GPU Acceleration of Particle Advection Workloads in a Parallel, Distributed Memory Setting

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dc.contributor.authorCamp, Daviden_US
dc.contributor.authorKrishnan, Harien_US
dc.contributor.authorPugmire, Daviden_US
dc.contributor.authorGarth, Christophen_US
dc.contributor.authorJohnson, Ianen_US
dc.contributor.authorBethel, E. Wesen_US
dc.contributor.authorJoy, Kenneth I.en_US
dc.contributor.authorChilds, Hanken_US
dc.contributor.editorFabio Marton and Kenneth Morelanden_US
dc.date.accessioned2014-01-26T17:10:26Z
dc.date.available2014-01-26T17:10:26Z
dc.date.issued2013en_US
dc.description.abstractAlthough there has been significant research in GPU acceleration, both of parallel simulation codes (i.e., GPGPU) and of single GPU visualization and analysis algorithms, there has been relatively little research devoted to visualization and analysis algorithms on GPU clusters. This oversight is significant: parallel visualization and analysis algorithms have markedly different characteristics - computational load, memory access pattern, communication, idle time, etc. - than the other two categories. In this paper, we explore the benefits of GPU acceleration for particle advection in a parallel, distributed-memory setting. As performance properties can differ dramatically between particle advection use cases, our study operates over a variety of workloads, designed to reveal insights about underlying trends. This work has a three-fold aim: (1) to map a challenging visualization and analysis algorithm - particle advection - to a complex system (a cluster of GPUs), (2) to inform its performance characteristics, and (3) to evaluate the advantages and disadvantages of using the GPU. In our performance study, we identify which factors are and are not relevant for obtaining a speedup when using GPUs. In short, this study informs the following question: if faced with a parallel particle advection problem, should you implement the solution with CPUs, with GPUs, or does it not matter?en_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US
dc.identifier.isbn978-3-905674-45-3en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttps://doi.org/10.2312/EGPGV/EGPGV13/001-008en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectD.1.3 [Computer Graphics]en_US
dc.subjectConcurrent Programmingen_US
dc.subjectParallel programmingen_US
dc.titleGPU Acceleration of Particle Advection Workloads in a Parallel, Distributed Memory Settingen_US
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EGPGV13: Eurographics Symposium on Parallel Graphics and Visualization