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Computer Science > Emerging Technologies

Title: Asynchronous Neuromorphic Optimization with Lava

Authors: Shay Snyder (1), Sumedh R. Risbud (2), Maryam Parsa (1) ((1) George Mason University, (2) Intel Labs)
Abstract: Performing optimization with event-based asynchronous neuromorphic systems presents significant challenges. Intel's neuromorphic computing framework, Lava, offers an abstract application programming interface designed for constructing event-based computational graphs. In this study, we introduce a novel framework tailored for asynchronous Bayesian optimization that is also compatible with Loihi 2. We showcase the capability of our asynchronous optimization framework by connecting it with a graph-based satellite scheduling problem running on physical Loihi 2 hardware.
Comments: 2 figures
Subjects: Emerging Technologies (cs.ET)
Cite as: arXiv:2404.17052 [cs.ET]
  (or arXiv:2404.17052v1 [cs.ET] for this version)

Submission history

From: Shay Snyder [view email]
[v1] Thu, 25 Apr 2024 21:23:11 GMT (1534kb,D)

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