In this paper, we present a new multilevel k-way hypergraph partitioning al
gorithm that substantially outperforms the existing state-of-the-art K-PM/L
R algorithm for multiway partitioning, both for optimizing local as well as
global objectives. Experiments on the ISPD98 benchmark suite show that the
partitionings produced by our scheme are on the average 15% to 23% better
than those produced by the K-PM/LR algorithm, both in terms of the hyperedg
e cut as well as the (K - 1) metric. Furthermore, our algorithm is signific
antly faster, requiring 4 to 5 times less time than that required by K-PM/L
R.