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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
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Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

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  3/2009 - 18

Workload Characterization an Essential Step in Computer Systems Performance Analysis - Methodology and Tools

CHEVERESAN, R.T. See more information about CHEVERESAN, R.T. on SCOPUS See more information about CHEVERESAN, R.T. on IEEExplore See more information about CHEVERESAN, R.T. on Web of Science, HOLBAN., S. See more information about HOLBAN., S. on SCOPUS See more information about HOLBAN., S. on SCOPUS See more information about HOLBAN., S. on Web of Science
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (361 KB) | Citation | Downloads: 817 | Views: 3,368

Author keywords
performance analysis, workload characterization, instruction traces, instruction decomposition, data locality

References keywords
performance(9), modeling(5), memory(5), applications(5), systems(4), supercomputing(4), parallel(4), architecture(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-10-26
Volume 9, Issue 3, Year 2009, On page(s): 100 - 106
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.03018
Web of Science Accession Number: 000271872000018
SCOPUS ID: 77954752048

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Computer system performance is a very complex process in which the hardware and software manufacturers invest important human and financial resources. Workload characterization represents an essential component of performance analysis. This paper presents a trace based methodology for software applications evaluation. It introduces a new analysis concept designed to significantly ease this process and it presents a set of experimental data collected using the new analysis structure on a representative set of scientific and commercial applications. Several important conclusions are drawn regarding workload characteristics, classifications and runtime behavior. This type of data is used by the computer architects in their efforts to maximize the performance of the hardware platforms these applications are going to execute on.

References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 505 TCR
SCOPUS® Citations for all references: 714 TCR

Web of Science® Average Citations per reference: 23 ACR
SCOPUS® Average Citations per reference: 32 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-02-17 11:05 in 82 seconds.

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