cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia · HackerPapers discussions

cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia — mentioned by dsfcxv

Sat, 21 Sep 2024 18:53:22 GMT

Their numerical results with GPUs, compared to Gurobi, are quite impressive [1]. In my opinion (unless I'm missing something), the key benefits of their algorithms lie in the ability to leverage GPUs and the fact that there’s no need to store factorization in memory. However, if the goal is to solve a small problem on a CPU that fits comfortably in memory, there may be no need to use this approach. [1] https://arxiv.org/pdf/2311.12180

Paper and discussion history. A mention is not an endorsement.

cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia — mentioned by optcoder

Sat, 21 Sep 2024 17:52:18 GMT

The three linked papers seem to be old, but the broader impact section mentioned cupdlp, which is more recent and has interesting numerical comparisons with commercial solvers: https://arxiv.org/abs/2311.12180, https://arxiv.org/pdf/2312.14832. It is CPU vs GPU, though, not sure how fair it is.

Paper and discussion history. A mention is not an endorsement.

cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia — HN submission

Wed, 03 Jan 2024 23:28:35 GMT

Cupdlp.jl: A GPU Impl. Of Restarted Primal-Dual Hybrid Gradient for LP in Julia

3 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.