Benchmark Sets and Experimental Results for "High-Quality Multi-Constraint Hypergraph Partitioning via Greedy Rebalancing"

set_h.zip: benchmark set of 50 small to medium hypergraphs with 2-dimensional node weights (unit weights, degree)

set_v.zip: benchmark set of 27 small to medium hypergraphs from VLSI design with 3-dimensional node weights (unit weights, degree, area of component)

set_v_prime.zip: identical to Set V, but with 3 additional weight dimensions containing uniform random weights (6 dimensions in total)

set_r.zip: benchmark set of 33 large regular graphs (i.e., graphs with low degree variance, such as mesh graphs) with 2-dimensional node weights (unit weights, degree)

set_i.zip: benchmark set of 34 large irregular graphs (i.e., graphs with high degree variance, such as social networks) with 2-dimensional node weights (unit weights, degree)

stats_hg.csv: general statistics for Set H

stats_vlsi.csv: general statistics for Set V

stats_regular.csv: general statistics for Set R

stats_irregular.csv: general statistics for Set I

results_ablation.zip: experimental results for our ablation study

results_refinement.zip: experimental results for our evaluation of refinement algorithms

results_fallback.zip: experimental results for our evaluation of fallback rating functions
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results_comparison.zip: experimental results for our comparison to the state of the art