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Invasive Computing for Mapping Parallel Programs to Many-Core ArchitecturesSelf-embedding

Invasive Computing for Mapping Parallel Programs to Many-Core Architectures: Self-embedding [In this chapter, a self-embedding algorithm is presented which solves the mapping problem consisting of task binding to tiles, respectively processors, and message routing to NoC links as formalized in the previous chapter in an autonomous way. In the realm of invasive computing, self-embedding tackles the problem in a resource-aware, decentralized, and adaptive manner. Contrary to related work, the application itself initiates and performs its own mapping autonomously. The main idea of the algorithm is that each task, or i-let in invasive computing, embeds its succeeding task and the respective communication towards it.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Invasive Computing for Mapping Parallel Programs to Many-Core ArchitecturesSelf-embedding

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Publisher
Springer Singapore
Copyright
© Springer Nature Singapore Pte Ltd. 2018
ISBN
978-981-10-7355-7
Pages
57 –83
DOI
10.1007/978-981-10-7356-4_4
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter, a self-embedding algorithm is presented which solves the mapping problem consisting of task binding to tiles, respectively processors, and message routing to NoC links as formalized in the previous chapter in an autonomous way. In the realm of invasive computing, self-embedding tackles the problem in a resource-aware, decentralized, and adaptive manner. Contrary to related work, the application itself initiates and performs its own mapping autonomously. The main idea of the algorithm is that each task, or i-let in invasive computing, embeds its succeeding task and the respective communication towards it.]

Published: Dec 30, 2017

Keywords: Invasive Computing; Seed Points; Application Graph; Monitor Overhead; Average Network Load

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