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From Reactive Systems to Cyber-Physical Systems pp 9–34Cite as

A Comprehensive Comparison of GPU Implementations of Cardiac Electrophysiology Models

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11500))

Abstract

Cardiac disease is the leading cause of death in developed countries, and arrhythmias, which are disorders in the regular generation and propagation of electrical waves that trigger contraction, form a major class of heart diseases. Computational techniques have proved to be useful in the study and understanding of cardiac arrhythmias. However, the computational cost associated with solving cardiac models makes them especially challenging to solve. Traditionally, hardware available on personal computers has been insufficient for such models; instead, supercomputers have been employed to overcome the computational costs of cardiac simulations. However, in recent years substantial advances in the computational power of graphics processing units (GPUs), combined with their modest prices and widespread availability, have made them an attractive alternative to high-performance computing using supercomputers. With greater use of GPUs, however, new challenges have emerged. GPUs must be programmed using their own languages or extensions of other languages, and, at present, there are a number of languages that support general-purpose GPU codes with substantial differences in programming ease and available levels of optimization. In this work, we present the implementation of cardiac models in several major GPU languages without language-specific optimization and compare their performance for different levels of model complexity and domain sizes.

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Acknowledgements

This work was supported in part by the National Science Foundation under grants CNS-1446312(EMC) and by CMMI-1762553 (FHF and AK). EMC, AK, YS, and FHF, also collaborated while at Kavli Institute for Theoretical Physics (KITP) and thus research was also supported in part by NSF Grant No. PHY-1748958, NIH Grant No. R25GM067110, and the Gordon and Betty Moore Foundation Grant No. 2919.01.

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  1. Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Abouzar Kaboudian, Hector Augusto Velasco-Perez, Elizabeth M. Cherry & Flavio H. Fenton

  2. Emory University, Atlanta, GA, 30322, USA

    Shahriar Iravanian

  3. California State University, Northridge, CA, 91330, USA

    Yohannes Shiferaw

  4. Rochester Institute of Technology, Rochester, NY, 14623, USA

    Elizabeth M. Cherry

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  1. Abouzar Kaboudian
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  3. Shahriar Iravanian
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  4. Yohannes Shiferaw
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  5. Elizabeth M. Cherry
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  6. Flavio H. Fenton
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Correspondence to Abouzar Kaboudian .

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  1. Technische Universität Wien, Vienna, Austria

    Ezio Bartocci

  2. University of Maryland, College Park, MD, USA

    Rance Cleaveland

  3. Technische Universität Wien, Vienna, Austria

    Radu Grosu

  4. University of Pennsylvania, Philadelphia, PA, USA

    Oleg Sokolsky

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Kaboudian, A., Velasco-Perez, H.A., Iravanian, S., Shiferaw, Y., Cherry, E.M., Fenton, F.H. (2019). A Comprehensive Comparison of GPU Implementations of Cardiac Electrophysiology Models. In: Bartocci, E., Cleaveland, R., Grosu, R., Sokolsky, O. (eds) From Reactive Systems to Cyber-Physical Systems. Lecture Notes in Computer Science(), vol 11500. Springer, Cham. https://doi.org/10.1007/978-3-030-31514-6_2

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