Parallel dynamic graph partitioning for adaptive unstructured meshes
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
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
Partitioning Rectangular and Structurally Unsymmetric Sparse Matrices for Parallel Processing
SIAM Journal on Scientific Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Fine-Grain Hypergraph Model for 2D Decomposition of Sparse Matrices
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
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 linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
SIAM Journal on Scientific Computing
A Parallel Algorithm for Multilevel k-Way Hypergraph Partitioning
ISPDC '04 Proceedings of the Third International Symposium on Parallel and Distributed Computing/Third International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Networks
New challenges in dynamic load balancing
Applied Numerical Mathematics - Adaptive methods for partial differential equations and large-scale computation
Parallel hypergraph partitioning for scientific computing
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Partitioning Hypergraphs in Scientific Computing Applications through Vertex Separators on Graphs
SIAM Journal on Scientific Computing
Model-based cache-aware dispatching of object-oriented software for multicore systems
Journal of Systems and Software
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In this paper, we present a new graph model of sparse matrix decomposition for parallel sparse matrix–vector multiplication. Our model differs from previous graph-based approaches in two main respects. Firstly, our model is based on edge colouring rather than vertex partitioning. Secondly, our model is able to correctly quantify and minimise the total communication volume of the parallel sparse matrix–vector multiplication while maintaining the computational load balance across the processors. We show that our graph edge colouring model is equivalent to the fine-grained hypergraph partitioning-based sparse matrix decomposition model. We conjecture that the existence of such a graph model should lead to faster serial and parallel sparse matrix decomposition heuristics and associated tools.