Abstract
This paper introduces an infrastructure for parallel mesh computations running on distributed-memory computers. The infrastructure consists of the mesh partitioning algorithm GARP and the domain-specific communication library GRAPHlib. Unlike existing algorithms, GARP exploits geometrical properties of the mesh shape in order to produce shape-adequate rectilinear partitions. The structure of such partitions is exploited by GRAPHlib using an optimized message ordering strategy. We describe the concepts behind GARP and GRAPHlib and show that for meshes with particular shapes our infrastructure provides better utilization of the parallel computer than solutions using existing partitioning algorithms and communication libraries.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berger, M., Bokhari, S.: A partitioning strategy for non-uniform problems on multiprocessors. IEEE Transactions on Computers 36 (1987) 570–580
Chrisochoides, N.: On the mapping of PDE computations to distributed memory machines. Ph.D. thesis, Purdue University (1992)
Farhat, C.: A simple and efficient automatic FEM domain decomposer. Computers and Structures 28 (1988) 579–602
Farhat, C., Lesoinne, M.: Automatic Partititioning of Unstructured Meshes for the Parallel Solution of Problems in Computational Mechanics. International Journal for Numerical Methods in Engineering 36 (1993) 745–764
Hammond, S.: Mapping Unstructured Grid Computations to Massively Parallel Computers. Ph.D. thesis, Renesselaer Polytechnic Institute (1992)
Hinz, D.: A run-time load balancing strategy for highly parallel systems. Acta Informatica 29 (1992) 63–94
Kernighan, B., Lin, S.: An efficient heuristic procedure for partitioning graphs. Bell System Technical Journal 49 (1970) 291–307
Mavriplis, D.J.: Three-Dimensional Multigrid for the Euler Equations. AIAA Paper 91-1549CP, American Institute of Aeronautics and Astronautics (1991) 824–831
Nicol, D.: Rectilinear Partitioning of Irregular Data Parallel Computations. Journal of Parallel and Distributed Computing 23 (1994) 119–134
Nour-Omid, B., Raefsky, A., Lyzenga, G.: Solving finite element equations on concurrent computers. In Noor, A.K. (ed.): Parallel computations and their impact on mechanics. American Society on Mechanical Engineering (1986) 209–227
Pothen, A., Simon, H., Liou, K.-P.: Partitioning sparse matrices with eigenvectors of graphs. SIAM Journal of Matrix Analysis and Applications 11 (1990) 430–452
Sadayappan, P., Ercal, F.: Nearest Neighbor Mapping of Finite Element Graphs onto Processor Meshes. IEEE Transactions on Computers 36 (1987) 1408–1424
Simon, H.: Partitioning of unstructured problems for parallel processing. Computing Systems in Engineering 2 (1991) 135–148
Wang, J.-C.: Load Balancing and Communication Support for Irregular Problems. Ph. D. thesis, Syracuse University (1993)
Walshaw, C., Cross, M., Everett, M., Johnson, S., McManus, K.: Partitioning and Mapping of Unstructured Meshes to Parallel Machine Topologies. In Ferreira, A., Rolim, J. (eds.): Parallel Algorithms for Irregular Structures Problems. Springer LNCS 980 (1995) 121–126
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Koppler, R. (1999). Geometry-Aided Rectilinear Partitioning of Unstructured Meshes. In: Zinterhof, P., Vajteršic, M., Uhl, A. (eds) Parallel Computation. ACPC 1999. Lecture Notes in Computer Science, vol 1557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49164-3_43
Download citation
DOI: https://doi.org/10.1007/3-540-49164-3_43
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65641-8
Online ISBN: 978-3-540-49164-4
eBook Packages: Springer Book Archive