Cardiovascular diseases are the most frequent cause of death worldwide and half of these deaths are due to cardiac arrhythmia, disorders of the heart's electrical synchronization system. Computer models are essential to understand the behaviour of this complex system and its diseases. These models are already very sophisticated and widely used, but currently they are not powerful enough to take the heart's (2 billion!) individual cells into account. They must therefore assume that hundreds of cells are doing approximately the same thing. Due to this limitation, current models cannot represent the events in aging and structurally diseased hearts, in which reduced electrical coupling leads to large differences in behaviour between neigbouring cells, with possibly fatal consequences.
If we want to model the heart cell by cell, we face a mathematical problem that is 10,000 times larger, and also harder to solve. We will need larger supercomputers than those that exist today, and a lot of inventiveness to solve our problem efficiently on these future machines. The purpose of the MICROCARD project, which consists of 11 European partners, is to develop software that can solve this problem on future exascale supercomputers. We will develop algorithms that are tailored to the specific mathematical problem, to the size of the computations, and to the particular design of these future computers, which will probably owe most of their compute power to ultra-parallel computing elements such as Graphics Processing Units. We will not content ourselves with a "proof of concept", but will use the code that we develop to solve real-life problems in cardiology. Therefore the project includes computer experts, mathematicians, and biomedical engineers, and collaborates with cardiologists and physiologists.
Cardiovascular diseases are the most frequent cause of death worldwide and half of these deaths are due to cardiac arrhythmia, a disorder of the heart's electrical synchronization system. Numerical models of this complex system are highly sophisticated and widely used, but to match observations in aging and diseased hearts they need to move from a continuum approach to a representation of individual cells and their interconnections. This implies a different, harder numerical problem and a 10,000-fold increase in problem size. Exascale computers will be needed to run such models.
We propose to develop an exascale application platform for cardiac electrophysiology simulations that is usable for cell-by- cell simulations. The platform will be co-designed by HPC experts, numerical scientists, biomedical engineers, and biomedical scientists, from academia and industry. We will develop, in concert, numerical schemes suitable for exascale parallelism, problem-tailored linear-system solvers and preconditioners, and a compiler to translate high-level model descriptions into optimized, energy-efficient system code for heterogeneous computing systems. The code will be parallelized with a recently developed runtime system that is resilient to hardware failures and will use an energy-aware task placement strategy.
The platform will be applied in real-life use cases with high impact in the biomedical domain and will showcase HPC in this area where it is painfully underused. It will be made accessible for a wide range of users both as code and through a web interface. We will further employ our HPC and biomedical expertise to accelerate the development of parallel segmentation and (re)meshing software, necessary to create the extremely large and complex meshes needed from available large volumes of microscopy data. The platform will be adaptable to similar biological systems such as nerves, and components of the platform will be reusable in a wide range of applications.