Journal Article

FZJ-2021-06186

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Fast Ising solvers based on oscillator networks

Strachan, J. P. (Corresponding author)FZJ*RWTH*

2021
Springer Nature Limited London

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Please use a persistent id in citations: doi:10.1038/s41928-021-00620-x

Abstract: Some of the hardest problems we throw at computers are known as NP-hard or NP-complete. In the worst-case scenarios, solving them requires an amount of time or compute resources that scales exponentially with problem size. These types of problem are ubiquitous, and can show up, for example, when deciding a shipping route for package deliveries, when wiring up a state-of-the-art computer chip, when figuring out how to parse DNA sequence data, and when training an artificial neural network. Today, we get around such problems using approximations that can be highly problem specific — or, in fact, just declaring the problem intractable. Fortunately, real-world problems often end up being considerably easier than the worst-case scenarios. Nonetheless, many industries anxiously seek more powerful computers to let them solve larger problems faster and with better quality results.

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Contributing Institute(s):

1. Neuromorphic Compute Nodes (PGI-14)

Research Program(s):

1. 5234 - Emerging NC Architectures (POF4-523) (POF4-523)

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Essential Science Indicators ; IF >= 25 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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