Recursive bi-partitioning of netlists for large number of partitions

Abstract

In many application in VLSI CAD, a given netlist has to be partitioned into smaller sub-designs which can be handled much better. In this paper we present a new recursive bi-partitioning algorithm that is especially applicable, if a large number of final partitions, e.g. more than 1000, has to be computed. The algorithm consists of two steps. Based on recursive splits the problem is divided into several sub-problems, but with increasing recursion depth more run time is invested. By this an initial solution is determined very fast. The core of the method is a second step, where a very powerful greedy algorithm is applied to refine the partitions. Experimental results are given that compare the new approach to state-of-the-art tools. The experiments show that the new approach outperforms the standard techniques with respect to run time and quality. Furthermore, the memory usage is very low and is reduced in comparison to other methods by more than a factor of four.

A Multiway Design-driven Partitioning Algorithm for Distributed Verilog Simulation

“…There are two kinds of multiway partitioning algorithms, a flat k-way partitioning [30] and a recursive multiway partitioning algorithm [31][32][33]. The recursive approach applies bi-partitioning recursively until the desired number of partitions is obtained, while the direct approach forsakes recursion.…”

Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulation

“…Most graph partitioning approaches are hierarchical and split a graph into two partitions per recursion level [14, 15]. Such an approach is called bi‐partitioning, and recursive bi‐partitioning can create a k‐partitioning, but it is not a computationally efficient means of doing so [16] [While not computationally efficient, recursive bi‐partitioning has been shown to make more efficient use of memory resources [17]]. Some specialised partitioning methods have been developed for use in distributed OPF, such as the spectral method of [15].…”