3 papers
cs.SI2026
Neural Acceleration for Graph Partitioning
Joshua Dennis Booth, Vishvam Patel
Graph Partitioning is a critical problem in numerous scientific and engineering domains including social network analysis, VLSI design, and many more. Spectral methods are known to…
cs.DC2024
Neural Acceleration of Incomplete Cholesky Preconditioners
Joshua Dennis Booth, Hongyang Sun, Trevor Garnett
The solution of a sparse system of linear equations is ubiquitous in scientific applications. Iterative methods, such as the Preconditioned Conjugate Gradient method (PCG), are nor…
cs.MS2018
Javelin: A Scalable Implementation for Sparse Incomplete LU Factorization
Joshua Dennis Booth, Gregory Bolet
In this work, we present a new scalable incomplete LU factorization framework called Javelin to be used as a preconditioner for solving sparse linear systems with iterative methods…