Solving QUBO on the Loihi 2 Neuromorphic Processor
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929450785964032 |
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| author | Pierro, Alessandro Stratmann, Philipp Guerra, Gabriel Andres Fonseca Risbud, Sumedh Shea, Timothy Mangalore, Ashish Rao Wild, Andreas |
| author_facet | Pierro, Alessandro Stratmann, Philipp Guerra, Gabriel Andres Fonseca Risbud, Sumedh Shea, Timothy Mangalore, Ashish Rao Wild, Andreas |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2408_03076 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Solving QUBO on the Loihi 2 Neuromorphic Processor Pierro, Alessandro Stratmann, Philipp Guerra, Gabriel Andres Fonseca Risbud, Sumedh Shea, Timothy Mangalore, Ashish Rao Wild, Andreas Neural and Evolutionary Computing Artificial Intelligence Discrete Mathematics I.2.8, G.2.1, C.1.4 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. |
| title | Solving QUBO on the Loihi 2 Neuromorphic Processor |
| topic | Neural and Evolutionary Computing Artificial Intelligence Discrete Mathematics I.2.8, G.2.1, C.1.4 |
| url | https://arxiv.org/abs/2408.03076 |