Neuromorphic Computing: Programming Spiking Neural Networks on SpiNNaker2

Hands-on workshop exploring energy-efficient AI hardware and the principles of neuromorphic computing through programming spiking neural networks on the SpiNNaker2 chip.

How can artificial intelligence become more energy-efficient? While conventional AI hardware requires significant amounts of energy, the human brain processes information using a fraction of that power. Neuromorphic computing takes inspiration from biological neural systems to explore alternative approaches to AI hardware and information 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 are introduced to the principles of brain-inspired computing. Unlike conventional artificial neural networks, spiking neural networks (SNNs) communicate through short electrical pulses called spikes, with neurons remaining inactive between signals.

Using SpiNNaker2 as a practical example, the workshop demonstrates how neuromorphic chips operate and how they can be programmed. The session offers an introduction to a computing approach that seeks to combine AI capabilities with more energy-efficient processing.

Date: November 18, 2026
Time: 2:00–5:00 PM
Location: Hasso Plattner Institute, Main Building (H), Room H-2.57/58, Prof.-Dr.-Helmert-Straße 2–3, 14482 Potsdam
Organizer: AI Service Center Berlin-Brandenburg at HPI
Admission: Free, registration via Eventbrite
Audience: AI developers, researchers, students, and professionals interested in AI hardware and brain-inspired computing
Focus: Neuromorphic computing, spiking neural networks, SpiNNaker2, AI hardware, and energy-efficient computing
Practical component: Introduction to programming spiking neural networks on SpiNNaker2
Duration: 3 hours