An efficient algorithm for the minimum capacity cut problem
Mathematical Programming: Series A and B
An Õ(n2) algorithm for minimum cuts
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
The Complexity of Multiterminal Cuts
SIAM Journal on Computing
Randomized algorithms
SlimCuts: graphcuts for high resolution images using graph reduction
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
An optimal component distribution algorithm based on MINLP
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
From static code distribution to more shrinkage for the multiterminal cut
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
| Hi-index | 0.00 |
The problem of optimally allocating the components of a distributed program over several machines can be shown to reduce to a multi-terminal graph cutting problem. In case of three of more terminals, this problem has been shown to be NP-hard. This paper introduces a number of heuristic graph algorithms for use in partitioning distributed object applications --- that is, for deciding which objects should be placed on which machines in order to minimize communication and achieve best overall performance of the application. These heuristics are particularly effective for graphs with characteristics specific to representative distributed object applications.