The Neuromorphic Computing Platform developed in the Human Brain Project (HBP) provides remote access to two complementary, large-scale neuromorphic computing systems (NCS) built in custom hardware at locations in Heidelberg (the BrainScaleS system) and Manchester (the SpiNNaker system).
The NCS are programmable, brain-inspired computing devices which enable high-speed, low-energy simulations of spiking neural networks with synaptic plasticity.
The BrainScaleS system is based on physical (analogue or mixed-signal) emulations of neuron, synapse and plasticity models with digital connectivity, running up to ten thousand times faster than real time.
The SpiNNaker system is based on numerical models running in real time on custom digital multicore chips using the ARM architecture.
The Neuromorphic Computing platform targets researchers in multiple fields, including computational neuroscience and machine learning. Platform users will be able to study network implementations of their choice including simplified versions of brain models developed on the HBP Brain Simulation Platform or generic circuit models based on theoretical work.
The platform also offers industry researchers and technology developers the possibility to experiment with and test applications based on state-of-the-art neuromorphic devices and systems.
Compared to traditional HPC resources, the Neuromorphic systems potentially offer higher speed (real-time or accelerated) and lower energy consumption. The accelerated systems are particularly suited for investigations of plasticity and learning, enabling simulation of hours or days of biological time in only a few seconds.
Users do not need to be members of the Human Brain Project.
This is the first public release of the Neuromorphic Computing platform. We expect there will still be a few rough edges, but the platform offers user support and training, and the software supporting the platform will be continuously improved.
The BrainScaleS system (NM-PM-1) contains 20 8-inch silicon wafers in 180 nm process technology. Each wafer incorporates 50 x 106 plastic synapses and 200,000 biologically realistic neurons. The system does not execute pre-programmed code but evolves according to the physical properties of the electronic devices, running at up to 10 thousand times faster than real time.
The SpiNNaker system (NM-MC-1) provides almost 30,000 custom digital chips, each with eighteen cores and a shared local 128 Mbyte RAM, giving a total of over 500,000 cores. A single chip can simulate 16,000 neurons with eight million plastic synapses running in real time with an energy budget of 1W.
Both systems have an interface designed for neuroscience researchers, based on Python scripts using the PyNN API for simulator-independent specification of neuronal network models. PyNN scripts also run on the popular software simulators NEST, NEURON and Brian.
Access to the system will be based on peer-reviewed proposals, as is commonly done for traditional HPC resources. Development accounts will also be available.
Models and simulation experiments are described in a Python script using the PyNN API. Experiments can be submitted in your browser through the HBP Collaboratory or via our web API (Python client available). Similarly, once the simulation is complete you can view the results in your browser, download data files via the web API, or transfer the data to the HBP High Performance Computing platform for further analysis.