Accelerating simulations of cardiac electrical dynamics through a multi-GPU platform and an optimized data structure.

Autor: Vasconcellos EC; Institute of Computing, Fluminense Federal University, Niterói, Brazil., Clua EWG; Institute of Computing, Fluminense Federal University, Niterói, Brazil., Fenton FH; School of Physics, Georgia Institute of Technology, Atlanta, Georgia., Zamith M; Department of Computer Science, Universidade Federal Rural do Rio de Janeiro, Seropédica, Brazil.
Jazyk: angličtina
Zdroj: Concurrency and computation : practice & experience [Concurr Comput] 2020 Mar 10; Vol. 32 (5). Date of Electronic Publication: 2019 Oct 23.
DOI: 10.1002/cpe.5528
Abstrakt: Simulations of cardiac electrophysiological models in tissue, particularly in 3D require the solutions of billions of differential equations even for just a couple of milliseconds, thus highly demanding in computational resources. In fact, even studies in small domains with very complex models may take several hours to reproduce seconds of electrical cardiac behavior. Today's Graphics Processor Units (GPUs) are becoming a way to accelerate such simulations, and give the added possibilities to run them locally without the need for supercomputers. Nevertheless, when using GPUs, bottlenecks related to global memory access caused by the spatial discretization of the large tissue domains being simulated, become a big challenge. For simulations in a single GPU, we propose a strategy to accelerate the computation of the diffusion term through a data-structure and memory access pattern designed to maximize coalescent memory transactions and minimize branch divergence, achieving results approximately 1.4 times faster than a standard GPU method. We also combine this data structure with a designed communication strategy to take advantage in the case of simulations in multi-GPU platforms. We demonstrate that, in the multi-GPU approach performs, simulations in 3D tissue can be just 4× slower than real time.
Competing Interests: CONFLICT OF INTEREST The authors declare no potential conflict of interests.
Databáze: MEDLINE
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