GPUAM

GPUAM computes molecular electrostatic potentials (MEPs) using GPU-accelerated quantum chemistry methods to characterize electrostatic environments relevant to chemical reactivity, drug interactions, and materials properties.

Key Features:

• Quantum Chemistry Methods: Employs Gaussian functions within quantum chemistry methods to generate molecular electrostatic potentials (MEPs).
• Full-Range Rys Polynomials: Implements full-range Rys polynomials with nodes and weights computed in each GPU thread for precise integration over molecular surfaces.
• High Angular Moments Handling: Solves integrals for high angular moments using a one-dimensional vertical recurrence relation to enhance accuracy and stability.
• CUDA-C Programming Techniques: Implements the computation in CUDA-C to exploit GPU resources for accelerated evaluation of integrals and potentials.
• Stability and Efficiency: Demonstrates stability and computational efficiency on GPUs, reducing computation times compared to CPU-based implementations.

Scientific Applications:

• Chemical Reactivity Analysis: Provides MEPs to assess reactive sites and intermolecular electrostatic interactions.
• Drug Design and Development: Predicts atomic-level electrostatic interactions relevant to ligand design and evaluation.
• Material Science: Analyzes electrostatic interactions that govern material properties.

Methodology:

Full-range Rys polynomials are evaluated with nodes and weights computed per GPU thread; integrals for high angular moments are solved via a one-dimensional vertical recurrence relation; the implementation is in CUDA-C using per-thread GPU parallelism.