Finite element numerical integration for first order approximations on multi- and many-core architectures

被引:25
作者
Banas, Krzysztof [1 ]
Kruzel, Filip [2 ]
Bielanski, Jan [1 ]
机构
[1] AGH Univ Sci & Technol, Dept Appl Comp Sci & Modelling, Mickiewicza 30, PL-30059 Krakow, Poland
[2] Cracow Univ Technol, Inst Comp Sci, Warszawska 24, PL-31155 Krakow, Poland
关键词
Finite element method; First order approximation; Numerical integration; Multi-threaded programming; Multi-core processors; Graphics processors; PERFORMANCE ANALYSIS; GPU ACCELERATION; LINEAR-EQUATIONS; SOLVERS; IMPLEMENTATION; GENERATION; MODEL;
D O I
10.1016/j.cma.2016.03.038
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The paper presents investigations on the performance of the finite element numerical integration algorithm for first order approximations and three processor architectures, popular in scientific computing, classical x86_64 CPU, Intel Xeon Phi and NVIDIA Kepler GPU. We base the discussion on theoretical performance models and our own implementations for which we perform a range of computational experiments. For the latter, we consider a unifying programming model and portable OpenCL implementation for all architectures. Variations of the algorithm due to different problems solved and different element types are investigated and several optimizations aimed at proper optimization and mapping of the algorithm to computer architectures are demonstrated. The experimental results show the varying levels of performance for different architectures, but indicate that the algorithm can be effectively ported to all of them. The conclusions indicate the factors that limit the performance for different problems and types of approximation and the performance ranges that can be expected for FEM numerical integration on different processor architectures. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:827 / 848
页数:22
相关论文
共 47 条
[1]   A scalable multi-level preconditioner for matrix-free μ-finite element analysis of human bone structures [J].
Arbenz, Peter ;
van Lenthe, G. Harry ;
Mennel, Uche ;
Mueller, Ralph ;
Sala, Marzio .
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2008, 73 (07) :927-947
[2]  
Banas K, 2004, LECT NOTES COMPUT SC, V3037, P155
[3]   Adaptive finite element modelling of welding processes [J].
Banaś, Krzysztof ;
Chloń, Kazimierz ;
Cybulka, Pawel ;
Michalik, Kazimierz ;
Plaszewski, Przemyslaw ;
Siwek, Aleksander .
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8500 :391-406
[4]  
Banas K, 2008, LECT NOTES COMPUT SC, V4967, P1265
[5]   Numerical integration on GPUs for higher order finite elements [J].
Banas, Krzysztof ;
Plaszewski, Przemyskaw ;
Maciol, Pawel .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2014, 67 (06) :1319-1344
[6]  
Becker E., 1981, Finite Elements, An Introduction
[7]   Sparse matrix solvers on the GPU:: Conjugate gradients and multigrid [J].
Bolz, J ;
Farmer, I ;
Grinspun, E ;
Schröder, P .
ACM TRANSACTIONS ON GRAPHICS, 2003, 22 (03) :917-924
[8]   STREAMLINE UPWIND PETROV-GALERKIN FORMULATIONS FOR CONVECTION DOMINATED FLOWS WITH PARTICULAR EMPHASIS ON THE INCOMPRESSIBLE NAVIER-STOKES EQUATIONS [J].
BROOKS, AN ;
HUGHES, TJR .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 1982, 32 (1-3) :199-259
[9]  
Cai Y., 2013, PROCEDIA ENG, V61, P318, DOI [10.1016/j.proeng.2013.08.022, DOI 10.1016/J.PROENG.2013.08.022, DOI 10.1016/j.proeng.2013.08.022]
[10]  
Cecka C., 2011, GPU COMPUTING GEMS, P187