Solving QUBO on the Loihi 2 Neuromorphic Processor
Abstract
An Intel Loihi 2-based hardware-aware parallel simulated annealing algorithm efficiently solves Quadratic Unconstrained Binary Optimization problems with low latency and high energy efficiency.
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.
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