Live Demonstration: Packet-Based AER with 3 GEvent/s Cumulative Throughput
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Traditionally, the communication in neuromorphic VLSI systems has been done via parallel asynchronous transmission of Address-Event-Representations (AER) of neuron pulses. Recently, there has been a move towards greater event transmission speed via a serialization of the AER protocols. We give a live demonstration of a packet based synchronous serial AER infrastructure presented in a recent paper, which handles the complete off-wafer communication and configuration for a newly developed waferscale neuromorphic system, operating at a factor of 10 4 faster than biological real-time. Pulse packets are routed from the host PC via Gbit Ethernet to an FPGA board, which forwards them to 4 purpose designed Digital Network ASICs (DNCs) on the same board. The DNCs buffer and sort the pulses, implementing 32 2GBit/s Low Voltage Differential Signaling (LVDS) interfaces to the neuromorphic circuits on the wafer. Pulse communication to other wafers is done via an FPGA- FPGA communication using 10 Gbit/s Aurora links.
Details
Originalsprache | Englisch |
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Titel | 2011 IEEE International Symposium of Circuits and Systems (ISCAS) |
Herausgeber (Verlag) | IEEE Xplore |
Seiten | 1988-1988 |
Seitenumfang | 1 |
ISBN (elektronisch) | 978-1-4244-9474-3, 978-1-4244-9472-9 |
ISBN (Print) | 978-1-4244-9473-6 |
Publikationsstatus | Veröffentlicht - 18 Mai 2011 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | IEEE International Symposium on Circuits and Systems (ISCAS) |
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ISSN | 0271-4302 |
Konferenz
Titel | 2011 IEEE International Symposium of Circuits and Systems (ISCAS) |
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Dauer | 15 - 18 Mai 2011 |
Ort | Rio de Janeiro, Brazil |
Externe IDs
Scopus | 79960883166 |
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Ieee | 10.1109/ISCAS.2011.5937981 |
ORCID | /0000-0002-6286-5064/work/166324417 |
Schlagworte
Schlagwörter
- Biology, Delay, Semiconductor device modeling, Field programmable gate arrays, Neuromorphics, Throughput