|
This article is cited in 1 scientific paper (total in 1 paper)
Information and Computer Technologies in Biology and Medicine
Data center efficiency model: A new approach and the role of artificial intelligence
E. A. Isaeva, V. V. Kornilovb, A. A. Grigor'evc a Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Moscow, Russia
b National Research University Higher School of Economics, Moscow, Russia
c Financial University under the Government of the Russian Federation, Moscow, Russia
Abstract:
Bioinformatics technologies play a significant and growing role in life science research, and as these technologies develop, so does the complexity of data. The challenge of biological data growth has given rise to a number of bioinformatics data centers that offer services and solutions ranging from large-scale biosystems analyze that accounts for entire OMICs to nanoscale experiments where molecular modeling can provide insight o structure and dynamics of molecular complexes of biological components. Obviously, this kind of research requires a highly specialized level of computational and statistical expertise, as well as high-performance resources. The importance of information technology is growing, as is the use of computer information systems throughout the world. There are more and more specialized data centers and they consume more energy. The development of new strategies for energy efficiency of data centers is becoming relevant. These strategies aim to reduce the amount of energy consumed by data centers and their environmental impact without sacrificing performance. The article examines performance metrics, proposes a new method for data center energy efficiency, and discusses the role of artificial intelligence techniques in achieving these goals.
Key words:
data centers; green data centers; energy efficiency; artificial intelligence.
Received 28.02.2023, 19.06.2023, Published 23.06.2023
Citation:
E. A. Isaev, V. V. Kornilov, A. A. Grigor'ev, “Data center efficiency model: A new approach and the role of artificial intelligence”, Mat. Biolog. Bioinform., 18:1 (2023), 215–227
Linking options:
https://www.mathnet.ru/eng/mbb516 https://www.mathnet.ru/eng/mbb/v18/i1/p215
|
Statistics & downloads: |
Abstract page: | 278 | Full-text PDF : | 125 | References: | 20 |
|