{"ID":2849115,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.24429","arxiv_id":"2510.24429","title":"Concurrent Crossover for PDHG","abstract":"First-order methods based on the PDHG algorithm have recently emerged as a viable option for efficiently solving large-scale linear programming problems. One highly desirable property of these methods is that they can make effective use of GPUs. One undesirable property is that, as first-order methods, their convergence can be extremely slow. This property forces one to decide how much accuracy is truly necessary when solving an LP problem. This paper looks at whether a parallel, concurrent crossover scheme can help to obtain highly accurate solutions without sacrificing the benefits of these new approaches.","short_abstract":"First-order methods based on the PDHG algorithm have recently emerged as a viable option for efficiently solving large-scale linear programming problems. One highly desirable property of these methods is that they can make effective use of GPUs. One undesirable property is that, as first-order methods, their convergenc...","url_abs":"https://arxiv.org/abs/2510.24429","url_pdf":"https://arxiv.org/pdf/2510.24429v1","authors":"[\"Edward Rothberg\"]","published":"2025-10-28T13:57:10Z","proceeding":"math.OC","tasks":"[\"math.OC\"]","methods":"[]","has_code":false}