Study of Neocortex Simulations with GENESIS on High Performance Computing Resources
| Autor: | Joshua C. Crone, Dale R. Shires, Michela Taufer, David L. Boothe, Sean McDaniel, Alfred B. Yu, Song J. Park |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Theoretical computer science Neocortex Computer science Supercomputer Brain simulation 03 medical and health sciences 030104 developmental biology 0302 clinical medicine medicine.anatomical_structure Encoding (memory) medicine Differential (infinitesimal) 030217 neurology & neurosurgery |
| Zdroj: | ICPADS |
| Popis: | One significant challenge in neuroscience is understanding the cooperative behavior of large numbers of neurons. Models of neuronal networks allow scientists to explore the impact of differential neuronal connectivity using analysis techniques and information not available experimentally. However, modeling realistic neurobiological processes and encoding them in computer simulations is challenging, as increasing computing and data requirements are all of concern. In this work we study the performance of neocortex simulations using GEneral NEural SImulation System (GENESIS), a well-known multi-function brain simulation package, supported by high performance computing resources. The contribution of our work is threefold. First, we study the impact of platforms (i.e., single fat nodes versus high-end clusters) and their features on the performance and data generation for a small scale model of neocortex. Second, we assess the impact of the model complexity (i.e., number of cells and cell connectivity)on the performance and data generation for increasingly large versions of the neocortex model on high-end clusters. Third, we provide selected scientific results obtained by increasing the model complexity. We show that the more realistic and rigorous modeling of neocortex functions is computationally feasible but requires high performance computing resources to mitigate the growing computing and data requests of the associated simulations. |
| Databáze: | OpenAIRE |
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