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2 results for “hypergraph partitioning”
Benchmark Hypergraphs and Detailed Experimental Results of "k-way Hypergraph Partitioning via n-Level Recursive Bisection"
<p>This dataset contains hypergraphs derived from three benchmark sets: The<br /> ISPD98 VLSI Circuit Benchmark Suite [1], the University of Florida Sparse Matrix Collec-<br /> tion [2] and the international SAT Competition 2014 [3]. From the latter, we randomly selected<br /> 100 instances from the application track and converted them into hypergraphs as follows:<br /> Each boolean variable (and its complement) is mapped to one vertex and each clause constitutes<br /> a net [41]. The Sparse Matrix Collection is organized into 172 groups and each group contains<br /> matrices of different application areas. From each group, we choose one matrix for each appli-<br /> cation area that has between 10 000 and 10 000 000 columns. In case multiple matrices fulfill<br /> our criteria, we randomly select one. In total, we include 192 matrices, which are translated into<br /> hypergraphs using the row-net model, i.e. each row is treated as a net and each column as<br /> a vertex. Empty rows are discarded. Both vertices and nets have unit weight. Together with the<br /> 18 ISPD98 VLSI instances , a total of 310 hypergraphs constitute our benchmark set. 4 Each of<br /> these hypergraphs is partitioned into k ∈ {2, 4, 8, 16, 32, 64, 128} blocks with ε = 0.03. For each<br /> value of k, a k-way partition is considered to be one test instance, resulting in a total of 2170<br /> instances.</p> <p>See the README for further information on the different files contained in this dataset.</p> <p>[1 ]C. J. Alpert. The ISPD98 Circuit Benchmark Suite. In Proc. of the 1998 Int. Symp. on Physical Design, ISPD ’98, pages 80–85, New York, 1998. ACM.<br /> [2] T. A. Davis and Y. Hu. The University of Florida Sparse Matrix Collection. ACM Trans. Math. Softw.,38(1):1:1–1:25, 2011.<br /> [3] A. Belov, D. Diepold, M. Heule, and M. Järvisalo. The SAT Competition 2014. http://www.satcompetition.org/2014/, 2014.</p>
A Benchmark Set for Multilevel Hypergraph Partitioning Algorithms
<p>DESCRIPTION<br> -------------------------------------------------------------------------------------------------------<br> This archive contains a large benchmark set for hypergraph partitioning algorithms.<br> All hypergraphs are unweighted (i.e., have unit edge and vertex weights) and use<br> the hMetis hypergraph input file format [1].</p> <p>BENCHMARK SETS<br> -------------------------------------------------------------------------------------------------------<br> Hypergraphs are derived from the following benchmark sets:<br> - The ISPD98 Circuit Benchmark Suite [2]<br> - The DAC 2012 Routability-Driven Placement Contest [3]<br> - The international SAT Competition 2014 [4]<br> - The University of Florida Sparse Matrix Collection (UF-SPM) [5]</p> <p>The benchmark set contains all ISPD98 and DAC2012 instances. Furthermore,<br> it contains 92 randomly selected instances from the application track of the SAT Competition 2014.<br> The Sparse Matrix Collection is organized into 172 groups and each group contains<br> matrices of different application areas. From each group, we chose one matrix for each application <br> area that has between 10 000 and 10.000.000 columns. In case multiple matrices fulfill<br> our criteria, we randomly selected one. In total, we include 192 matrices.</p> <p><br> HYPERGRAPH REPRESENTATION<br> -------------------------------------------------------------------------------------------------------<br> VLSI instances [2,3] are transformed into hypergraphs by converting the netlist into a<br> set of hyperedges. Sparse Matrices are translated into hypergraphs using the row-net model [6],<br> i.e. each row is treated as a net and each column as a vertex. SAT instances are converted into<br> three different hypergraph representations: In the literal model, each boolean literal is mapped to one<br> vertex and each clause constitutes a net [7]. In the primal model each variable is represented by a vertex<br> and each clause is represented by a net, whereas in the dual model the opposite is the case [8].</p> <p>FILE NAMES<br> -------------------------------------------------------------------------------------------------------<br> The origin of each hypergraph (and for SAT instances the hypergraph model) is encoded<br> into the file names as follows:<br> - Sparse Matrices : *.mtx.hgr<br> - DAC2012 : dac2012_superblue*.hgr<br> - ISPD98 : ISPD98_ibm*.hgr<br> - SAT-14 primal : sat14_*.cnf.primal.hgr<br> - SAT-14 dual : sat14_*.cnf.dual.hgr<br> - SAT-14 literal : sat14_*.cnf.hgr</p> <p>REFERENCES<br> -------------------------------------------------------------------------------------------------------<br> [1] http://glaros.dtc.umn.edu/gkhome/fetch/sw/hmetis/manual.pdf<br> [2] C. J. Alpert. The ISPD98 Circuit Benchmark Suite. In Proc. of the 1998 Int. Symp. on Physical Design, pages 80–85, New York, 1998. ACM.<br> [3] N. Viswanathan, C. Alpert, C. Sze, Z. Li, and Y/ Wei. The dac 2012 routability-driven placement contest and benchmark suite. In Proceedings of the 49th Annual Design Automation Conference, DAC ’12, pages 774–782<br> [4] A. Belov, D. Diepold, M. Heule, and M. Järvisalo. The SAT Competition 2014. http://www.satcompetition.org/2014/, 2014.<br> [5] T. A. Davis and Y. Hu. The University of Florida Sparse Matrix Collection. ACM Trans. Math. Softw.,38(1):1:1–1:25, 2011.<br> [6] Ü. V. Catalyürek and C. Aykanat. Hypergraph-partitioning-based decomposition for parallel sparse-matrix vector multiplication. IEEE Transactions on Parallel and Distributed Systems, 10(7):673–693, Jul 1999.<br> [7] D. A. Papa and I. L. Markov. Hypergraph Partitioning and Clustering. In T. F. Gonzalez, editor, Handbook of Approximation Algorithms and Metaheuristics. Chapman and Hall/CRC, 2007.<br> [8] Zoltan Mann and Pal Papp. Formula partitioning revisited. In Daniel Le Berre, editor, POS-14. Fifth Pragmatics of SAT workshop, volume 27 of EPiC Series in Computing, pages 41–56. EasyChair, 2014.</p>
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