|Authors||J. Langguth, X. Cai and J. Chai|
|Title||Heterogeneous Manycore Simulations in Cardiac Electrophysiology|
|Project(s)||Meeting Exascale Computing with Source-to-Source Compilers, Center for Biomedical Computing (SFF)|
|Publication Type||Talks, contributed|
|Year of Publication||2017|
|Location of Talk||Tenth International Workshop on Programmability and Architectures for Heterogeneous Multicores (MULTIPROG-2017), Stockholm, Sweden|
The demand for computing power in computational cardiology is continuously increasing due to the use of physiologically realistic cell models and the need to simulate the heart and use higher resolutions in time and space. And while parallel computing itself is widely used in the field by now, the arrival of heterogeneous multicore architectures presents an important opportunity for speeding up the cardiac simulation process. However, this speedup is not obtained effortlessly, and achieving it presents numerous computational challenges of its own.
We present a summary of our experiences from the implementation of multiple cardiac research codes on multicore, manycore, and GPU processors. Our main goal is to highlight the platform-specific challenges we face in our applications, ranging from efficient data movement to optimizations for large-scale irregular computations. Based on that, we discuss the suitability of the different plattforms for cardiac computations.