AuthorsJ. Langguth, N. Wu, J. Chai and X. Cai
TitleParallel performance modeling of irregular applications in cell-centered finite volume methods over unstructured tetrahedral meshes
AfilliationHigh Performance Computing, , Scientific Computing
Project(s)Center for Biomedical Computing (SFF)
StatusPublished
Publication TypeJournal Article
Year of Publication2015
JournalJournal of Parallel and Distributed Computing
Volume76
Pagination120-131
Date Published02/2015
PublisherElsevier
Abstract

Finite volume methods are widely used numerical strategies for solving partial differential equations. This paper aims at obtaining a quantitative understanding of the achievable performance of the cell-centered finite volume method on 3D unstructured tetrahedral meshes, using traditional multicore CPUs as well as modern GPUs. By using an optimized implementation and a synthetic connectivity matrix that exhibits a perfect structure of equal-sized blocks lying on the main diagonal, we can closely relate the achievable computing performance to the size of these diagonal blocks. Moreover, we have derived a theoretical model for identifying characteristic levels of the attainable performance as a function of hardware parameters, based on which a realistic upper limit of the performance can be predicted accurately. For real-world tetrahedral meshes, the key to high performance lies in a reordering of the tetrahedra, such that the resulting connectivity matrix resembles a block diagonal form where the optimal size of the blocks depends on the hardware. Numerical experiments confirm that the achieved performance is close to the practically attainable maximum and it reaches 75% of the theoretical upper limit, independent of the actual tetrahedral mesh considered. From this, we develop a general model capable of identifying bottleneck performance of a system’s memory hierarchy in irregular applications.

DOI10.1016/j.jpdc.2014.10.005
Citation Key19103