Towards Optimal Supercomputer Energy Consumption Forecasting Method

Jiří Tomčala
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Jiří Tomčala: IT4Innovations, VSB—Technical University of Ostrava, 17.listopadu 2172/15, 70833 Ostrava-Poruba, Czech Republic

Mathematics, 2021, vol. 9, issue 21, 1-9

Abstract: 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’ 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.

Keywords: forecasting; prediction method; time series; random time delays patterns; zeroth algorithm; machine learning; statistical; supercomputer power consumption; complex system (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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