Towards Green Big Data at CERN

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • CERN
  • University of Lausanne
  • VTT Technical Research Centre of Finland
  • Reaktor Group Oy

Abstract

High-energy physics studies collisions of particles traveling near the speed of light. For statistically significant results, physicists need to analyze a huge number of such events. One analysis job can take days and process tens of millions of collisions. Today the experiments of the large hadron collider (LHC) create 10 GB of data per second and a future upgrade will cause a ten-fold increase in data. The data analysis requires not only massive hardware but also a lot of electricity. In this article, we discuss energy efficiency in scientific computing and review a set of intermixed approaches we have developed in our Green Big Data project to improve energy efficiency of CERN computing. These approaches include making energy consumption visible to developers and users, architectural improvements, smarter management of computing jobs, and benefits of cloud technologies. The open and innovative environment at CERN is an excellent playground for different energy efficiency ideas which can later find use in mainstream computing.

Details

Original languageEnglish
Pages (from-to)103-113
Number of pages11
JournalFuture Generation Computer Systems
Volume81
Publication statusPublished - 1 Apr 2018
MoE publication typeA1 Journal article-refereed

    Research areas

  • CERN, Energy efficiency, Green computing, Scientific computing

ID: 16607667