Open AccessSelecting Best CPU frequency for energy saving in cluster using genetic algorithm
Author(s) -
Zainab A. Abdulazeez,
Ahmed Fanfakh,
Esraa H. Alwan
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/928/3/032073
Subject(s) - frequency scaling , computer science , energy consumption , genetic algorithm , energy (signal processing) , parallel computing , algorithm , degradation (telecommunications) , cluster (spacecraft) , function (biology) , real time computing , operating system , engineering , mathematics , electrical engineering , telecommunications , statistics , machine learning , evolutionary biology , biology
Dynamic voltage and frequency scaling (DVFS) is a technique mainly used for reducing the consumed energy of computer’s processor. Its only drawback detracting the performance of parallel application when executing them over parallel platform. However, genetic algorithm is introduced and applied in a heterogeneous cluster architecture for modeling the best trade-off between the energy saving and performance degradation of the parallel application in the same time. The suggested algorithm selects the best frequencies vector to achieve that targets by offering equal trade-off between them. The genetic algorithm simultaneously gives minimum energy consumption and minimal performance degradation via its objective function. All experiment will apply using SimGrid simulator. The experiments show that the algorithm reduces the energy consumption of the message passing application by (24% with 8000 problem size and 22% for 4000 problem size) and in almost cases improve the application performance up to 3%.