In this article, we describe an algorithm for solving Quadratic Unconstrained Binary Optimization problems on the Intel Loihi 2 neuromorphic processor. The solver is based on a hardware-aware fine-grained parallel simulated annealing algorithm developed for Intel's neuromorphic research chip Loihi 2. Preliminary results show that our approach can generate feasible solutions in as little as 1 ms and up to 37x more energy efficient compared to two baseline solvers running on a CPU. These advantages could be especially relevant for size-, weight-, and power-constrained edge computing applications.
@article{arxiv.2408.03076,
title = {Solving QUBO on the Loihi 2 Neuromorphic Processor},
author = {Alessandro Pierro and Philipp Stratmann and Gabriel Andres Fonseca Guerra and Sumedh Risbud and Timothy Shea and Ashish Rao Mangalore and Andreas Wild},
journal= {arXiv preprint arXiv:2408.03076},
year = {2024}
}
Comments
12 pages, 3 figures. Shared first authorship: Alessandro Pierro, Philipp Stratmann, and Gabriel Andres Fonseca Guerra