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Accelerating cardiac excitation spread simulations using graphics processing units
Author(s) -
Rocha B. M.,
Campos F. O.,
Amorim R. M.,
Plank G.,
Santos R. W. dos,
Liebmann M.,
Haase G.
Publication year - 2011
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1683
Subject(s) - computer science , cardiac electrophysiology , graphics , ordinary differential equation , graphics processing unit , computational science , partial differential equation , multi core processor , cuda , parallel computing , code (set theory) , differential equation , computer engineering , computer graphics (images) , electrophysiology , medicine , physics , set (abstract data type) , quantum mechanics , programming language
The modeling of the electrical activity of the heart is of great medical and scientific interest, because it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. The cardiac electrophysiology may be simulated by solving a partial differential equation coupled to a system of ordinary differential equations describing the electrical behavior of the cell membrane. The numerical solution is, however, computationally demanding because of the fine temporal and spatial sampling required. The demand for real‐time high definition 3D graphics made the new graphic processing units (GPUs) a highly parallel, multithreaded, many‐core processor with tremendous computational horsepower. It makes the use of GPUs a promising alternative to simulate the electrical activity in the heart. The aim of this work is to study the performance of GPUs for solving the equations underlying the electrical activity in a simple cardiac tissue. In tests on 2D cardiac tissues with different cell models it is shown that the GPU implementation runs 20 times faster than a parallel CPU implementation running with 4 threads on a quad–core machine, parts of the code are even accelerated by a factor of 180. Copyright © 2010 John Wiley & Sons, Ltd.