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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Schemmel, J. Grubl, A. Hartmann, S. Kononov, A. Mayr, C. Meier, K. Millner, S. Partzsch, J. Schiefer, S. Scholze, S. Schuffny, R. Schwartz, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Highly-Parallel VLSI-Systems and Neuromorphic Circuits, Technische Universität Dresden, Germany (Hartmann, S.; Mayr, C.; Partzsch, J.; Schiefer, S.; Scholze, S.; Schuffny, R.) || Kirchhoff Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, 69120, Germany (Schemmel, J.; Grubl, A.; Kononov, A.; Meier, K.; Millner, S.; Schwartz, M.) |
| Abstract | This demonstration is based on the wafer-scale neuromophic system presented in [1], [2] and [3]. One wafer of this system contains 384 analog network chips (ANC) for a total of 40 M synapses and 200k neurons. 12 FPGA boards hosting 48 digital network chips (DNC) [4] connect the wafer to outside stimuli by 768 2 Gb/s serial links. Since it is not feasible to bring a wafer module to the conference, a scaled-down demonstrator system was prepared, containing one FPGA board, one DNC and eight ANC chips (Fig. 1). The FPGA connects to a host PC via Gbit Ethernet and an oscilloscope will be used to visualize the analog signals within the network chips. The total setup will contain nearly one million individually programmable synapses and 4k neurons. Each neuron can be separately configured by 24 analog parameters. The whole system can emulate biological neural networks up to $10^{5}$ times faster than biological real time. |
| Starting Page | 702 |
| Ending Page | 702 |
| File Size | 1079444 |
| Page Count | 1 |
| File Format | |
| ISBN | 9781467302180 |
| ISSN | 02714302 |
| e-ISBN | 9781467302197 |
| DOI | 10.1109/ISCAS.2012.6272131 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-20 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Neurons Neuromorphics Field programmable gate arrays Biological neural networks Hardware Biomembranes |
| Content Type | Text |
| Resource Type | Article |
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