Towards optimal supercomputer energy consumption forecasting method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F21%3A10248132" target="_blank" >RIV/61989100:27740/21:10248132 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3390/math9212695" target="_blank" >https://doi.org/10.3390/math9212695</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/math9212695" target="_blank" >10.3390/math9212695</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards optimal supercomputer energy consumption forecasting method

Popis výsledku v původním jazyce

Accurate prediction methods are generally very computationally intensive, so they take a long time. Quick prediction methods, on the other hand, are not very accurate. Is it possible to design a prediction method that is both accurate and fast? In this paper, a new prediction method is proposed, based on the so-called random time-delay patterns, named the RTDP method. Using these random time-delay patterns, this method looks for the most important parts of the time series&apos; previous evolution, and uses them to predict its future development. When comparing the supercomputer infrastructure power consumption prediction with other commonly used prediction methods, this newly proposed RTDP method proved to be the most accurate and the second fastest. (C) 2021 by the authors. Licensee MDPI, Basel Switzerland.

Název v anglickém jazyce

Towards optimal supercomputer energy consumption forecasting method

Popis výsledku anglicky

Accurate prediction methods are generally very computationally intensive, so they take a long time. Quick prediction methods, on the other hand, are not very accurate. Is it possible to design a prediction method that is both accurate and fast? In this paper, a new prediction method is proposed, based on the so-called random time-delay patterns, named the RTDP method. Using these random time-delay patterns, this method looks for the most important parts of the time series&apos; previous evolution, and uses them to predict its future development. When comparing the supercomputer infrastructure power consumption prediction with other commonly used prediction methods, this newly proposed RTDP method proved to be the most accurate and the second fastest. (C) 2021 by the authors. Licensee MDPI, Basel Switzerland.

Druh

J_imp - 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)

Projekt

<a href="/cs/project/LM2018140" target="_blank" >LM2018140: e-Infrastruktura CZ</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Mathematics

ISSN

2227-7390

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

21

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

9

Strana od-do

—

Kód UT WoS článku

000719579900001

EID výsledku v databázi Scopus

2-s2.0-85117810207