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| Hauptseite > Publikationsdatenbank > Integrating brain structure and dynamics on supercomputers > print |
| Hauptseite > Publikationsdatenbank > Integrating brain structure and dynamics on supercomputers > print |
| 001 | 155133 | ||
| 005 | 20240313095017.0 | ||
| 020 | _ | _ | |a 978-3-319-12083-6 (print) |
| 020 | _ | _ | |a 978-3-319-12084-3 (electronic) |
| 024 | 7 | _ | |a 10.1007/978-3-319-12084-3_3 |2 doi |
| 024 | 7 | _ | |a 0302-9743 |2 ISSN |
| 024 | 7 | _ | |a 1611-3349 |2 ISSN |
| 024 | 7 | _ | |a WOS:000345024600003 |2 WOS |
| 037 | _ | _ | |a FZJ-2014-04318 |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a van Albada, Sacha |0 P:(DE-Juel1)138512 |b 0 |e Corresponding Author |u fzj |
| 111 | 2 | _ | |a 1st International Workshop on Brain-inspired Computing |g BrainComp 2013 |c Cetraro |d 2013-07-08 - 2013-07-11 |w Italy |
| 245 | _ | _ | |a Integrating brain structure and dynamics on supercomputers |
| 260 | _ | _ | |a Cham Heidelberg New York Dordrecht London |c 2014 |b Springer |
| 295 | 1 | 0 | |a Brain-inspired Computing |
| 300 | _ | _ | |a 22-32 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1563263897_1091 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 490 | 0 | _ | |a Lecture Notes in Computer Science |v 8603 |
| 500 | _ | _ | |a DOI: 10.1007/978-3-319-12084-3_3 |
| 520 | _ | _ | |a Large-scale simulations of neuronal networks provide a unique view onto brain dynamics, complementing experiments, small-scale simulations, and theory. They enable the investigation of integrative models to arrive at a multi-scale picture of brain dynamics relating macroscopic imaging measures to the microscopic dynamics. Recent years have seen rapid development of the necessary simulation technology. We give an overview of design features of the NEural Simulation Tool (NEST) that enable simulations of spiking point neurons to be scaled to hundreds of thousands of processors. The performance of supercomputing applications is traditionally assessed using scalability plots. We discuss reasons why such measures should be interpreted with care in the context of neural network simulations. The scalability of neural network simulations on available supercomputers is limited by memory constraints rather than computational speed. This calls for future generations of supercomputers that are more attuned to the requirements of memory-intensive neuroscientific applications. |
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| 536 | _ | _ | |a BRAINSCALES - Brain-inspired multiscale computation in neuromorphic hybrid systems (269921) |0 G:(EU-Grant)269921 |c 269921 |x 3 |f FP7-ICT-2009-6 |
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| 700 | 1 | _ | |a Diesmann, Markus |0 P:(DE-Juel1)144174 |b 3 |u fzj |
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