Can Linear Approximation Improve Performance Prediction ?
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F11%3A10099123" target="_blank" >RIV/00216208:11320/11:10099123 - isvavai.cz</a>
Result on the web
<a href="http://www.springerlink.com/content/50868p3861927512/" target="_blank" >http://www.springerlink.com/content/50868p3861927512/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-24749-1_19" target="_blank" >10.1007/978-3-642-24749-1_19</a>
Alternative languages
Result language
angličtina
Original language name
Can Linear Approximation Improve Performance Prediction ?
Original language description
Software performance evaluation relies on the ability of simple models to predict the performance of complex systems. Often, however, the models are not capturing potentially relevant effects in system behavior, such as sharing of memory caches or sharing of cores by hardware threads. The goal of this paper is to investigate whether and to what degree a simple linear adjustment of service demands in software performance models captures these effects and thus improves accuracy. Outlined experiments explore the limits of the approach on two hardware platforms that include shared caches and hardware threads, with results indicating that the approach can improve throughput prediction accuracy significantly, but can also lead to loss of accuracy when the performance models are otherwise defective.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Computer Science
ISSN
0302-9743
e-ISSN
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Volume of the periodical
2011
Issue of the periodical within the volume
6977
Country of publishing house
DE - GERMANY
Number of pages
15
Pages from-to
250-264
UT code for WoS article
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EID of the result in the Scopus database
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