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20242026
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math.OC2026

GPU-Accelerated Conic Quadratic Programming with Local Linear Convergence under Strict Complementarity

Hongpei Li, Yicheng Huang, Huikang Liu +2

We present PDHCG-CQP, a GPU-accelerated first-order solver for large-scale conic convex quadratic programming. PDHCG-CQP supports affine constraints and Cartesian products of nonne…

math.OC2026

A Curvature-Aware Rank-Adaptive Distributed Augmented-Lagrangian Solver for Large-Scale SDPs

Hongpei Li, Huikang Liu, Dongdong Ge +1

We present CARDAL (Curvature-Aware Rank-Adaptive Distributed Augmented Lagrangian), a distributed multi-GPU solver for large-scale semidefinite programs (SDPs) based on a rank-adap…

math.OC2026

D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems

Hongpei Li, Yicheng Huang, Huikang Liu +2

We present a distributed framework of the Primal-Dual Hybrid Gradient (PDHG) algorithm for solving massive-scale linear programming (LP) problems. Although PDHG-based solvers demon…

math.OC2026

A Practical GPU-Enhanced Matrix-Free Primal-Dual Method for Large-Scale Conic Programs

Zhenwei Lin, Zikai Xiong, Dongdong Ge +1

In this paper, we introduce a practical GPU-enhanced matrix-free first-order method for solving large-scale conic programming problems, which we refer to as PDCS, standing for the…

math.OC2026

A Technical Note on the Implementation and Use of PDCS

Zhenwei Lin, Zikai Xiong, Dongdong Ge +1

This technical note documents the implementation and use of the Primal-Dual Conic Programming Solver (PDCS), a first-order solver for large-scale conic optimization problems introd…

math.OC2026

FMIP: Joint Continuous-Integer Flow For Mixed-Integer Linear Programming

Hongpei Li, Hui Yuan, Han Zhang +4

Mixed-Integer Linear Programming (MILP) is a foundational tool for complex decision-making problems. However, the NP-hard nature of MILP presents a significant computational challe…