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Reprint of: Simulation Platform: A cloud-based online simulation environment
- Source :
- Neural Networks. 24:927-932
- Publication Year :
- 2011
- Publisher :
- Elsevier BV, 2011.
-
Abstract
- For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called ''Simulation Platform''. Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software.
- Subjects :
- Internet
Web-based simulation
Informatics
Databases, Factual
Computer science
business.industry
Cognitive Neuroscience
Models, Neurological
Cloud computing
computer.software_genre
Online Systems
User-Computer Interface
Upload
Software
Artificial Intelligence
Human–computer interaction
Virtual machine
Operating system
Computer Simulation
Compiler
Web service
business
computer
Algorithms
Subjects
Details
- ISSN :
- 08936080
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- Neural Networks
- Accession number :
- edsair.doi.dedup.....e041fb031b14b05fc337d3fa99bb1d71
- Full Text :
- https://doi.org/10.1016/j.neunet.2011.08.007