The Software Cache Optimization-Based Method for Decreasing Energy Consumption of Computational Clusters
Alla G. Kravets () and
Vitaly Egunov
Additional contact information
Alla G. Kravets: CAD&RD Department, Volgograd State Technical University, 400005 Volgograd, Russia
Vitaly Egunov: Computers and Systems Department, Volgograd State Technical University, 400005 Volgograd, Russia
Energies, 2022, vol. 15, issue 20, 1-15
Abstract:
Reducing the consumption of electricity by computing devices is currently an urgent task. Moreover, if earlier this problem belonged to the competence of hardware developers and the design of more cost-effective equipment, then more recently there has been an increased interest in this issue on the part of software developers. The issues of these studies are extensive. From energy efficiency issues of various programming languages to the development of energy-saving software for smartphones and other gadgets. However, to the best of our knowledge, no study has reported an analysis of the impact of cache optimizations on computing devices’ power consumption. Hence, this paper aims to provide an analysis of such impact on the software energy efficiency using the original software design procedure and computational experiments. The proposed Software Cache Optimization (SCO)-based Methodology was applied to one of the key linear algebra transformations. Experiments were carried out to determine software energy efficiency. RAPL (Running Average Power Limit) was used—an interface developed by Intel, which provides built-in counters of Central Processing Unit (CPU) energy consumption. Measurements have shown that optimized software versions reduce power consumption up to 4 times in relation to the basic transformation scheme. Experimental results confirm the effectiveness of the SCO-based Methodology used to reduce energy consumption and the applicability of this technique for software optimization.
Keywords: energy efficiency of software; RAPL; cache memory; software cache optimization; reflection transformation; householder transformation; cache miss; analytical efficiency evaluation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/20/7509/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/20/7509/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:20:p:7509-:d:940014
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().