Load Balancing for CPU-GPU Coupling in Computational Fluid Dynamics

被引：2

作者：

Huismann, Immo ^{[1
,3
]}

Lieber, Matthias ^{[2
,3
]}

Stiller, Joerg ^{[1
,3
]}

Froehlich, Jochen ^{[1
,3
]}

机构：

[1] Tech Univ Dresden, Inst Fluid Mech, Dresden, Germany

[2] Tech Univ Dresden, Ctr Informat Serv & High Performance Comp, Dresden, Germany

[3] Ctr Adv Elect Dresden Cfaed, Dresden, Germany

来源：

PARALLEL PROCESSING AND APPLIED MATHEMATICS (PPAM 2017), PT I | 2018年 / 10777卷

关键词：

Parallelization; Heterogeneous computing; GPGPU; Load balancing; CFD; MULTI-GPU; PARALLELIZATION;

D O I：

10.1007/978-3-319-78024-5_30

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper investigates static load balancing models for CPU-GPU coupling from a computational fluid dynamics perspective. While able to generate a benefit, traditional load balancing models are found to be too inaccurate to predict the runtime of a preconditioned conjugate gradient solver. Hence, an expanded model is derived that accounts for the multi-step nature of the solver, i.e. several communication barriers per iteration. It is able to predict the runtime to a margin of 5%, rendering CPU-GPU coupling better predictable so that load balancing can be improved substantially.

引用

页码：337 / 347

页数：11

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