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2019 | OriginalPaper | Chapter

Multi-GPU Acceleration of the iPIC3D Implicit Particle-in-Cell Code

Authors : Chaitanya Prasad Sishtla, Steven W. D. Chien, Vyacheslav Olshevsky, Erwin Laure, Stefano Markidis

Published in: Computational Science – ICCS 2019

Publisher: Springer International Publishing

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Abstract

iPIC3D is a widely used massively parallel Particle-in-Cell code for the simulation of space plasmas. However, its current implementation does not support execution on multiple GPUs. In this paper, we describe the porting of iPIC3D particle mover to GPUs and the optimization steps to increase the performance and parallel scaling on multiple GPUs. We analyze the strong scaling of the mover on two GPU clusters and evaluate its performance and acceleration. The optimized GPU version which uses pinned memory and asynchronous data prefetching outperform their corresponding CPU versions by \(5-10\times \) on two different systems equipped with NVIDIA K80 and V100 GPUs.

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Metadata
Title
Multi-GPU Acceleration of the iPIC3D Implicit Particle-in-Cell Code
Authors
Chaitanya Prasad Sishtla
Steven W. D. Chien
Vyacheslav Olshevsky
Erwin Laure
Stefano Markidis
Copyright Year
2019
Book
Computational Science – ICCS 2019

Print ISBN: 978-3-030-22749-4

Electronic ISBN: 978-3-030-22750-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-22750-0_58

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