Using OpenCL, we developed a cross-platform software to compute electrical excitation conduction in cardiac tissue. OpenCL allowed the software to run parallelized and on different computing devices (e.g., CPUs and GPUs).We used the macroscopic mono-domain model for excitation conduction and an atrial myocyte model by Courtemanche et al. for ionic currents. On a CPU with 12 HyperThreading-enabled Intel Xeon 2.7 GHz cores, we achieved a speed-up of simulations by a factor of 1.6 against existing software that uses OpenMPI. On two high-end AMD FirePro D700 GPUs the OpenCL software ran 2.4 times faster than the OpenMPI implementation. The more nodes the discretized simulation domain contained, the higher speed-ups were achieved.
Student Theses (1)
Z. Zhamoliddinov. Activation Time Imaging based Generation of Purkinje Trees: Forward and Inverse Problem based Evaluation. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Bachelorarbeit. 2015
The spread of electrical activity through the ventricular myocardium produces the QRS complex on the ECG and the Purkinje tree is the major component in the correct elec- trical sequence initiation of the ventricles. Unfortunately, no in-vivo imaging system can visualize the Purkinje system and its activity in individual patients. On the other hand, the precise activation sequence of the ventricles is needed in order to reconstruct proper- ly the depolarization and repolarization process in the individuals heart and therefore the proper ECG waveforms. The aim of this Bachelor thesis is to use ECG imaging (the inverse problem of ECG) to estimate local activation times (activation time imaging) based on body surface potential maps (BSPM). The task of the thesis is to prove the concept: to use a predefined stimulation protocol for simulating the electrical excitation propagation in the heart and to perform a forward calculation in the corresponding torso model in order to generate a synthetic BSPM during the QRS complex (see Chapter 3.2). The monodomain model is selected as an excitation propagation model (see Chap- ter 3.1.2). The synthetic BSPM data will be used to calculate local activation times by solving the inverse problem of ECG (see Chapter 3.5.3). For solving the inverse problem the Multi-Foci Search Algorithm of  has been applied (see Chapter 18.104.22.168). As a final point, it follows the evaluation of activation times reconstructions during the excitation propagation.