A multi‐GPU shallow‐water simulation with transport of contaminants. (14th August 2012)

• Record Type: Journal Article
• Authors: Viñas, M.; Lobeiras, J.; Fraguela, B.B.; Arenaz, M.; Amor, M.; García, J.A.; Castro, M.J.; Doallo, R.; Hidalgo, Jose Ignacio; Fernández‐de‐Vega, Francisco; Amor, Margarita; Doallo, Ramón; Fraguela, Basilio B.; Herrero, José R.; Quintana‐Ortí, Enrique S.; Strzodka, Robert
• Is Part Of: Concurrency and computation. Volume 25:Number 8(2013:Jun.)
• Page Start: 1153
• Page End: 1169
• Publication Date: 2012-08-14
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.2917
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main" id="cpe2917-abs-0001"> <title>SUMMARY</title> <p>This work presents cost‐effective multi‐graphics processing unit (GPU) parallel implementations of a finite‐volume numerical scheme for solving pollutant transport problems in bidimensional domains. The fluid is modeled by 2D shallow‐water equations, whereas the transport of pollutant is modeled by a transport equation. The 2D domain is discretized using a first‐order Roe finite‐volume scheme. Specifically, this paper presents <italic>multi‐GPU</italic> implementations of both a solution that exploits recomputation on the GPU and an optimized solution that is based on a ghost cell decoupling approach. Our multi‐GPU implementations have been optimized using nonblocking communications, overlapping communications and computations and the application of ghost cell expansion to minimize communications. The fastest one reached a speedup of 78 × using four GPUs on an InfiniBand network with respect to a parallel execution on a multicore CPU with six cores and two‐way hyperthreading per core. Such performance, measured using a realistic problem, enabled the calculation of solutions not only in real time but also in orders of magnitude faster than the simulated time.Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract>