software energy consumption
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2020 ◽  
Vol 27 (3) ◽  
pp. 72-83
Author(s):  
Danilo Silva Alves ◽  
Oseias Ayres Ferreira ◽  
Lucio Mauro Duarte ◽  
Davi Silva ◽  
Paulo Henrique Maia

Although energy has become an important aspect in software development, little support exists for creating energy-efficient programs. One reason for that is the lack of abstractions and tools to enable the analysis of relevant properties involving energy consumption. This paper presents the results of some experiments involving the gathering, modelling, and analysis of energy-related information, in particular, the costs of executing certain parts of a software. We combine some existing free and open-source tools to carry out the experiments, extending one of them to handle energy information. Our experiments consider a comparison of energy consumption of Java implementations of the Bubble Sort, Insertion Sort and Selection Sort algorithms using different data structures. We show how to combine an energy measurement tool and a model analysis tool to carry such a comparison. Based on this support and on our experiments, we believe this is a first step to allow developers to start creating more energy-efficient software.


Author(s):  
Lucio Mauro Duarte ◽  
Danilo da Silva Alves ◽  
Bruno Ramos Toresan ◽  
Paulo Henrique Maia ◽  
Davi Silva

2019 ◽  
Vol 4 (2) ◽  
pp. 40-44
Author(s):  
V. A. Kulkarni ◽  
G. R. Udupi

Embedded systems are portable battery powered devices that have limited power resource. Hence, most of embedded systems need to meet energy constraint. Performance and energy consumption are the most important metrics for embedded system design. Estimation of performance, energy utilization and its validation are essential for embedded system design. Attempt has been made to precisely measure software energy consumption by three methods on ARM Cortex M4 processor. The results are validated with five benchmark programs. Tedious calculation of inter instruction cost has been minimized by taking it as certain percent of total energy. Percentage error between actual and estimated energy is found to be less than 5%. 


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