Guest Blog by Andrew Cassidy and Rodrigo Alvarez-Icaza
Gearing up. We are preparing for the
2016 Telluride Neuromorphic Cognition Engineering Workshop,
in the Colorado mountain town.
Beginning Sunday Jun 26th, this annual workshop brings together nearly 100
researchers from all around the world to investigate brain-inspired solutions
to topics such as:
- Decoding Multi-Modal Effects on Auditory Cognition
- Spike-Based Cognition in Active Neuromorphic Systems
- Neuromorphic Path Planning for Robots in a Disaster Response Scenario
- Neuromorphic Tactile Sensing
- Computational Neuroscience
IBM’s Brain-Inspired Computing Group is sending two researchers with
an end-to-end hardware/software ecosystem for training neural networks to run,
in realtime, on the 4096 core
Eedn (Energy-efficient deep neuromorphic network)
training algorithm enables near state-of-the-art accuracy on a wide range of
visual, auditory, and other sensory datasets. When run on TrueNorth, these
networks can be run at
between 25 and 275mW, achieving >6000 FPS/W performance.
We are bringing (Figures 1-3):
- 16 NS1e boards (each with 1 TrueNorth neurosynaptic processor)
- 1 server (with 4 Titan X GPUs) for training deep neuromorphic networks
- and a bucket of cables.
Building on the successes from
last year’s workshop,
and leveraging the training material from
our goal is to enable train, build, and run for workshop participants.
Combined with real-time runtime infrastructure to connect input sensors
and output actuators to/from the NS1e board,
we have all of the tools in place to build
low-power end-to-end mobile and embedded systems,
to solve real-world cognitive problems.
Figure 1. Sixteen NS1e Boards
Figure 2. Training Server and Gear
Figure 3. Prep Station
Photo Credits: Rodrigo Alvarez-Icaza