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Toward Efficient Execution of RVC-CAL Dataflow Programs on Multicore Platforms

Research output: Contribution to journalArticleScientificpeer-review

Details

Original languageEnglish
Pages (from-to)1507-1517
Number of pages11
JournalJournal of Signal Processing Systems
Volume90
Issue number11
Early online date9 Feb 2018
DOIs
Publication statusPublished - Nov 2018
Publication typeA1 Journal article-refereed

Abstract

The increasing number of cores in System on Chips (SoC) has introduced challenges in software parallelization. As an answer to this, the dataflow programming model offers a concurrent and reusability promoting approach for describing applications. In this work, a runtime for executing Dataflow Process Networks (DPN) on multicore platforms is proposed. The main difference between this work and existing methods is letting the operating system perform Central processing unit (CPU) load-balancing freely, instead of limiting thread migration between processing cores through CPU affinity. The proposed runtime is benchmarked on desktop and server multicore platforms using five different applications from video coding and telecommunication domains. The results show that the proposed method offers significant improvements over the state-of-art, in terms of performance and reliability.

Keywords

  • Dataflow Process Networks, Multicore, Orcc, RVC-CAL

Publication forum classification

Field of science, Statistics Finland