Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Computing the block triangular form of a sparse matrix
ACM Transactions on Mathematical Software (TOMS)
Fast parallel algorithms for graph matching problems
Fast parallel algorithms for graph matching problems
On Algorithms For Permuting Large Entries to the Diagonal of a Sparse Matrix
SIAM Journal on Matrix Analysis and Applications
Matching Theory (North-Holland mathematics studies)
Matching Theory (North-Holland mathematics studies)
A parallel approximation algorithm for the weighted maximum matching problem
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Design, implementation, and analysis of maximum transversal algorithms
ACM Transactions on Mathematical Software (TOMS)
Hi-index | 0.03 |
We discuss parallel algorithms for computing maximum matchings in bipartite graphs on multithreaded computers, reporting for the first time, good speedups for the maximum cardinality matching problem. Experiments with serial matching algorithms have shown that their performance is sensitive to the order in which vertices are processed. In the execution of a multithreaded parallel algorithm for matching, variability in the order in which different threads process vertices is unavoidable. This sensitivity raises the possibility that different execution orderings might adversely affect the performance of parallel matching algorithms. In this paper, we answer this question by showing that good speedups are attainable by careful design of algorithms tuned to the characteristics of multithreaded architectures and the structure of the input graphs. We discuss preliminary results from parallel implementations of two key algorithms (Hopcroft-Karp and Pothen-Fan) and their variants on three multithreaded platforms (Cray XMT, AMD Opteron and Intel Nehalem) using a carefully chosen test set from real-world applications as well as synthetical graphs.