A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures
HARP: a fast spectral partitioner
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
Load balanced parallel radix sort
ICS '98 Proceedings of the 12th international conference on Supercomputing
Special issue on dynamic load balancing: guest editor's introduction
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
On the performance of spectral graph partitioning methods
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Load Balancing Highly Irregular Computations with the Adaptive Factoring
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Performance of Scheduling Scientific Applications with Adaptive Weighted Factoring
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Overhead Analysis of a Dynamic Load Balancing Library for Cluster Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 1 - Volume 02
Design and implementation of a novel dynamic load balancing library for cluster computing
Parallel Computing - Heterogeneous computing
A Load Balancing Tool for Distributed Parallel Loops
Cluster Computing
Performance evaluation of a dynamic load-balancing library for cluster computing
International Journal of Computational Science and Engineering
Library support for parallel sorting in scientific computations
Euro-Par'07 Proceedings of the 13th international Euro-Par conference on Parallel Processing
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Computational science problems with adaptive meshes involve dynamic load balancing when implemented on parallel machines. This dynamic load balancing requires fast partitioning of computational meshes at run time. We present in this report a scalable parallel dynamic partitioner, called S-HARP. The underlying principles of S-HARP are the fast feature of inertial partitioning and the quality feature of spectral partitioning. S-HARP is a universal dynamic partitioner with three distinctive features: (a) fast partitioning from scratch with a global view, requiring no information from the previous iterations, (b) no restriction on the issue of one partition per processor, (c) no imbalance factor issue because of precise bisection using sorting. Two types of parallelism have been exploited in S-HARP, fine-grain loop-level parallelism and coarse-grain recursive parallelism. The parallel partitioner has been implemented in Message Passing Interface on Cray T3E and IBM SP2 for portability. Experimental results indicate that S-HARP can partition a mesh of over 100,000 vertices into 256 partitions in 0.18 seconds on a 64-processor Cray T3E. S-HARP is much more scalable than other dynamic partitioners, giving over 17-fold speedup on 64 processors while ParaMeTiS1.0 gives a few-fold speedup. Experimental results demonstrate that S-HARP is three to 15 times faster than the other dynamic partitioners on computational meshes of size over 100,000 vertices while giving comparable edge cuts.