HARP: a fast spectral partitioner

Partitioningunstructuredgraphsis central to the parallel solution of computational science and engineering problems, Spectral partitioners, such recursive spectral bisection (RSB), have proven effective in generating high-quality partitions of realistically-sized meshes. The major problem which hindered their widespread use was their long execution times. This paper presents a new inertial spectral partitioned, called HARP. The main objective of the proposed approach is to quickly partition the meshes at runtime in a manner that works efficiently for real applications in the context of distributed-memory machines. The underlying principle of HARP is to find the eigenvectors of the unpartitioned vertices and then project them onto the eigenvectors of the originaJ mesh. Results for various meshes ranging in size from 1000 to 100,000 vertices indicate that HARP can indeed partition meshes rapidly at runtime, Experimental results show that our largest mesh can be partitioned sequentially in only a few seconds on an SP2 which is several times faster than other spectral partitioners while maintaining the solution quality of the proven RSB method. A parallel MPI version of HARP has also been implemented on IBM SP2 and Cray T3E. PrrralIel HARP, running on 64 processors SP2 and T3E, can partition a mesh containing more than 100,000 vertices into 64 subgrids in about half a second. These results indicate that graph partitioning can now be truly embedded in dynamically-changing real-world applications,

[1]  J. G. Lewis,et al.  A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems , 1994, SIAM J. Matrix Anal. Appl..

[2]  Charbel Farhat,et al.  A simple and efficient automatic fem domain decomposer , 1988 .

[3]  Brian W. Kernighan,et al.  An efficient heuristic procedure for partitioning graphs , 1970, Bell Syst. Tech. J..

[4]  Rupak Biswas,et al.  Impact of load balancing on unstructured adaptive grid computations for distributed-memory multiprocessors , 1996, Proceedings of SPDP '96: 8th IEEE Symposium on Parallel and Distributed Processing.

[5]  Horst D. Simon,et al.  Partitioning of unstructured problems for parallel processing , 1991 .

[6]  PothenAlex,et al.  Partitioning sparse matrices with eigenvectors of graphs , 1990 .

[7]  Steven J. Plimpton,et al.  Parallel Algorithms for Dynamically Partitioning Unstructured Grids , 1995, PPSC.

[8]  M. Fiedler A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory , 1975 .

[9]  Stéphane Lanteri,et al.  TOP/DOMDEC : a software tool for mesh partitioning and parallel processing and applications to CSM a , 1995 .

[10]  Alex Pothen,et al.  PARTITIONING SPARSE MATRICES WITH EIGENVECTORS OF GRAPHS* , 1990 .

[11]  T. Chan,et al.  Geometric Spectral Partitioning , 1994 .

[12]  Vipin Kumar,et al.  A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs , 1998, SIAM J. Sci. Comput..

[13]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[14]  Bruce Hendrickson,et al.  A Multi-Level Algorithm For Partitioning Graphs , 1995, Proceedings of the IEEE/ACM SC95 Conference.

[15]  Alan George,et al.  A linear time implementation of the reverse Cuthill-McKee algorithm , 1980, BIT.

[16]  R. Biswas,et al.  A new procedure for dynamic adaption of three-dimensional unstructured grids , 1994 .

[17]  P. Sadayappan,et al.  Nearest-Neighbor Mapping of Finite Element Graphs onto Processor Meshes , 1987, IEEE Transactions on Computers.

[18]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[19]  Steve Furber,et al.  ARM System Architecture , 1996 .

[20]  Steven L. Scott,et al.  Synchronization and communication in the T3E multiprocessor , 1996, ASPLOS VII.

[21]  Tilak Agerwala,et al.  SP2 System Architecture , 1999, IBM Syst. J..

[22]  Johan De Keyser,et al.  Grid partitioning by inertial recursive bisection , 1992 .

[23]  Rupak Biswas,et al.  A new procedure for dynamic adaption of three-dimensional unstructured grids , 1993 .

[24]  Dirk Roose,et al.  A Grapg Contraction Algorithm for the Fast Calculation of the Fiedler Vector of a Graph , 1995, PPSC.

[25]  Horst D. Simon,et al.  Fast multilevel implementation of recursive spectral bisection for partitioning unstructured problems , 1994, Concurr. Pract. Exp..

[26]  Rupak Biswas,et al.  A dynamic load balancing framework for unstructured adaptive computations on distributed-memory multiprocessors , 1996, SPAA '96.