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Rozdział

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Tytuł

Energy efficiency and performance modeling of stencil applications on manycore and GPU computing resources

Autorzy

[ 1 ] Poznańskie Centrum Superkomputerowo-Sieciowe, Polska Akademia Nauk | [ P ] pracownik

Dyscyplina naukowa (Ustawa 2.0)

[2.3] Informatyka techniczna i telekomunikacja

Rok publikacji

2020

Typ rozdziału

rozdział w monografii naukowej / referat

Język publikacji

angielski

Słowa kluczowe
EN
Streszczenie

EN One of the most critical application areas for many operational High-Performance Computing systems worldwide is a numerical weather prediction. Such complex predictions and corresponding computing models have to solve a large number of Partial Differential Equations using stencil computations on structured grids within tight production schedules. A stencil kernel within simulations is often the most demanding computing part and naturally may impact the energy consumption of the whole HPC system. In this paper, we introduce new functional extensions developed for DCworms and GSSIM simulators to predict the energy efficiency of extreme-scale stencil applications on heterogeneous computing resources, in particular consisting of a large number of many-core and GPUs. New energy-efficiency metrics for modeling of heterogeneous computing resources have been successfully added to the simulators thanks to their pluggable and extensible architectures. Our recent improvements related to application-specific performance models in simulators help users to take into account many relevant application parameters, in particular, those related to detailed energy consumption on heterogeneous HPC resources. We show in this paper how to extract stencil application-specific parameters based on real experiments. Moreover, we demonstrate how those parameters can be applied for modeling and simulation experiments to evaluate the overall performance and energy consumption of stencil computations on manycore CPUs and GPUs. Finally, we discuss new DCworms simulator capabilities and demonstrate added-values of performance analysis tools.

Strony (od-do)

232 - 241

DOI

10.1109/CCGrid49817.2020.00-70

URL

http://xplorestaging.ieee.org/ielx7/9136834/9139601/09139731.pdf?arnumber=9139731

Książka

2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)

Zaprezentowany na

20th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 11-14.05.2020, Melbourne, Australia

Punktacja Ministerstwa / konferencja (CORE)

140