Intel goes to ICONS 2022
- Garrick Orchard (Deactivated)
- Timothy Shea
Intel had a strong showing at ICONS 2022 in Knoxville Tennessee. We presented 3 papers, won the best paper award, and featured prominently in many of the other presentations. We also participated in an NSF workshop panel discussion where Lava garnered a lot of interest and positive feedback from attendees.
About ICONS
The International Conference on Neuromorphic Systems (ICONS) brings together leading researchers in neuromorphic computing to share emerging research and build a collaborative ecosystem. The focus is on architectures, models, algorithms, and applications of neuromorphic systems.
Papers
The full list of conference papers is available in the ICONS Proceedings, and Intel’s papers are available at the links below. Look out for a separate blog post soon on Elvin’s award-winning paper!
“Fine-tuning Deep Reinforcement Learning Policies with r-STDP for Domain Adaptation.” Mahmoud Akl, Yulia Sandamirskaya, Deniz Ergene, Florian Walter and Alois Knoll. (pdf)
“Sparse Vector Binding on Spiking Neuromorphic Hardware Using Synaptic Delays.” Alpha Renner, Yulia Sandamirskaya, Friedrich T. Sommer and E. Paxon Frady. (pdf)
“Interactive continual learning for robots: a neuromorphic approach.” Elvin Hajizada, Patrick Berggold and Yulia Sandamirskaya. (BEST PAPER) (pdf)
NSF Workshop
The NSF International Workshop On Large Scale Neuromorphic Computing was held on the second day of ICONS, consisting of two panel discussions. I attended in person and served on the first panel “Opportunities & Challenges for Large-scale Neuromorphic Computing”.
The “large-scale” aspect of the panel discussion focused on the difference in scale between neuromorphic models and modern deep neural networks which can have well over 1 trillion parameters. Although some neuromorphic processors offer features to accelerate conventional AI models (deep networks), there is more to computing than AI, and there is more to AI than backprop trained deep networks. The Neuromorphic Computing field should focus on the novel compute and AI capabilities it can provide.
The discussion turned to how these capabilities can be identified and proven. There was a clear consensus among the panelists and audience on the need to be able to share and replicate algorithmic and benchmarking results across teams. When teams can replicate and scrutinize each other’s results, it brings additional credibility to the field and makes for fairer comparisons between approaches. It also allows teams to improve or extend each other’s work, or re-use each other’s work as modular components of a more complex large-scale application.
The need for Lava
At Intel we are already addressing these needs with the Lava software framework, which can support a variety of computing backends and provides a common framework within which algorithms and code can be shared and reused across teams. Lava is available free on github and offers permissive licensing. The idea of Lava was positively received by the audience and panelists, with some asking how they could get started.
The need for such a framework is so strongly recognized that the topic came up again almost immediately in the second panel discussion (some of the panelists had missed the first discussion) and I was called from the audience to recap the earlier discussion points and aims of Lava.
Summary
Overall, we had a strong showing at ICONS 2022, came away with a best paper award, and received positive feedback from the community on our plans for Lava.