FastAlign: Scalable Optimal Transport Algorithm for Network Alignment

Jul 15, 2026

Researchers introduce FastAlign, a sparsity-aware framework for optimal transport-based network alignment. FastAlign maintains alignment quality comparable to state-of-the-art methods while significantly improving computational efficiency, achieving up to 9.45x speedup on CPU and 32.54x on GPU. The method leverages mixed sparse-dense operations and custom kernel fusion to address scalability challenges in large-scale network alignment.

Why it matters: This work enables efficient analysis of large-scale networks, addressing a major scalability bottleneck in network alignment tasks relevant to fields such as social network analysis and fraud detection.

Full story at: arXiv Machine Learning ↗