The pairing heap: a new form of self-adjusting heap
Algorithmica
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
A polynomial algorithm for b-matchings: an alternative approach
Information Processing Letters
A faster strongly polynomial minimum cost flow algorithm
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Pairing heaps: experiments and analysis
Communications of the ACM
Handbook of combinatorics (vol. 1)
Mesh refinement via bidirected flows: modeling, complexity, and computational results
Journal of the ACM (JACM)
On the efficiency of pairing heaps and related data structures
Journal of the ACM (JACM)
Implementing weighted b-matching algorithms: towards a flexible software design
Journal of Experimental Algorithmics (JEA)
Complexity and Modeling Aspects of Mesh Refinement into Quadrilaterals
ISAAC '97 Proceedings of the 8th International Symposium on Algorithms and Computation
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Matching algorithms.
Clustering with r-regular graphs
Pattern Recognition
Proteus: a topology malleable data center network
Hotnets-IX Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks
Algorithm engineering: bridging the gap between algorithm theory and practice
Algorithm engineering: bridging the gap between algorithm theory and practice
B-Matching for spectral clustering
ECML'06 Proceedings of the 17th European conference on Machine Learning
OSA: an optical switching architecture for data center networks with unprecedented flexibility
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Quadrilateral surface meshes without self-intersecting dual cycles for hexahedral mesh generation
Computational Geometry: Theory and Applications
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We present an experimental study of an implementation of weighted perfect b-matching based on the primal-dual blossom algorithm. Although this problem is well-understood in theory and efficient algorithms are known, only little experience with implementations is available. In this paper several algorithmic variants are compared on synthetic and application problem data of very sparse graphs. This study was motivated by the practical need for an efficient b-matching solver for the latter application, namely as a subroutine in our approach to a mesh refinement problem in computer-aided design (CAD).Linear regression and operation counting is used to analyze code variants. The experiments confirm that a fractional jump-start speeds up the algorithm, they indicate that a variant based on pairing heaps is slightly superior to a k-heap variant, and that scaling of large b-values is not necessary, whereas a delayed blossom shrinking heuristic significantly improves running times only for graphs with average degree two. The fastest variant of our implementation appears to be highly superior to a code by Miller and Pekny (1995).