A Look at BrainScaleS-1 — Heidelberg University - Neuromorphic Chip

The BrainScaleS-1 is an accelerated spiking neuromorphic system integrating 200k adaptive exponential integrate-and-fire neurons, 43M plastic synapses, and event routing on a silicon wafer substrate. It enables fast emulation of complex neural dynamics and exploration of STDP-type synaptic plasticity.

Developed By:

Heidelberg University

Official Product Page

The BrainScaleS-1 accelerated neuromorphic system is an wafer-scale integrated circuit architecture for emulating biologically-inspired spiking neural networks.
It was developed by researchers at the Heidelberg University and collaborators.
Key features of the BrainScaleS-1 system include:

System Architecture

20 wafers comprising 384 ASICs interconnected by a configurable circuit-switched event routing network on a silicon wafer
Every ASIC integrate a custom analog core with 512 neuron circuits, 112k plastic synapses, floating-gate-based analog parameter storage, STDP-type long-term and STP-type short-term plasticity and an event routing network

Neural and Synapse Circuits

Implements the Adaptive Exponential Integrate-and-Fire (AdEx) neuron model with individually configurable model parameters
On-chip synapse correlation and plasticity measurement enable programmable spike-timing dependent plasticity

Software and Experiment Control

BrainScaleS OS provides a full software stack including:
- High-level PyNN-based experiment interfaces
- C++ core libraries for configuration, calibration and control
- Mapping and routing tools to translate neural models onto hardware
Allows both novice and expert usage with varying levels of abstraction
Supports batch-mode and hybrid-mode experiments (chip-in-the-loop)

Applications and Experiments

Accelerated (10,000-fold compared to biological real time) emulation of complex spiking neuron dynamics
Exploration of synaptic plasticity models and critical network dynamics at biological timescales

The accelerated operation and flexible architecture facilitate applications in computational neuroscience research.

Date	Title	Authors	Venue/Source
September 2023	From clean room to machine room: commissioning of the first-generation BrainScaleS wafer-scale neuromorphic system	Hartmut Schmidt, José Montes, Andreas Grübl, Maurice Güttler, Dan Husmann, Joscha Ilmberger, Jakob Kaiser, Christian Mauch, Eric Müller, Lars Sterzenbach, Johannes Schemmel and Sebastian Schmitt	Neuromorphic Computing and Engineering
May 2022	The operating system of the neuromorphic BrainScaleS-1 system	Eric Müller, Sebastian Schmitt, Christian Mauch, Sebastian Billaudelle, Andreas Grübl, Maurice Güttler, Dan Husmann, Joscha Ilmberger, Sebastian Jeltsch, Jakob Kaiser, Johann Klähn, Mitja Kleider, Christoph Koke, José Montes, Paul Müller, Johannes Partzsch, Felix Passenberg, Hartmut Schmidt, Bernhard Vogginger, Jonas Weidner, Christian Mayr, Johannes Schemmel	Neurocomputing
March 2016	Neuromorphic Computer Coming Online	No author listed	Press Release by Heidelberg University
June 2010	A wafer-scale neuromorphic hardware system for large-scale neural modeling	Johannes Schemmel, Daniel Brüderle, Andreas Grübl, Matthias Hock, Karlheinz Meier, Sebastian Millner	2010 IEEE International Symposium on Circuits and Systems (ISCAS)
June 2008	Wafer-scale integration of analog neural networks	Johannes Schemmel, Johannes Fieres, Karlheinz Meier	2008 IEEE International Joint Conference on Neural Networks (IJCNN)

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