SP9 - Neuromorphic Computing
SP9 designs, implements and operate a Neuromorphic Computing Platform. This Platform allows non-expert neuroscientists and engineers to perform experiments with configurable Neuromorphic Computing Systems (NCS), implementing simplified versions of brain models developed on the Brain Simulation Platform, and on generic circuit models. The NCS comprises hardware devices that incorporate state-of-the-art electronic component and circuit technologies as well as new knowledge arising from other areas of HBP research, such as experimental neuroscience, theory, and brain modelling.
The platform provide NCS based on physical (analogue or mixed-signal) emulations of brain models (NM-PM), running in accelerated mode, numerical models running in real time on digital multicore architectures, (NM-MC), and the software tools necessary to design, configure and measure the performance of these systems. The platform will be tightly integrated with the High Performance Analytics and Computing Platform, which will provide essential services for mapping and routing circuits to neuromorphic substrates, benchmarking and simulation-based verification of hardware specifications.
SP9's primary objective for the Ramp-Up Phase was to construct a first fully operational version of the HBP Neuromorphic Computing Platform. The platform consists of two complementary, large-scale NCS built in custom hardware at locations in Heidelberg, Germany (the NM-PM system) and Manchester, United Kingdom (the NM-MC system). The Platform provides remote access to both NCS, as well as software tools for their configuration, operation, and the analysis of generated data, and user support documentation, training workshops and a consulting service. Platform users will be able to study network implementations of their choice, including simplified versions of brain models developed on the Brain Simulation Platform, or generic circuit models based on theoretical work.
In SGA1, SP9 aims to:
- Develop the feature set for NM-PM-2;
- Increase the scale, performance and online accessibility of NM-MC-1, with a real-time closed-loop virtual robotics environment from SP10;
- Provide an architecture model for NM-MC-2, and test silicon where appropriate.
What People are Saying
Neuromorphic Computing is a huge opportunity for European science and industry. It could create a completely new industry based on those computing architectures [human brain inspired architectures] that are so energy efficient, fault tolerant and that do not use predefined software.
We've established collaborations with a number of groups around Europe and in fact the wider world. And the HBP has created a unique opportunity to extend these collaborations within Europe and to apply the SpiNNaker digital Neuromorphic computing technology to a wide range of interesting problems in the areas of computational neuroscience.
Within the open call part of the HBP, we're inviting new partners to join us to find suitable applications to explore the capabilities of the many core Neuromorphic technology that we've developed.
We're looking forward to receiving very original ideas from different fields that will make use of these novel computing systems - very much in the spirit of the way people used the first programmable computer built by John von Neumann in the Princeton Institute of Advanced study in the 40s of the last century.
The overall goal of the Neuromorphic Computing Subproject is to build and operate and use radically different computing architectures – Neuromorphic architecture – which is modeled after the architecture we find in the human brain and which we're going to explore in the human brain project.
Neuromorphic computers are systems radically different from traditional information processing devices in the sense that they really copy the structure, the function of biological brains.
The brain has amazing computing capabilities, it runs at very low power, it doesn't need any software, it's fault tolerant. It's pretty obvious that bringing these features into synthetic systems must have a rather severe effect on the way we build computers in the future.