PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration

TL;DR

PyClustrPath is a Python package that efficiently generates clustering paths using convex clustering with GPU acceleration, outperforming existing solvers in speed and scalability.

Contribution

It introduces a modular, GPU-accelerated Python package for convex clustering, enabling scalable and efficient generation of clustering paths.

Findings

Demonstrates superior performance over existing solvers

Efficient GPU acceleration for convex clustering

Scalable modular design for future algorithm integration

Abstract

Convex clustering is a popular clustering model without requiring the number of clusters as prior knowledge. It can generate a clustering path by continuously solving the model with a sequence of regularization parameter values. This paper introduces {\it PyClustrPath}, a highly efficient Python package for solving the convex clustering model with GPU acceleration. {\it PyClustrPath} implements popular first-order and second-order algorithms with a clean modular design. Such a design makes {\it PyClustrPath} more scalable to incorporate new algorithms for solving the convex clustering model in the future. We extensively test the numerical performance of {\it PyClustrPath} on popular clustering datasets, demonstrating its superior performance compared to the existing solvers for generating the clustering path based on the convex clustering model. The implementation of {\it PyClustrPath} can be found at: https://github.com/D3IntOpt/PyClustrPath.