Artificial intelligence: An energy efficiency tool for enhanced high performance computing

Anabi Hilary Kelechi, Mohammed H. Alsharif, Okpe Jonah Bameyi, Paul Joan Ezra, Iorshase Kator Joseph, Aaron Anthony Atayero, Zong Woo Geem, Junhee Hong

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations


Power-consuming entities such as high performance computing (HPC) sites and large data centers are growing with the advance in information technology. In business, HPC is used to enhance the product delivery time, reduce the production cost, and decrease the time it takes to develop a new product. Today's high level of computing power from supercomputers comes at the expense of consuming large amounts of electric power. It is necessary to consider reducing the energy required by the computing systems and the resources needed to operate these computing systems to minimize the energy utilized by HPC entities. The database could improve system energy efficiency by sampling all the components' power consumption at regular intervals and the information contained in a database. The information stored in the database will serve as input data for energy-efficiency optimization. More so, device workload information and different usage metrics are stored in the database. There has been strong momentum in the area of artificial intelligence (AI) as a tool for optimizing and processing automation by leveraging on already existing information. This paper discusses ideas for improving energy efficiency for HPC using AI.

Original languageEnglish
Article number1029
Issue number6
StatePublished - 1 Jun 2020


  • 5G
  • Artificial intelligence (AI)
  • Big data
  • Energy efficiency (EE)
  • High performance computing (HPC)
  • Internet of things (IoT)
  • Machine learning (ML)


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