A GPU-accelerated direct-sum boundary integral Poisson–Boltzmann solver Original Research Article

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 image size-of-double device memory for a biomolecule with image triangular surface elements and image 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 2.27 GHz). With our approach, solving PB equations on well-discretized molecular surfaces with up to 300,000 boundary elements will take less than about 10 min, hence our approach is particularly suitable for fast electrostatics computations on small to medium biomolecules.