Presentation
Hyspecpro: Scalable Hypergraph Partitioning via Spectral Projection Optimization
DescriptionModern VLSI designs contain tens of billions of components, making scalable hypergraph partitioning essential for parallel or hierarchical optimization. Although the multilevel partitioning paradigm remains effective, coarsening can distort structural information—especially in hypergraphs with many high-degree hyperedges—leading to substantial refinement overhead and limited scalability. Recent works incorporate spectral information, but only heuristically and without directly targeting the partitioning objective or enforcing constraints, leaving refinement to recover quality. We introduce HySpecPro, a single-level hypergraph partitioner that performs end-to-end optimization in a spectral embedding space. HySpecPro constructs embeddings from a bipartite Laplacian and performs efficient projection-based search, supported by a fully GPU-accelerated implementation. Experiments show that HySpecPro delivers cut quality comparable to state-of-the-art multilevel methods while scaling linearly with the total hyperedge degree.
Event Type
Research Manuscript
TimeTuesday, July 285:18pm - 5:30pm PDT
LocationMtg Room 203AB