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Spatio-Temporal Statistics and Data Science
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Spatio-Temporal Statistics and Data Science
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supercomputing

CEMSE Big Data Open Day shows off fascinating discoveries

1 min read · Thu, Dec 8 2016

News

big data machine learning knowledge discovery supercomputing

The fifth-anniversary event marked CEMSE's biggest successes and featured 20 KAUST discoveries, with more than 1,000 visitors from the community attending the event."Big data has many applications: to understand medicine better; to manage food supplies, and to connect objects. Data is at the center of everything," said Dean Mootaz Elnozahy of the University's Computer, Electrical, Mathematical Science and Engineering (CEMSE) Division at the CEMSE Big Data Open Day held on December 4, 2016.

Mixing precision for model acceleration

1 min read · Mon, Jul 26 2021

News

extreme computing supercomputing big data statistics

A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.

Spatio-Temporal Statistics and Data Science (STSDS)

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