PARALLELIZATION OF A CLASS OF IMPLICIT FINITE DIFFERENCE SCHEMES IN COMPUTATIONAL FLUID DYNAMICS

作     者：NAOMI H. NAIK VIJAY K. NAIK MICHEL NICOULES 

作者机构：Lamont-Doherty Earth Observatory Columbia University Palisades NY 10964 USA Research supported by the National Aeronautics and Space Administration under NASA Contract No. NAS1-18605 while in residence at the Institute for Computer Applications in Science and Engineering (ICASE) NASA Langley Research Center Hampton VA 23665– 5225. IBM T.J. Watson Research Center P.O. Box 218 Yorktown Heights NY 10598 USA Current address: Institut National Des Telecommunications 91011 Evry France. 

出 版 物：《International Journal of High Speed Computing》 

年 卷 期：1993年第5卷第1期

页      面：1-50页

主　　题：Parallel CFD implicit finite difference schemes partitioning methods for block tri-diagonal and scalar penta-diagonal solvers ARC-3D message passing systems 

摘      要：Implicit finite difference schemes are often the preferred numerical methods in computational fluid dynamics, requiring less stringent stability bounds than the explicit schemes. Each iteration in an implicit scheme, however, involves global data dependencies in the form of second and higher order recurrences. Efficient parallel implementations of such methods, therefore, are more difficult and can be non-intuitive. Moreover, in practical applications, some sections of the computations are explicit while other sections are implicit in nature. Developing techniques that extract maximum parallelism simultaneously from all sections of an application is considerably harder than extracting parallelism from just an implicit section or an explicit section of the computations. In this paper, we consider issues in the parallelization of techniques that are used for solving Euler and thin-layer Navier-Stokes equations and that require, as a part of the computation, solving large linear systems in the form of block tri-diagonal and/or scalar penta-diagonal matrices. We focus our attention on three-dimensional cases and present schemes that minimize the total execution time when implemented on a message passing system. We describe various partitioning and scheduling strategies for alleviating the effects of the global data dependencies. Analyses of the computation, the communication, and the memory requirements of these methods are presented. The ARC-3D code, developed at NASA Ames, is used as an example application. Performance of the proposed methods is verified on the Victor multiprocessor system, a message passing architecture developed at the IBM T.J. Watson Research Center.