Exascale computing

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Exascale computing refers to computing systems capable of at least one exaFLOPS. Such capacity represents a thousandfold increase over the first petascale computer that came into operation in 2008.[1] (One exaflops is a thousand petaflops or a quintillion, 1018, floating point operations per second.) At a supercomputing conference in 2009, Computerworld projected exascale implementation by 2018.[2]

Exascale computing would be considered as a significant achievement in computer engineering, for it is believed to be the order of processing power of the human brain at neural level (functional might be lower). It is for instance the target power of the Human Brain Project.

Development[edit]

In January 2012 Intel purchased the InfiniBand product line from QLogic for US $125 million in order to fulfill its promise of developing exascale technology by 2018.[3]

The initiative has been endorsed by two US agencies: the Office of Science and the National Nuclear Security Administration,[4] both of which are part of the US Department of Energy. The technology would be useful in various computation-intensive research areas, including basic research, engineering, earth science, biology, materials science, energy issues, and national security.[5]

The United States has put aside $126 million for exascale computing beginning in 2012.[6]

Three projects aiming at developing technologies and software for exascale computing have been started in 2011 within the European Union. The CRESTA project (Collaborative Research into Exascale Systemware, Tools and Applications),[7] the DEEP project (Dynamical ExaScale Entry Platform),[8] and the project Mont-Blanc.[9]

In Japan, the RIKEN Advanced Institute for Computational Science is planning an exascale system for 2020, it will consume less than 30 megawatts.[10]

In June 2014, the stagnation of the Top500 supercomputer list had observers question the possibility of exascale systems by 2020.[11]

See also[edit]

References[edit]

Footnotes[edit]

  • [1]. MPI at Exascale: Challenges for Data Structures and Algorithms. Abstract of Recent Advances in Parallel Virtual Machine and Message Passing Interface, Lecture Notes in Computer Science, Volume 5759. ISBN 978-3-642-03769-6. Springer Berlin Heidelberg, 2009, p. 3.
  • [2] The Road to Exascale: Can Nanophotonics Help? Digital Manufacturing Report. November 22, 2011.

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