A GPU-accelerated Direct-sum Boundary Integral Poisson-Boltzmann Solver

TL;DR

This paper introduces a GPU-accelerated boundary integral method for solving the Poisson-Boltzmann equation, achieving significant speed-ups and maintaining accuracy for biomolecular electrostatics calculations.

Contribution

It presents a novel GPU-based parallel implementation of a boundary integral solver for the Poisson-Boltzmann equation, enabling faster computations on complex biomolecular surfaces.

Findings

Achieves 120-150X speed-up over CPU implementation.

Handles molecular surfaces with up to 300,000 elements in under 10 minutes.

Maintains accuracy and fast convergence in numerical tests.

Abstract

In this paper, we present a GPU-accelerated direct-sum boundary integral method to solve the linear Poisson-Boltzmann (PB) equation. In our method, a well-posed boundary integral formulation is used to ensure the fast convergence of Krylov subspace based linear algebraic solver such as the GMRES. The molecular surfaces are discretized with flat triangles and centroid collocation. To speed up our method, we take advantage of the parallel nature of the boundary integral formulation and parallelize the schemes within CUDA shared memory architecture on GPU. The schemes use only $11N+6N_c$ size-of-double device memory for a biomolecule with $N$ triangular surface elements and $N_c$ partial charges. Numerical tests of these schemes show well-maintained accuracy and fast convergence. The GPU implementation using one GPU card (Nvidia Tesla M2070) achieves 120-150X speed-up to the implementation using one CPU (Intel L5640 2.27GHz). With our approach, solving PB equations on well-discretized molecular surfaces with up to 300,000 boundary elements will take less than about 10 minutes, hence our approach is particularly suitable for fast electrostatics computations on small to medium biomolecules.