GenPart 2.0: Enhanced Hypergraph Partitioning with Vertex Weight Handling using a Generative Model

This article introduces GenPart 2.0, an enhanced version of the hypergraph partitioner GenPart. While GenPart was limited to handling only unit vertex weights, GenPart 2.0 extends capabilities to include varying vertex weights. This extension is achieved through a variational graph neural network-based generative model and new feature preparation techniques. GenPart 2.0 addresses hypergraph partitioning challenges by establishing an embedding space that adheres to normalized cut and balance constraints. The generative model in GenPart 2.0 is designed to explore various partitioning configurations within this embedding space. Further, it enhances partitioning solutions using the V-cycle method. Testing on VLSI circuit benchmarks, including ISPD98, ISPD2005, and Titan23, under various balance constraints, has demonstrated improved performance by GenPart 2.0.

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Publication Details

Journal
ACM Transactions on Design Automation of Electronic Systems
Published
2025-05-08
DOI
https://doi.org/10.1145/3735133
Primary Topic
VLSI and FPGA Design Techniques
Type
article
Field-Weighted Citation Impact
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article

GenPart 2.0: Enhanced Hypergraph Partitioning with Vertex Weight Handling using a Generative Model

Magi Chen, Ting-Chi Wang
ACM Transactions on Design Automation of Electronic Systems
VLSI and FPGA Design Techniques
article

GenPart 2.0: Enhanced Hypergraph Partitioning with Vertex Weight Handling using a Generative Model

Magi Chen, Ting-Chi Wang
article en

Abstract

This article introduces GenPart 2.0, an enhanced version of the hypergraph partitioner GenPart. While GenPart was limited to handling only unit vertex weights, GenPart 2.0 extends capabilities to include varying vertex weights. This extension is achieved through a variational graph neural network-based generative model and new feature preparation techniques. GenPart 2.0 addresses hypergraph partitioning challenges by establishing an embedding space that adheres to normalized cut and balance constraints. The generative model in GenPart 2.0 is designed to explore various partitioning configurations within this embedding space. Further, it enhances partitioning solutions using the V-cycle method. Testing on VLSI circuit benchmarks, including ISPD98, ISPD2005, and Titan23, under various balance constraints, has demonstrated improved performance by GenPart 2.0.

ACM Transactions on Design Automation of Electronic SystemsVol. 31(3)
National Tsing Hua University (TW)
Openalex Percentile: Top 92%
VLSI and FPGA Design Techniques
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