NDLI: Power and performance characterization, analysis and tuning for energy-efficient edge detection on atom and ARM based platforms

Content Provider	IEEE Xplore Digital Library
Author	Otto, P. Malik, M. Akhlaghi, N. Sequeira, R. Homayoun, H. Sikdar, S.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., George Mason Univ., Fairfax, VA, USA (Otto, P.; Malik, M.; Akhlaghi, N.; Sequeira, R.; Homayoun, H.; Sikdar, S.)
Abstract	The de facto standard for embedded platforms with medium to low computing demands are ARM with Thumb ISA and Intel Atom with the X86 ISA with multiple cores. Operating these architectures in the milliwatts range while running realtime computer vision corner detection algorithms is a challenging problem. We present the analysis of power, performance and energy-efficiency measurements of Harris corner detection across a wide range of voltage and frequency settings, multicore/multithreading strategies, and compiler and application optimization parameters to find how the interplay of these parameters affect the power, performance and energy-efficiency. Our measurement of results on state-of-the-art embedded platforms demonstrate that a systematic cross-layer optimization at the application level (Sobel filter type, aperture size, number of image tiles), compiler level (branch prediction, function inlining) and system level (voltage and frequency setting, single core vs multicore implementation) significantly improves the energy-efficiency of corner detection, while meeting its real-time performance constraints. This cross-layer optimization improves the energy-efficiency of Harris corner on Atom and ARM by 89.5% and 87.2%, respectively.
Sponsorship	IEEE
Starting Page	479
Ending Page	482
File Size	222213
Page Count	4
File Format	PDF
e-ISBN	9781467371667
DOI	10.1109/ICCD.2015.7357153
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multicore processing Optimization Apertures Atomic measurements Frequency measurement Image edge detection Power measurement System optimization Harris corner Detection Embedded Platforms Energy Delay Product Algorithm Optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Power and Performance Characterization, Analysis and Tuning for Energy-efficient Edge Detection on Atom and ARM based Platforms

Harris Corner Detection on a NUMA Manycore

A comparative assessment of the performances of different edge detection operator using harris corner detection method.

Improvements Based on the Harris Algorithm

An improved Harris corner detection algorithm for low contrast image

The comparison and application of corner detection algorithms.

A fast detection algorithm of Harris apparent corners based on the local features

Auto-adaptive harris corner detection algorithm based on block processing

An effective method for corner detection

Power and performance characterization, analysis and tuning for energy-efficient edge detection on atom and ARM based platforms

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Power and Performance Characterization, Analysis and Tuning for Energy-efficient Edge Detection on Atom and ARM based Platforms

Harris Corner Detection on a NUMA Manycore

A comparative assessment of the performances of different edge detection operator using harris corner detection method.

Improvements Based on the Harris Algorithm

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The comparison and application of corner detection algorithms.

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Auto-adaptive harris corner detection algorithm based on block processing

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Power and performance characterization, analysis and tuning for energy-efficient edge detection on atom and ARM based platforms