Name
Abstract | ||
|---|---|---|
This paper presents configuration methods for an existing neuromorphic hardware and shows first experimental results. The utilized mixed-signal VLSI device implements a highly accelerated network of integrate-and-fire neurons. We present a software framework, which provides the possibility to interface the hardware and explore it from the point of view of neuroscience. It allows to directly compare both spike times and membrane potentials which are emulated by the hardware or are computed by the software simulator NEST, respectively, from within a single software scope. Membrane potential and spike timing dependent plasticity measurements are shown which illustrate the capabilities of the software framework and document the functionality of the chip. |
Year | Venue | Keywords |
|---|---|---|
2007 | IWANN | accelerated network,software framework,vlsi device,spike time,membrane potential,neuromorphic silicon,existing neuromorphic hardware,spike timing,configuration method,single software scope,software simulator nest,chip |
Field | DocType | Volume |
Computer science,Neuromorphic engineering,Real-time computing,Graphical user interface,Software,Artificial intelligence,Very-large-scale integration,Computer architecture,Chip,Spike-timing-dependent plasticity,Synaptic weight,Machine learning,Software framework | Conference | 4507 |
ISSN | Citations | PageRank |
0302-9743 | 6 | 0.62 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Brüderle | 1 | 349 | 17.67 |
| Andreas Grübl | 2 | 207 | 11.51 |
| Karlheinz Meier | 3 | 478 | 40.10 |
| Eilif Mueller | 4 | 247 | 16.65 |
| Johannes Schemmel | 5 | 533 | 49.34 |