Programming Scalable Neuromorphic Algorithms With Fugu

Explore neural-inspired computing with Brad Aimone, a leading neuroscientist at Sandia Labs. Join us for insights into next-gen technology and neuroscience.

Edit Page

Fugu is a high-level framework specifically designed for developing spiking circuits in terms of computation graphs . Accordingly, with a base leaky-integrate-and fire (LIF) neuron model at its core, neural circuits are built as bricks. These foundational computations are then combined and composed as scaffolds to construct larger computations. This allows us to describe spiking circuits in terms of neural features common to most NMC architectures rather than platform specific designs.

Social share preview for Programming Scalable Neuromorphic Algorithms with Fugu

Upcoming Workshops

No workshops are currently scheduled. Check back soon for new events!

Are you an expert in a neuromorphic topic? We invite you to share your knowledge with our community. Hosting a workshop is a great way to engage with peers and share your work.

About the Speaker

Brad Aimone is a Distinguished Member of Technical Staff in the Center for Computing Research at Sandia National Laboratories, where he is a lead researcher in leveraging computational neuroscience to advance artificial intelligence and in using neuromorphic computing platforms for future scientific computing applications. Brad currently leads a multi-institution DOE Office of Science Microelectronics Co-Design project titled COINFLIPS (which stands for CO-designed Influenced Neural Foundations Inspired by Physical Stochasticity) which is focused on developing a novel probabilistic neuromorphic computing platform. He also currently leads several other research efforts on designing neural algorithms for scientific computing applications and neuromorphic machine learning implementations.

Brad has published over seventy peer-reviewed journal and conference articles in venues such as Advanced Materials, Neuron, Nature Neuroscience, Nature Electronics, Communications of the ACM, and PNAS and he is one of the co-founders of the Neuro-Inspired Computational Elements, or NICE, conference. Prior to joining the technical staff at Sandia in 2011, Dr. Aimone was a postdoctoral research associate at the Salk Institute for Biological Studies, with a Ph.D. in computational neuroscience from the University of California, San Diego and Bachelor’s and Master’s degrees in chemical engineering from Rice University.

Inspired? Share your work.

Share your expertise with the community by speaking at a workshop, student talk, or hacking hour. It’s a great way to get feedback and help others learn.

Learn How to Present

Related Workshops

The ELM Neuron: An Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks

The ELM Neuron: An Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks

Aaron tells us about the Expressive Leaky Memory (ELM) neuron model, a biologically inspired phenomenological model of a cortical neuron.

C-DNN and C-Transformer: mixing ANNs and SNNs for the best of both worlds

C-DNN and C-Transformer: mixing ANNs and SNNs for the best of both worlds

Join us for a talk by Sangyeob Kim, Postdoctoral researcher at KAIST, on designing efficient accelerators that mix SNNs and ANNs.

Spyx Hackathon: Speeding up Neuromorphic Computing

Spyx Hackathon: Speeding up Neuromorphic Computing

Explore the power of Spyx in a hands-on hackathon session and dive into the world of neuromorphic frameworks with Kade Heckel.