Energy Efficiency and Performance Management of Parallel Dataflow Applications

A4 Conference proceedings

Internal Authors/Editors

Publication Details

List of Authors: Simon Holmbacka, Erwan Nogues, Maxime Pelcat, Sébastien Lafond, Johan Lilius
Editors: Pinzari Ana, Morawiec Adam
Publication year: 2014
Publisher: ECDI Electronic Chips & Systems design initiative
Book title: The 2014 Conference on Design & Architectures for Signal & Image Processing
Start page: 1
End page: 8
ISSN: 2164-9766


Abstract—Parallelizing software is a popular way of achieving high energy efficiency since parallel applications can be mapped on many cores and the clock frequency can be lowered. Perfect parallelism is, however, not often reached and different program phases usually contain different levels of parallelism due to data dependencies. Applications have currently no means of expressing the level of parallelism, and the power management is mostly done based on only the workload. In this work, we provide means of expressing QoS and levels of parallelism in applications for more tight integration with the power management to obtain optimal energy efficiency in multi-core systems. We utilize the dataflow framework PREESM to create and analyze program structures and expose the parallelism in the program phases to the power
management. We use the derived parameters in a NLP (NonLinear Programming) solver to determine the minimum power for allocating resources to the applications.

Last updated on 2019-24-10 at 03:48