Toward a modular precision ecosystem for high-performance computing
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Altres documents de l'autoria: Anzt, Hartwig; Flegar, Goran; Grützmacher, Thomas; Quintana-Orti, Enrique S.
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Toward a modular precision ecosystem for high-performance computingData de publicació
2019-05Editor
SageCita bibliogràfica
ANZT, Hartwig, et al. Toward a modular precision ecosystem for high-performance computing. The International Journal of High Performance Computing Applications, 2019, 33(6): 1069–1078Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://journals.sagepub.com/doi/full/10.1177/1094342019846547Versió
info:eu-repo/semantics/acceptedVersionParaules clau / Matèries
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With the memory bandwidth of current computer architectures being significantly slower than the (floating point) arithmetic performance, many scientific computations only leverage a fraction of the computational power ... [+]
With the memory bandwidth of current computer architectures being significantly slower than the (floating point) arithmetic performance, many scientific computations only leverage a fraction of the computational power in today’s high-performance architectures. At the same time, memory operations are the primary energy consumer of modern architectures, heavily impacting the resource cost of large-scale applications and the battery life of mobile devices. This article tackles this mismatch between floating point arithmetic throughput and memory bandwidth by advocating a disruptive paradigm change with respect to how data are stored and processed in scientific applications. Concretely, the goal is to radically decouple the data storage format from the processing format and, ultimately, design a “modular precision ecosystem” that allows for more flexibility in terms of customized data access. For memory-bounded scientific applications, dynamically adapting the memory precision to the numerical requirements allows for attractive resource savings. In this article, we demonstrate the potential of employing a modular precision ecosystem for the block-Jacobi preconditioner and the PageRank algorithm—two applications that are popular in the communities and at the same characteristic representatives for the field of numerical linear algebra and data analytics, respectively. [-]
Proyecto de investigación
Helmholtz Association, “Impuls undVernetzungsfond” (grant VH-NG-1241) ; MINECOand FEDER (project TIN2017-82972-R) ; H2020 EU FETHPC (Project 732631“OPRECOMP”)Drets d'accés
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