A User Manual for cuHALLaR: A GPU Accelerated Low-Rank Semidefinite Programming Solver

Aguirre, Jacob, Cifuentes, Diego, Guigues, Vincent, Monteiro, Renato D. C., Nascimento, Victor Hugo, Sujanani, Arnesh

arXiv.org Artificial Intelligence 

We present a Julia-based interface to the precompiled HALLaR and cuHALLaR binaries for large-scale semidefinite programs (SDPs). Both solvers are established as fast and numerically stable, and accept problem data in formats compatible with SDPA and a new enhanced data format taking advantage of Hybrid Sparse Low-Rank (HSLR) structure. The interface allows users to load custom data files, configure solver options, and execute experiments directly from Julia. A collection of example problems is included, including the SDP relaxations of the Matrix Completion and Maximum Stable Set problems.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found