Abstract
Background Large neural network simulations are becoming more complex to set up. They require modeling at multiple scales, include the effects of many interacting physical processes, encompass greater detail, and consume greater computational resources. The drive to solve problems that rely on increasingly complex codes will soon land us in the realm of petascale computing. How will we manage such simulations, configure them, and accurately aim them at the problems we're trying to solve? Simulation is an increasingly expensive process, with each run providing data to inform configuration and targeting of subsefrom Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 Toronto, Canada. 7–12 July 2007
Highlights
Large neural network simulations are becoming more complex to set up
Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 William R Holmes Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here http://www.biomedcentral.com/content/pdf/1471-2202-8-S2-info.pdf
The drive to solve problems that rely on increasingly complex codes will soon land us in the realm of petascale computing
Summary
Address: 1Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL USA and 2Department of Pediatrics, University of Chicago Hospitals, The University of Chicago, Chicago, IL USA. Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 William R Holmes Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here http://www.biomedcentral.com/content/pdf/1471-2202-8-S2-info.pdf
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