|Authors||N. Altanaite and J. Langguth|
|Editors||D. Kaeli and J. Cavazos|
|Title||GPU-based Acceleration of Detailed Tissue-Scale Cardiac Simulations|
|Project(s)||Meeting Exascale Computing with Source-to-Source Compilers|
|Publication Type||Proceedings, refereed|
|Year of Publication||2018|
|Conference Name||Proceedings of the 11th Workshop on General Purpose GPUs|
|Place Published||New York, NY, USA|
We present a GPU based implementation for tissue-scale 3D sim- ulations of the human cardiac ventricle using a physiologically realistic cell model. Computational challenges in such simulations arise from two factors, the rst of which is the sheer amount of computation when simulating a large number of cardiac cells in a detailed model containing 104 calcium release units, 106 stochasti- cally changing ryanodine receptors and 1.5 × 105 L-type calcium channels per cell.
Additional challenges arise from the fact that the computational tasks have various levels of arithmetic intensity and control com- plexity, which require careful adaptation of the simulation code to the target device. By exploiting the strengths of the GPU, we obtain a performance that is far superior to that of the CPU, and also signi cantly higher than that of other state of the art manycore devices, thus paving the way for detailed whole-heart simulations in future generations of leadership class supercomputers.