What is Event-Driven Computing?
With the increasing demand for "smart" algorithms on mobile and wearable devices, the energy cost of computing is becoming the bottleneck for battery lifetime. One approach to defuse this bottleneck is to reduce the compute activity on such devices - one of the most popular approaches uses sensor information to determine whether it is worth to run expensive computations or whether there is not enough activity in the environment. This approach is called event-driven computing. Event-driven architectures can be implemented for many applications - From pure sensing platforms to multi-core systems for machine learning on the edge. At IIS, we cover most of these application. Besides working with novel, state-of-the-art sensors and sensing platforms to push the limits of lifetime of wearables and mobile devices, we also work with cutting-edge computing systems like Intel Loihi for Spiking Neural Networks to minimize the energy cost of machine intelligence.
- Evaluating An Ultra low Power Vision Node
- Event-Driven Vision on an embedded platform
- Spiking Neural Network for Autonomous Navigation
- Event-Driven Convolutional Neural Network Modular Accelerator
- Level Crossing ADC For a Many Channels Neural Recording Interface
Projects In Progress
- Toward hyperdimensional active perception: learning compressed sensorimotor control by demonstration
- Ternary Weights Engine For Efficient Many Channels Spike Sorting Applications
- Digital Audio Interface for Smart Intensive Computing Triggering
- Interfacing PULP with a Brain-Inspired Ultra-Low Power Spiking Cochlea