Data-parallel algorithms for large-scale real-time simulation of the cellular potts model on graphics processing units

In the following paper we present techniques for data-parallel execution of the cellular potts model (CPM) on graphics processing units (GPUs). We have developed data-structures and algorithms that are optimized to use available hardware resources on the GPU. To the best of our knowledge, this is th...

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Veröffentlicht in:2009 IEEE International Conference on Systems, Man and Cybernetics S. 1411 - 1418
Hauptverfasser: Tapia, J.J., D'Souza, R.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2009
Schlagworte:
Analytical models
Biological system modeling
Biophysics
Cellular Arrays and Automata
Cellular Potts Model
Central Processing Unit
Computational modeling
Computer architecture
Computer graphics
Costs
GPGPU
Large-scale systems
Performance gain
Yarn
ISBN:9781424427932, 1424427932
ISSN:1062-922X
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:In the following paper we present techniques for data-parallel execution of the cellular potts model (CPM) on graphics processing units (GPUs). We have developed data-structures and algorithms that are optimized to use available hardware resources on the GPU. To the best of our knowledge, this is the first attempt at using data-parallel techniques for simulating the CPM. We benchmarked this implementation against other parallel CPM implementations using traditional CPU clusters. Experimental results demonstrate that this implementation solves many of the drawbacks of traditional CPU clusters, and results in a performance gain of up to 30x, without sacrificing the integrity of the original model.
ISBN:9781424427932
1424427932
ISSN:1062-922X
DOI:10.1109/ICSMC.2009.5346282