NDLI: Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models

Content Provider	IEEE Xplore Digital Library
Author	Pope, Bernard J. Fitch, Blake G. Pitman, Michael C. Rice, John J. Reumann, Matthias
Copyright Year	2011
Description	Author affiliation: Victorian Life Science Computation Initiative, 187 Grattan Street, Carlton, VIC 3010, Australia (Pope, Bernard J) \|\| IBM Research Collaboratory for Life Sciences-Melbourne, 187 Grattan Street, Carlton, VIC 3010, Australia (Reumann, Matthias) \|\| IBM T. J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY, 10598 USA (Fitch, Blake G; Pitman, Michael C; Rice, John J)
Abstract	Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.
Starting Page	433
Ending Page	436
File Size	402600
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6090058
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational modeling Programming Load modeling Instruction sets Biological system modeling Synchronization Mathematical model
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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