AbstractThe
cardiac bidomain model is a popular approach to study electrical
behavior of tissues and simulate interactions between
the cells by solving partial differential equations. The
iterative and data parallel model is an ideal match for the parallel
architecture of Graphic Processing Units (GPUs). In this
study, we evaluate the effectiveness of architecture-specific
optimizations
and fine grained parallelization strategies, completely port
the model to GPU, and evaluate the performance of single-GPU
and multi-GPU implementations. Simulating one action
potential duration (350 msec real time) for a 256×256×256 tissue takes
453 hours on a high-end general purpose processor, while it
takes 664 seconds on a four-GPU based system including the communication
and data transfer overhead. This drastic improvement (a
factor of 2460×) will allow clinicians to extend the time-scale of
simulations from milliseconds to seconds and minutes; and
evaluate hypotheses in a shorter amount of time that was not feasible
previously.
Publications: Venkata Krishna Nimmagadda, Ali Akoglu, Salim Hariri, Talal Moukabary (2011) Cardiac simulation on multi-GPU platform, The Journal of Supercomputing, Springer Netherlands, P1-19, Issn: 0920-8542, Url: http://dx.doi.org/10.1007/s11227-010-0540-x, Doi: 10.1007/s11227-010-0540-x Available at springerlink |
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