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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.