Description

Biological neural systems are well known for their robust and power-efficient operation in highly noisy environments. Biological circuits are made up of low-precision, unreliable and massively parallel neural elements with highly reconfigurable and plastic connections. Two of the most interesting properties of the neural systems are its self-organizing capabilities and its template architecture. Recent research in biologically-plausible neural networks has demonstrated interesting principles about learning and neural computation. Understanding and applying these principles to practical problems is only possible if large-scale neural simulators or circuits can be constructed. This workshop will outline key modelling abstractions for the brain and focus on recent neural network models. Aspects of neuronal processing and computational issues related to modelling these processes will be discussed. Hardware and software solutions readily usable by neuroscientists and computer scientists and efficient enough to construct very large networks comparable to brain networks will be presented.

Target Audience and Workshop Format

The workshop is designed to attract both newcomers to neuromorphic computing, as well as neuromorphic researchers who wish to interact with the DATE community to stimulate new ideas, topics and collaborations. Since this is a hot area but one that is probably new to a large segment of the DATE community, half of the workshop will be devoted to a comprehensive introduction to Neuromorphic and Brain-Based Computing, where the audience will be exposed to basic definitions, key concepts, abstractions, design flows, and design constraints; also some highly visible research projects will be presented as exemplars to provide an overview of existing and emerging solutions in this domain. The other half of the event will create a forum for interactive discussion and exchange of ideas and experiences between researchers through posters and demonstrations, with the goal of highlighting details on applicability, performance, and strengths of current solutions. Our aim is for attendees to learn about emerging Neuromorphic and Brain-Based computing techniques, highlight publicly available modelling and simulation tools, and view directions for longer term research.

Topics of interest

Authors are invited to submit original unpublished works on topics from a wide range of Neuromorphic and Brain-Based computing areas, including but not limited to:

• Formal models
• Hardware architectures
• Software tools
• Systems and applications
• Simulation Infrastructures

Submission

Submissions are invited in the form of 2-page extended abstract describing the novelties and advantages of the work.

Submissions must be done through Easychair at https://www.easychair.org/conferences/?conf=neucomp2013

All submissions will be evaluated with regard to their suitability for the workshop, originality and technical soundness. Selected submissions will be accepted for oral presentation and/or poster/interactive presentations. This workshop does not require blind submissions. Informal proceedings with accepted papers will be made available at the workshop as detailed below.

Important dates

Informal Workshop Digest

NeuComp 2013 will distribute an informal workshop digest to all workshop participants. NeuComp 2013 presenters are encouraged to submit papers for inclusion in this informal workshop digest.

Note that since the informal workshop digest is only distributed to workshop participants (and is not archived as part of DATE or ACM/IEEE digital libraries), authors are free to submit their work to other archival conferences and journals.

Workshop format

The workshop will combine oral and interactive sessions (posters and demonstrations) together with invited talks representing major neuromorphic research projects (e.g., BrainScaleS, NeuCod, SpiNNaker, SyNAPSE). The event will be designed to be highly interactive, with ample time for discussion and cross-disciplinary engagement.

Invited speakers

• Angelo Arleo - Université Pierre et Marie Curie, FR
• Claude Berrou - TelecomBretagne, FR
• Daniel Hammerstrom - DARPA and Portland State University, US
• Steve Furber and Alexander Rast - Manchester University, UK
• Sean Hill - INCF, US
• Jeff Krichmar - UC Irvine, US
• Karlheinz Meier and Simon Friedman - Heidelberg University, DE
• Vijay Narayanan - Pennsylvania State University, US
• Emre Neftci - UCSD, US
• Narayan Srinivasa - HRL, US