title: Near-real-time simulations of biolelectric activity in small mammalian hearts using graphical processing units.
abstract: Simulations of cardiac bioelectric phenomena remain a significant challenge despite continual advancements in computational machinery. Spanning large temporal and spatial ranges demands millions of nodes to accurately depict geometry, and a comparable number of timesteps to capture dynamics. This study explores a new hardware computing paradigm, the graphics processing unit (GPU), to accelerate cardiac models, and analyzes results in the context of simulating a small mammalian heart in real time. The ODEs associated with membrane ionic flow were computed on traditional CPU and compared to GPU performance, for one to four parallel processing units. The scalability of solving the PDE responsible for tissue coupling was examined on a cluster using up to 128 cores. Results indicate that the GPU implementation was between 9 and 17 times faster than the CPU implementation and scaled similarly. Solving the PDE was still 160 times slower than real time.
authors: Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada. vigmond@ucalgary.ca
authors: Edward J
authors: EJ
authors: Vigmond
authors: Patrick M
authors: PM
authors: Boyle
authors: L
authors: L
authors: Leon
authors: Gernot
authors: G
authors: Plank
mesh_terms: D000465:Algorithms; D000818:Animals; D001145:Arrhythmias, Cardiac / Q000175:diagnosis / Q000473:pathology; D003196:Computer Graphics; D003198:Computer Simulation; D003199:Computer Systems; D003201:Computers; D003952:Diagnostic Imaging / Q000379:methods*; D004594:Electrophysiology / Q000379:methods*; D006321:Heart / Q000033:anatomy & histology*; D006329:Heart Conduction System; D007091:Image Processing, Computer-Assisted / Q000379:methods; D011381:Programming Languages; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors