Domain knowledge specification for energy tuning
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10240441" target="_blank" >RIV/61989100:27240/18:10240441 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/61989100:27740/18:10240441
Výsledek na webu
<a href="https://onlinelibrary.wiley.com/doi/full/10.1002/cpe.4650" target="_blank" >https://onlinelibrary.wiley.com/doi/full/10.1002/cpe.4650</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/cpe.4650" target="_blank" >10.1002/cpe.4650</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Domain knowledge specification for energy tuning
Popis výsledku v původním jazyce
To overcome the challenges of energy consumption of HPC systems, the European Union Horizon 2020 READEX (Runtime Exploitation of Application Dynamism for Energy-efficient Exascale computing) project uses an online auto-tuning approach to improve energy efficiency of HPC applications. The READEX methodology pre-computes optimal system configurations at design-time, such as the CPU frequency, for instances of program regions and switches at runtime to the configuration given in the tuning model when the region is executed. READEX goes beyond previous approaches by exploiting dynamic changes of a region's characteristics by leveraging region and characteristic specific system configurations. While the tool suite supports an automatic approach, specifying domain knowledge such as the structure and characteristics of the application and application tuning parameters can significantly help to create a more refined tuning model. This paper presents the means available for an application expert to provide domain knowledge and presents tuning results for some benchmarks.
Název v anglickém jazyce
Domain knowledge specification for energy tuning
Popis výsledku anglicky
To overcome the challenges of energy consumption of HPC systems, the European Union Horizon 2020 READEX (Runtime Exploitation of Application Dynamism for Energy-efficient Exascale computing) project uses an online auto-tuning approach to improve energy efficiency of HPC applications. The READEX methodology pre-computes optimal system configurations at design-time, such as the CPU frequency, for instances of program regions and switches at runtime to the configuration given in the tuning model when the region is executed. READEX goes beyond previous approaches by exploiting dynamic changes of a region's characteristics by leveraging region and characteristic specific system configurations. While the tool suite supports an automatic approach, specifying domain knowledge such as the structure and characteristics of the application and application tuning parameters can significantly help to create a more refined tuning model. This paper presents the means available for an application expert to provide domain knowledge and presents tuning results for some benchmarks.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Ostatní
Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Concurrency Computation Practice and Experience
ISSN
1532-0626
e-ISSN
—
Svazek periodika
31
Číslo periodika v rámci svazku
6
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
15
Strana od-do
"e4650"
Kód UT WoS článku
000458902700001
EID výsledku v databázi Scopus
2-s2.0-85050645154