A pure-Julia, hardware-agnostic, batchable parallel implementation of Primal-Dual hybrid gradient for Linear Programming (PDLP) and its variants.
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Updated
Sep 7, 2026 - Julia
A pure-Julia, hardware-agnostic, batchable parallel implementation of Primal-Dual hybrid gradient for Linear Programming (PDLP) and its variants.
Build GAMS and GAMSPy solver link for NVIDIA cuOpt PDLP solver
A from-scratch branch-and-cut MIP solver in C++23 with Python bindings (early development)
A linear-programming solver that runs on the GPU: restarted PDHG (PDLP) as WebGPU compute shaders, native and in the browser. Every Optimal is re-verified in CPU f64.
Sovereign LP/MILP/QP solver core — from-scratch simplex, B&B, ADMM QP + GPU first-order PDHG (pip install igaos)
ROCm/HIP port of cuPDLP-C for AMD Radeon 890M / gfx1150 with cross-device CUDA/ROCm benchmarks.
This project implements a sparse Primal–Dual Hybrid Gradient (PDHG) solver for linear programs in standard form.
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