Rowlings, Matthew orcid.org/0000-0003-3800-2055, Tyrrell, Andy orcid.org/0000-0002-8533-2404 and Trefzer, Martin Albrecht orcid.org/0000-0002-6196-6832 (2020) Embedded Social Insect-Inspired Intelligence Networks for System-level Runtime Management. In: Design, Automation and Test in Europe Conference:DATE2020. , Grenoble, France
Abstract
Large-scale distributed computing architectures such as, e.g. systems on chip or many-core devices, offer advantages over monolithic or centralised single-core systems in terms of speed, power/thermal performance and fault tolerance. However, these are not implicit properties of such systems and runtime management at software or hardware level is required to unlock these features. Biological systems naturally present such properties and are also adaptive and scalable. To consider how these can be similarly achieved in hardware may be beneficial. We present Social Insect behaviours as a suitable model for enabling autonomous runtime management (RTM) in many-core architectures. The emergent properties sought to establish are self-organisation of task mapping and systemlevel fault tolerance. For example, large social insect colonies accomplish a wide range of tasks to build and maintain the colony. Many thousands of individuals, each possessing relatively little intelligence, contribute without any centralised control. Hence, it would seem that social insects have evolved a scalable approach to task allocation, load balancing and robustness that can be applied to large many-core computing systems. Based on this, a self-optimising and adaptive, yet fundamentally scalable, design approach for many-core systems based on the emergent behaviours of social-insect colonies are developed. Experiments capture decision-making processes of each colony member to exhibit such high-level behaviours and embed these decision engines within the routers of the many-core system.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | bio-inspired hardware, fault tolerance, social insects, adaptive system, many-core, runtime management |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Funding Information: | Funder Grant number EPSRC EP/K040820/1 |
Depositing User: | Pure (York) |
Date Deposited: | 12 Dec 2019 08:40 |
Last Modified: | 27 Nov 2024 00:14 |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154549 |
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