Parallel Computing for Long-Time Simulations of Calcium Waves in a Heart Cell

Abstract

Calcium waves are modeled by parabolic partial differential equations, whose simulation codes contain Krylov subspace methods as computational kernels. This paper presents GPU-based parallel computations for the conjugate gradient method applied to the finite difference discretization of a Poisson equation as prototype problem for the computational kernel. The CUDA algorithm tests the three memory systems of global memory, texture memory, and shared memory of a CUDA-enabled GPU. Due to the caching mechanism and coalesced read/write operations, the CUDA algorithm using global memory and single precision floating point numbers outperforms algorithms accessing texture memory and the shared memory. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)