A simple approximation algorithm for the weighted matching problem
Information Processing Letters
A simpler linear time 2/3 - ε approximation for maximum weight matching
Information Processing Letters
A linear-time approximation algorithm for weighted matchings in graphs
ACM Transactions on Algorithms (TALG)
Approximating weighted matchings in parallel
Information Processing Letters
Linear time local improvements for weighted matchings in graphs
WEA'03 Proceedings of the 2nd international conference on Experimental and efficient algorithms
Linear time 1/2 -approximation algorithm for maximum weighted matching in general graphs
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
A parallel approximation algorithm for the weighted maximum matching problem
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
The university of Florida sparse matrix collection
ACM Transactions on Mathematical Software (TOMS)
| Hi-index | 0.00 |
A linear time approximation algorithm for the weighted matching problem is presented using the partitioned global address space model (PGAS). The problem of finding a maximum weight matching in a graph is central to many areas of combinatorial scientific computing. Even though the exact algorithm runs in polynomial time, a fast approximate solution is often sufficient. Drake and Hougardy developed a parallel 1 -- ε approximation algorithm for the PRAM model that is not feasible in practice because it requires O(n8/ε) processes. The PGAS model enables an intuitive parallel implementation of a linear 2/3 -- ε approximation algorithm for the weighted matching problem. Through the use of atomic memory operations, a parallel algorithm is developed that is very similar to its serial counterpart.