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Coordination of Independent Loops in Self-Adaptive Systems

Panerati, Jacopo ; Maggio, Martina LU ; Carminati, Matteo ; Sironi, Filippo ; Triverio, Marco and Santambrogio, Marco Domenico (2014) In ACM Transactions on Reconfigurable Technology and Systems 7(2). p.12-16
Abstract
Nowadays, the same piece of code should run on different architectures, providing performance guarantees in a variety of environments and situations. To this end, designers often integrate existing systems with ad-hoc adaptive strategies able to tune specific parameters that impact performance or energy—for example, frequency scaling. However, these strategies interfere with one another and unpredictable performance degradation may occur due to the interaction between different entities. In this article, we propose a software approach to reconfiguration when different strategies, called loops, are encapsulated in the system and are available to be activated. Our solution to loop coordination is based on machine learning and it selects a... (More)
Nowadays, the same piece of code should run on different architectures, providing performance guarantees in a variety of environments and situations. To this end, designers often integrate existing systems with ad-hoc adaptive strategies able to tune specific parameters that impact performance or energy—for example, frequency scaling. However, these strategies interfere with one another and unpredictable performance degradation may occur due to the interaction between different entities. In this article, we propose a software approach to reconfiguration when different strategies, called loops, are encapsulated in the system and are available to be activated. Our solution to loop coordination is based on machine learning and it selects a policy for the activation of loops inside of a system without prior knowledge. We implemented our solution on top of GNU/Linux and evaluated it with a significant subset of the PARSEC benchmark suite. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
ACM Transactions on Reconfigurable Technology and Systems
volume
7
issue
2
pages
12 - 16
publisher
Association for Computing Machinery (ACM)
external identifiers
  • wos:000338627900007
  • scopus:84903824849
ISSN
1936-7406
DOI
10.1145/2611563
language
English
LU publication?
yes
id
1c9497a0-3e22-4773-a46a-8cfd8f5bc85a (old id 4584108)
alternative location
http://doi.acm.org/10.1145/2611563
date added to LUP
2016-04-01 10:07:44
date last changed
2022-03-04 08:23:22
@article{1c9497a0-3e22-4773-a46a-8cfd8f5bc85a,
  abstract     = {{Nowadays, the same piece of code should run on different architectures, providing performance guarantees in a variety of environments and situations. To this end, designers often integrate existing systems with ad-hoc adaptive strategies able to tune specific parameters that impact performance or energy—for example, frequency scaling. However, these strategies interfere with one another and unpredictable performance degradation may occur due to the interaction between different entities. In this article, we propose a software approach to reconfiguration when different strategies, called loops, are encapsulated in the system and are available to be activated. Our solution to loop coordination is based on machine learning and it selects a policy for the activation of loops inside of a system without prior knowledge. We implemented our solution on top of GNU/Linux and evaluated it with a significant subset of the PARSEC benchmark suite.}},
  author       = {{Panerati, Jacopo and Maggio, Martina and Carminati, Matteo and Sironi, Filippo and Triverio, Marco and Santambrogio, Marco Domenico}},
  issn         = {{1936-7406}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{12--16}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  series       = {{ACM Transactions on Reconfigurable Technology and Systems}},
  title        = {{Coordination of Independent Loops in Self-Adaptive Systems}},
  url          = {{http://dx.doi.org/10.1145/2611563}},
  doi          = {{10.1145/2611563}},
  volume       = {{7}},
  year         = {{2014}},
}