A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems
Abstract
In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results.
Cite
@article{arxiv.1011.2861,
title = {A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems},
author = {Daniel Brüderle and Mihai A. Petrovici and Bernhard Vogginger and Matthias Ehrlich and Thomas Pfeil and Sebastian Millner and Andreas Grübl and Karsten Wendt and Eric Müller and Marc-Olivier Schwartz and Dan Husmann de Oliveira and Sebastian Jeltsch and Johannes Fieres and Moritz Schilling and Paul Müller and Oliver Breitwieser and Venelin Petkov and Lyle Muller and Andrew P. Davison and Pradeep Krishnamurthy and Jens Kremkow and Mikael Lundqvist and Eilif Muller and Johannes Partzsch and Stefan Scholze and Lukas Zühl and Christian Mayr and Alain Destexhe and Markus Diesmann and Tobias C. Potjans and Anders Lansner and René Schüffny and Johannes Schemmel and Karlheinz Meier},
journal= {arXiv preprint arXiv:1011.2861},
year = {2011}
}