Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Concurrent number cruncher: an efficient sparse linear solver on the GPU
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
Run-time optimizations for replicated dataflows on heterogeneous environments
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Optimizing dataflow applications on heterogeneous environments
Cluster Computing
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The modeling of the electrical activity of the heart is of great medical and scientific interest, because it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. The cardiac electrophysiology may be simulated by solving a partial differential equation (PDE) coupled to a system of ordinary differential equations (ODEs) describing the electrical behavior of the cell membrane. The numerical solution is, however, computationally demanding because of the fine temporal and spatial sampling required. The demand for real time high definition 3D graphics made the new graphic processing units (GPUs) a highly parallel, multithreaded, many-core processor with tremendous computational horsepower. It makes the use of GPUs a promising alternative to simulate the electrical activity in the heart. The aim of this work is to study the performance of the use of GPUs to solve the equations underlying the electrical activity in a simple cardiac tissue.