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dc.contributor.authorGöddeke, Dominik
dc.contributor.authorKomatitsch, D.
dc.contributor.authorGeveler, Markus
dc.contributor.authorRibbrock, D.
dc.contributor.authorRajovic, Nikola
dc.contributor.authorPuzovic, Nikola
dc.contributor.authorRamírez Bellido, Alejandro
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.identifier.citationGöddeke, D. [et al.]. Energy efficiency vs. performance of the numerical solution of PDEs: an application study on a low-power ARM-based cluster. "Journal of computational physics", 05 Març 2013, vol. 237, p. 132-150.
dc.description.abstractPower consumption and energy efficiency are becoming critical aspects in the design and operation of large scale HPC facilities, and it is unanimously recognised that future exascale supercomputers will be strongly constrained by their power requirements. At current electricity costs, operating an HPC system over its lifetime can already be on par with the initial deployment cost. These power consumption constraints, and the benefits a more energy-efficient HPC platform may have on other societal areas, have motivated the HPC research community to investigate the use of energy-efficient technologies originally developed for the embedded and especially mobile markets. However, lower power does not always mean lower energy consumption, since execution time often also increases. In order to achieve competitive performance, applications then need to efficiently exploit a larger number of processors. In this article, we discuss how applications can efficiently exploit this new class of low-power architectures to achieve competitive performance. We evaluate if they can benefit from the increased energy efficiency that the architecture is supposed to achieve. The applications that we consider cover three different classes of numerical solution methods for partial differential equations, namely a low-order finite element multigrid solver for huge sparse linear systems of equations, a Lattice-Boltzmann code for fluid simulation, and a high-order spectral element method for acoustic or seismic wave propagation modelling. We evaluate weak and strong scalability on a cluster of 96 ARM Cortex-A9 dual-core processors and demonstrate that the ARM-based cluster can be more efficient in terms of energy to solution when executing the three applications compared to an x86-based reference machine.
dc.format.extent19 p.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.subjectÀrees temàtiques de la UPC::Energies::Eficiència energètica
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshEnergy conservation
dc.subject.lcshPhysics -- Data processing
dc.subject.otherARM processors
dc.subject.otherEnergy efficiency
dc.subject.otherFinite elements
dc.subject.otherHigh performance computing
dc.subject.otherLow-power processors
dc.subject.otherParallel scalability
dc.subject.otherWave propagation
dc.titleEnergy efficiency vs. performance of the numerical solution of PDEs: an application study on a low-power ARM-based cluster
dc.subject.lemacEnergia -- Estalvi
dc.subject.lemacFísica -- Informàtica
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/283493/EU/PRACE - Second Implementation Phase Project/PRACE-2IP
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/261557/EU/PRACE - First Implementation Phase Project/PRACE-1IP
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/287759/EU/High Performance and Embedded Architecture and Compilation/HIPEAC
local.citation.authorGöddeke, D.; Komatitsch, D.; Geveler, M.; Ribbrock, D.; Rajovic, N.; Puzovic, N.; Alex Ramirez
local.citation.publicationNameJournal of computational physics

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