November 2006. ACM, New York, p 119

18.

Rivoire S, Shah MA, Ranganathan P, Kozyrakis C, Meza J (2007) Models and metrics to enable energy-efficiency optimizations. IEEE Comput 40(12):39–48 CrossRef

19.

Schuermans A (2012) Schleifenbauer products bv, March 2012

20.

Stotzka R, Schiffers M, Cotronis Y (eds) (2012) Proceedings of the 20th euromicro international conference on parallel, distributed and network-based processing, PDP 2012, Munich, Germany, 15–17 February 2012. IEEE Press, New York, pp 15–17

21.

Various (2012) R, language and environment for statistical computing and graphics, March 2012

22.

Xu Z, Hwang K (1996) Modeling communication overhead: mpi and mpl performance on the ibm sp2. IEEE Parallel Distrib Technol, Syst Appl 4(1):9–24 CrossRef

Titel: Modeling energy consumption for master–slave applications
verfasst von: F. Almeida
V. Blanco
A. Cabrera
J. Ruiz
Publikationsdatum: 01.09.2013
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 3/2013
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-013-0914-y

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 3/2013

uBench: exposing the impact of CUDA block geometry in terms of performance

Fully distributed authentication with locality exploitation for the CoDiP2P peer-to-peer computing platform

Multicore implementation of a fixed-complexity tree-search detector for MIMO communications

Accelerating the Lyapack library using GPUs

Parallel construction of independent spanning trees and an application in diagnosis on Möbius cubes

A survey of fault tolerance mechanisms and checkpoint/restart implementations for high performance computing systems

Premium Partner