D-PDLP is the first distributed multi-GPU framework for PDLP that uses 2D grid partitioning of the constraint matrix plus nonzero-aware and random-permutation strategies to scale PDHG iterations with low overhead and full FP64 accuracy.
Miplib 2017: data-driven compilation of the 6th mixed-integer programming library
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D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems
D-PDLP is the first distributed multi-GPU framework for PDLP that uses 2D grid partitioning of the constraint matrix plus nonzero-aware and random-permutation strategies to scale PDHG iterations with low overhead and full FP64 accuracy.