Accelerating cardiac excitation spread simulations using graphics processing units
Verfasser/ VerfasserinRocha, Bernado M. ; Campos, Fernando ; Amorim, Ronan ; Plank, Gernot ; Weber dos Santos, Rodrigo ; Liebmann, Manfred ; Haase, Gundolf
Erschienen in
Concurrency and Computation: Practice and Experience, 2010, Jg. 23, H. 7, S. 708-720
ErschienenJohn Wiley & Sons
Accepted version
DokumenttypAufsatz in einer Zeitschrift
Schlagwörter (EN)cardiac electrophysiology; / graphic processing units; / high performance computing
Schlagwörter (GND)Elektrophysiologie / Hochleistungsrechnen / Online-Publikation
URNurn:nbn:at:at-ubg:3-587 Persistent Identifier (URN)
 Das Werk ist frei verfügbar
Accelerating cardiac excitation spread simulations using graphics processing units [0.8 mb]
Zusammenfassung (Englisch)

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 quadcore machine, parts of the code are even accelerated by a factor of 180.