6th March 2020: We are sorry to announce that NICE 2020, scheduled to be held on March 17-20 2020, will be postponed to a later date. Please see here for the new date in March 2021
NEUROTECH event: Future Application Directions for Neuromorphic Computing Technologies: agenda and registration (free, but mandatory). A half-day event with special focus on potential application of neuromorphic computing.
Travel info:
Getting to the venue:
the nearest tram stop to the meeting venue is "Heidelberg Bunsengymnasium" (marked in the map linked above) [online timetable]https://reiseauskunft.bahn.de//bin/query.exe/en?Z=Neuenheim+Bunsengymnasium,+Heidelberg), provided by German Railway. Here you can also buy tickets online
via Railway from the train station directly attached to the airport "Frankfurt Flughafen Fernbahnhof": online timetable by German Railway (tickets are also sold online via this website)
via airport shuttle service directly to the hotel. We have good experience with TLS Heidelberg. A single, shared ride costs about 40 Euro / person / ride
Hotels:
These hotels are relatively close to the meeting venue (Kirchhoff-Institute for Physics, see the map above). A lot more hotels are listed in online hotel booking sites (e.g. on booking.com)
The obvious promise of neuromorphic hardware is to enable efficient implementations of brain-derived algorithms. However, to be successful, it is essential that the community demonstrates that neuromorphic systems can be broadly impactful for beyond a few narrow tasks. While more advanced post-deep learning brain-derived algorithms would be ideal, it is helpful to look beyond cognitive algorithms as well for potential market impact.
In this talk, I will highlight one such opportunity: the application of neuromorphic hardware for large-scale scientific computing applications. Specifically, I will present a perspective on neuromorphic hardware that enables us to use large spiking architectures for solving stochastic differential equations and graph analytics. Our general approach treats neuromorphic architectures as a large computational graph onto which we can map sophisticated algorithmic tasks. We have demonstrated how this approach can be used to efficiently model Monte Carlo approximations to a class of partial differential equations that challenge the high-performance computing community, and we can further illustrate how this approach is well-suited for performing general dynamic programming tasks.
Finally, the talk will include some concrete examples of this approach on different spiking neuromorphic platforms, such as Loihi, TrueNorth, and SpiNNaker.
Brad Aimone
10:25‑10:35 (10+5 min)
Lightning talk: Benchmarking of Neuromorphic Hardware Systems
NICE 2020, Tutorials day: NOTE: NICE will be POSTPONED!
The tutorial day can be booked as one of the registration options. On the tutorial day hands-on interactive tutorials with several different neuromorphic compute systems will be offered:
Intel Loihi platform tutorial (Lecture style. To follow along from your own laptop your need to engage with Intel’s Intel’s Neuromorphic Research Community beforehand (email inrc_interest@intel.com for more information).