GPU Accelerated Simulation of Cardiac Activities

Yu, Renbo; Zhang, Yin; Zhang, Sanyuan; Chiang, Patricia; Cai, Yiyu; Zheng, Jianmin; Mak, Koon Hou

doi:10.4304/jcp.5.11.1700-1705

Cited by 4 publications

(4 citation statements)

References 21 publications

(15 reference statements)

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“…Cardiac arrhythmia research project (CARP) takes 6.4 h for simulating 200 ms of cardiac activity in a 64 processor machine (Mitchell, 2010 ). Many architectures based on GPU are developed to reduce the computation time required for simulating bidomain equations (Bordas et al, 2009 ; Yu et al, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

2015

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Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias.

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Section: Discussionmentioning

confidence: 99%

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

2015

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“…Recently, the utilization of Graphic Processing Units (GPUs) instead of CPUs in cardiac simulations is being paid more and more attention [5,6]. Each GPU may contain hundreds of stream multiprocessors.…”

Section: Introductionmentioning

confidence: 99%

“…CUDA (the Compute Unified Device Architecture) was used as the developing platform. In CUDA [6], the GPU is viewed as a computing device suitable for parallel data applications. It has its own device random access memory and may run a very high number of threads in parallel.…”

Section: Introductionmentioning

confidence: 99%

Accelerating sino-atrium computer simulations with graphic processing units

Zhang

Xiao

Lin

2015

BME

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Abstract. Sino-atrial node cells (SANCs) play a significant role in rhythmic firing. To investigate their role in arrhythmia and interactions with the atrium, computer simulations based on cellular dynamic mathematical models are generally used. However, the large-scale computation usually makes research difficult, given the limited computational power of Central Processing Units (CPUs). In this paper, an accelerating approach with Graphic Processing Units (GPUs) is proposed in a simulation consisting of the SAN tissue and the adjoining atrium. By using the operator splitting method, the computational task was made parallel. Three parallelization strategies were then put forward. The strategy with the shortest running time was further optimized by considering block size, data transfer and partition. The results showed that for a simulation with 500 SANCs and 30 atrial cells, the execution time taken by the non-optimized program decreased 62% with respect to a serial program running on CPU. The execution time decreased by 80% after the program was optimized. The larger the tissue was, the more significant the acceleration became. The results demonstrated the effectiveness of the proposed GPU-accelerating methods and their promising applications in more complicated biological simulations.

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“…GPUs also have been used for intracellular calcium dynamics within a single cell using Monte Carlo simulations, where a factor of 15,000 reduction in time compared to previous studies was found [16]. In addition to electrophysiological dynamics, GPUs have been used to accelerate heart manipulations to enhance intervention simulations such as catheter positioning [43], surgical deformation [26], simple contractions [42,44], and ECG generation [36,37].…”

Section: Related Workmentioning

confidence: 99%

Toward real-time simulation of cardiac dynamics

Bartocci

Cherry

Glimm

et al. 2011

Proceedings of the 9th International Conference on Computational Methods in Systems Biology

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We show that through careful and model-specific optimizations of their GPU implementations, simulations of realistic, detailed cardiac-cell models now can be performed in 2D and 3D in times that are close to real time using a desktop computer. Previously, large-scale simulations of detailed mathematical models of cardiac cells were possible only using supercomputers. In our study, we consider five different models of cardiac electrophysiology that span a broad range of computational complexity: the two-variable Karma model, the four-variable Bueno-Orovio-Cherry-Fenton (BCF) model, the eight-variable Beeler-Reuter (BR) model, the 19-variable Ten Tusscher-Panfilov (TP) model, and the 67-variable Iyer-Mazhari-Winslow(IMW) model. For each of these models, we treat both their single-and double-precision versions and demonstrate linear or even sub-linear growth in simulation times with an increase in the size of the grid used to model cardiac tissue. We also show that our GPU implementations of these models can increase simulation speeds to near real-time for simulations of complex spatial patterns indicative of cardiac arrhythmic disorders, including spiral waves and spiral wave breakup. The achievement of real-time applications without the need for supercomputers may facilitate the adoption of modeling-based clinical diagnostics and treatment planning, including patient-specific electrophysiological studies, in the near future.

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GPU Accelerated Simulation of Cardiac Activities

Cited by 4 publications

References 21 publications

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

Accelerating sino-atrium computer simulations with graphic processing units

Toward real-time simulation of cardiac dynamics

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