NVIDIA cuOpt adds mPDLP multi‑GPU LP solver that scales to 100M+ variables
NVIDIA released mPDLP, a Multi‑GPU Primal‑Dual hybrid gradient solver in cuOpt that shards large linear programs across NVLink‑connected GPUs. mPDLP cuts per‑GPU peak memory (up to 6× vs single‑GPU PDLP), supports problems up to 2.1B nonzeros, and in DGX B200 benchmarks shows PDLP‑step speedups up to 11.4× and typical overall gains of 1.2×–2.5× vs prior D‑PDLP; partner cases reported ~3.3× (Kinaxis, 135M variables) and >5× (PSR, 185M variables). A tutorial and source code are available on GitHub.