Can Linear Approximation Improve Performance Prediction ?

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Can Linear Approximation Improve Performance Prediction ?

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Can Linear Approximation Improve Performance Prediction ?

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Lecture Notes in Computer Science

ISSN

0302-9743

e-ISSN

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Svazek periodika

2011

Číslo periodika v rámci svazku

6977

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

15

Strana od-do

250-264

Kód UT WoS článku

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EID výsledku v databázi Scopus

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