5 papers · 1 filter
A User Manual for cuHALLaR: A GPU Accelerated Low-Rank Semidefinite Programming Solver
Jacob Aguirre, Diego Cifuentes, Vincent Guigues +3
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 numericall…
cuHALLaR: A GPU Accelerated Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming
Jacob M. Aguirre, Diego Cifuentes, Vincent Guigues +3
This paper introduces cuHALLaR, a GPU-accelerated implementation of the HALLaR method proposed in Monteiro et al. 2024 for solving large-scale semidefinite programming (SDP) proble…
Efficient parameter-free restarted accelerated gradient methods for convex and strongly convex optimization
Arnesh Sujanani, Renato D. C. Monteiro
This paper develops a new parameter-free restarted method, namely RPF-SFISTA, and a new parameter-free aggressive regularization method, namely A-REG, for solving strongly convex a…
Complexity and numerical experiments of a new adaptive generic proximal bundle method
Vincent Guigues, Renato Monteiro, Benoit Tran
This paper develops an adaptive generic proximal bundle method, shows its complexity, and presents numerical experiments comparing this method with two bundle methods on a set of o…
A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach
Renato D. C. Monteiro, Arnesh Sujanani, Diego Cifuentes
This paper introduces HALLaR, a new first-order method for solving large-scale semidefinite programs (SDPs) with bounded domain. HALLaR is an inexact augmented Lagrangian (AL) meth…