ACM Transactions on Mathematical Software (TOMS)
Combinatorial algorithms for integrated circuit layout
Combinatorial algorithms for integrated circuit layout
Sparse matrix computations on parallel processor arrays
SIAM Journal on Scientific Computing
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Distributed memory matrix-vector multiplication and conjugate gradient algorithms
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
Massively parallel methods for engineering and science problems
Communications of the ACM
Mapping molecular dynamics computations on to hypercubes
Parallel Computing
Parallel Incremental Graph Partitioning
IEEE Transactions on Parallel and Distributed Systems
T2: a customizable parallel database for multi-dimensional data
ACM SIGMOD Record
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Hypergraph-Partitioning-Based Decomposition for Parallel Sparse-Matrix Vector Multiplication
IEEE Transactions on Parallel and Distributed Systems
Querying very large multi-dimensional datasets in ADR
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Graph partitioning models for parallel computing
Parallel Computing - Special issue on graph partioning and parallel computing
Partitioning Unstructured Computational Graphs for Nonuniform and Adaptive Environments
IEEE Parallel & Distributed Technology: Systems & Technology
A Fine-Grain Hypergraph Model for 2D Decomposition of Sparse Matrices
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Decomposing Irregularly Sparse Matrices for Parallel Matrix-Vector Multiplication
IRREGULAR '96 Proceedings of the Third International Workshop on Parallel Algorithms for Irregularly Structured Problems
Graph Partitioning and Parallel Solvers: Has the Emperor No Clother? (Extended Abstract)
IRREGULAR '98 Proceedings of the 5th International Symposium on Solving Irregularly Structured Problems in Parallel
A Scalable Distributed Parallel Breadth-First Search Algorithm on BlueGene/L
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Parallel multilevel algorithms for hypergraph partitioning
Journal of Parallel and Distributed Computing
Multi-level direct K-way hypergraph partitioning with multiple constraints and fixed vertices
Journal of Parallel and Distributed Computing
A Matrix Partitioning Interface to PaToH in MATLAB
Parallel Computing
On Two-Dimensional Sparse Matrix Partitioning: Models, Methods, and a Recipe
SIAM Journal on Scientific Computing
Integrated data placement and task assignment for scientific workflows in clouds
Proceedings of the fourth international workshop on Data-intensive distributed computing
Hypergraph partitioning for the parallel computation of continuous Petri nets
PaCT'11 Proceedings of the 11th international conference on Parallel computing technologies
A scalable eigensolver for large scale-free graphs using 2D graph partitioning
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Highly scalable graph search for the Graph500 benchmark
Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing
Partitioning Hypergraphs in Scientific Computing Applications through Vertex Separators on Graphs
SIAM Journal on Scientific Computing
Parallel computation of continuous Petri nets based on hypergraph partitioning
The Journal of Supercomputing
Using LAMA for efficient AMG on hybrid clusters
Computer Science - Research and Development
Scalable matrix computations on large scale-free graphs using 2D graph partitioning
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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We propose a new two-phase method for the coarse-grain decomposition of irregular computational domains. This work focuses on the 2D partitioning of sparse matrices for parallel matrix-vector multiplication. However, the proposed model can also be used to decompose computational domains of other parallel reduction problems. This work also introduces the use of multi-constraint hypergraph partitioning, for solving the decomposition problem. The proposed method explicitly models the minimization of communication volume while enforcing the upper bound of p + q --- 2 on the maximum number of messages handled by a single processor, for a parallel system with P = p × q processors. Experimental results on a wide range of realistic sparse matrices confirm the validity of the proposed methods, by achieving up to 25 percent better partitions than the standard graph model, in terms of total communication volume, and 59 percent better partitions in terms of number of messages, on the overall average.