Neuromorphic Computing: Programming Spiking Neural Networks on SpiNNaker2

Hands-on workshop on brain-inspired computing, energy-efficient AI hardware, and programming spiking neural networks in Python on the SpiNNaker2 platform.

How can artificial intelligence become more energy-efficient? While conventional AI hardware requires substantial amounts of energy, the human brain processes information using only a fraction of that power. Neuromorphic computing draws inspiration from biological neural systems to explore alternative approaches to AI processing.

In the workshop “Neuromorphic Computing: Programming Spiking Neural Networks on SpiNNaker2,” organized by the AI Service Center Berlin-Brandenburg at the Hasso Plattner Institute, participants learn the principles of spiking neural networks (SNNs). These networks communicate through short pulses called spikes, allowing neurons to remain inactive between signals and potentially reducing energy consumption.

The practical session introduces participants to programming their own spiking neural networks in Python and running them on SpiNNaker2 chips located in HPI's data center. Participants will compare these networks with conventional deep learning approaches and discuss the potential of neuromorphic computing. By the end of the workshop, they will have gained practical experience and written code they can continue working with.

Date: December 9, 2026
Time: 10:00 AM–1:00 PM
Location: Hasso Plattner Institute, Prof.-Dr.-Helmert-Straße 2–3, 14482 Potsdam
Organizer: AI Service Center Berlin-Brandenburg at HPI
Admission: Free, binding registration via Eventbrite
Language: English
Audience: Developers, researchers, students, and professionals with machine learning knowledge or Python experience
Focus: Neuromorphic computing, spiking neural networks, SpiNNaker2, Python, energy-efficient AI hardware, and deep learning
Practical component: Programming spiking neural networks in Python and executing them on SpiNNaker2 hardware
Prerequisites: Machine learning knowledge or Python experience; no prior knowledge of neuroscience or neuromorphic hardware required
What to bring: A laptop
Note: Photo, audio, and video recordings will be made during the event