On implementation choices for iterative improvement partitioning algorithms

Iterative improvement partitioning algorithms such as the FM algorithm of Fiduccia and Mattheyses 8 , the algorithm of Krishnamurthy 13 , and Sanchis's extensions of these algorithms to multi-way partitioning 16 , all rely on e cient data structures to select the modules to be moved from one partition to the other. The implementation choices for one of these data structures, the gain bucket, is investigated. Surprisingly, selection from gain buckets maintained as LIFO Last-In-First-Out stacks leads to signi cantly better results than gain buckets maintained randomly as in previous studies of the FM algorithm 13 16  or as FIFO First-In-First-Out queues. In particular, LIFO buckets result in a 36 improvement over random buckets and a 43 improvementover FIFO buckets for minimum-cut bisection. Eliminatingrandomization from the bucket selection not only improves the solution quality, but has a greater impact on FM performance than adding the Krishnamurthy gain vector. The LIFO...

• Type: Conference
• Year: 1995
• Where: EURODAC
• Authors: Lars W. Hagen, Dennis J.-H. Huang, Andrew B. Kahng
• Keywords: Buckets, EURODAC 1995, Gain Buckets, LIFO Gain Buckets, VHDL