Big Data Meets Big Science.

The article focuses on the limitations of massively parallel computing in the analysis of data from next-generation scientific instruments. It states that powerful large-scale scientific instruments, such as the Large Synoptic Survey Telescope which is scheduled to go live in 2020, produce more data...

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Bibliographic Details
Published in:Communications of the ACM Vol. 57; no. 7; pp. 13 - 16
Main Author: Wright, Alex
Format: Article
Published: Association for Computing Machinery Jul2014
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Online Access:View this record in EBSCOhost
Description
Summary:The article focuses on the limitations of massively parallel computing in the analysis of data from next-generation scientific instruments. It states that powerful large-scale scientific instruments, such as the Large Synoptic Survey Telescope which is scheduled to go live in 2020, produce more data than the most powerful massively parallel supercomputers can handle. It mentions that scientists are examining new methods of reducing datasets to a manageable size, including cloud-based computing and emerging frameworks like quantum computing, and talks about algorithmic and economic constraints facing large scale data analysis. Massachusetts Institute of Technology professor Scott Aaronson suggests that Moore's Law has effectively broken down.