NDLI: Power Analysis of a General Convolution Algorithm Mapped on a Linear Processor Array

Content Provider	Springer Nature Link
Author	Manniesing, Rashindra Kleihorst, Richard van der Avoird, André Hendriks, Emile
Copyright Year	2004
Abstract	We explore the energy dissipation of the Linear Processor Array (LPA) as a function of the number of available resources (Processor Units P) within the array. This number P is an important parameter, as it reflects performance, relates parallel processing to energy dissipation, and influences the scaling of the various parts of the LPA architecture (memory, address generator, communication network).To make a comparison of the different design variants for a fixed datawidth possible, we propose a high-level energy dissipation model of the processor, which is based on a detailed analysis of a general convolution algorithm.It is shown that the energy dissipation of the LPA can roughly be described by the relationship E $_{total}$ ∼ N/P with N presenting the datawidth in pixels. This relationship is derived from two observations: first, the largest contribution to E $_{total}$ is formed by the energy dissipated by the memories, and second, in our model of the LPA, the datawidth of the memories corresponds with the number of pixels N to be processed, which results in an increase of the access rate when P decreases.Furthermore, we have shown that the energy dissipation caused by communication within the LPA, increases with increasing number of resources: the trade-off between communication versus computation in parallel computing. This turns out to be negligible in the total energy dissipation, and we therefore conclude, that the optimum solution is found, when a full number of resources is applied within the LPA.
Starting Page	5
Ending Page	19
Page Count	15
File Format	PDF
ISSN	09225773
Journal	Journal of Signal Processing Systems
Volume Number	37
Issue Number	1
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2004-05-01
Publisher Place	Boston
Access Restriction	Subscribed
Subject Keyword	Signal, Image and Speech Processing Circuits and Systems Electrical Engineering Image Processing and Computer Vision Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Information Systems Electrical and Electronic Engineering

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