2 citations · 3 across the 18 of their papers we have counts for
4 papers · 1 filter
cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia
Haihao Lu, Jinwen Yang
In this paper, we provide an affirmative answer to the long-standing question: Are GPUs useful in solving linear programming? We present cuPDLP.jl, a GPU implementation of restarte…
A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming
Haihao Lu, Jinwen Yang
Convex quadratic programming (QP) is an important class of optimization problem with wide applications in practice. The classic QP solvers are based on either simplex or barrier me…
On the Geometry and Refined Rate of Primal-Dual Hybrid Gradient for Linear Programming
Haihao Lu, Jinwen Yang
We study the convergence behaviors of primal-dual hybrid gradient (PDHG) for solving linear programming (LP). PDHG is the base algorithm of a new general-purpose first-order method…
On a Unified and Simplified Proof for the Ergodic Convergence Rates of PPM, PDHG and ADMM
Haihao Lu, Jinwen Yang
We present a unified viewpoint of proximal point method (PPM), primal-dual hybrid gradient (PDHG) and alternating direction method of multipliers (ADMM) for solving convex-concave…