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An overseer control methodology for data adaptable embedded systems

Published: 01 October 2012 Publication History

Abstract

The performance of software algorithms can be improved by performing those algorithms on specialized embedded hardware. However, complex algorithms that rely on input data at runtime for configuration have a combinatorial explosion of possible configurations, which has historically put hardware acceleration out of reach for applications wishing to serve large configuration spaces. Data adaptable embedded systems overcome this limitation by allowing for hardware reconfiguration during runtime, but the complexity of the specification of these systems is difficult to manage with traditional techniques. In this paper, a modeling approach is discussed in order to concurrently model two aspects of the final system: dependencies between algorithm tasks, and desired hardware configurations for each task. The contribution of the work is the model-based generation of hardware and software tasks, as well as a control scheme customized to each model that oversees the dynamic reconfiguration process.

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  • (2017)Task Transition Scheduling for Data-Adaptable SystemsACM Transactions on Embedded Computing Systems10.1145/304749816:4(1-28)Online publication date: 11-May-2017

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cover image ACM Conferences
MPM '12: Proceedings of the 6th International Workshop on Multi-Paradigm Modeling
October 2012
78 pages
ISBN:9781450318051
DOI:10.1145/2508443
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 October 2012

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Author Tags

  1. data adaptability
  2. domain specific modeling
  3. model-based design

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MODELS '12
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MPM '12 Paper Acceptance Rate 6 of 20 submissions, 30%;
Overall Acceptance Rate 6 of 20 submissions, 30%

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  • (2017)Task Transition Scheduling for Data-Adaptable SystemsACM Transactions on Embedded Computing Systems10.1145/304749816:4(1-28)Online publication date: 11-May-2017

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