My research lab, CudaOpt, is equipped with high-performance hardware and software to
support AI and large-scale Optimization research.

Computing Hardware

    → 4 NVIDIA GPUs — 2×40 GB and 2×96 GB, for AI model training and large-scale optimization
    → 2 High-Performance CPU nodes — 56–60 cores (112–120 threads) per node
    → System Memory — 256–512 GB RAM

Software & Computing Environment

    → Gurobi Optimizer & IPOPT — large-scale mathematical and nonlinear optimization
    → Python — TensorFlow, PyTorch, Keras for AI research
    → CUDA — GPU-accelerated computing and parallel optimization