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DTSTAMP:20190719T085745Z
LOCATION:HG D 1.1
DTSTART;TZID=Europe/Stockholm:20190614T150000
DTEND;TZID=Europe/Stockholm:20190614T153000
UID:submissions.pasc-conference.org_PASC19_sess160_msa317@linklings.com
SUMMARY:ECMWF's Extreme Data Challenges Towards a Exascale Weather Forecas
 ting System
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Clima
 te and Weather, Physics\n\nECMWF's Extreme Data Challenges Towards a Exasc
 ale Weather Forecasting System\n\nQuintino, Smart, Hawkes, Raoult\n\nECMWF
 's operational weather forecast generates massive I/O in short bursts, cur
 rently approaching 100 TiB per day, in two hour-long windows. From this ou
 tput, millions of user-defined daily products are generated and disseminat
 ed to member states and commercial clients all over the world. As ECMWF ai
 ms to achieve Exascale NWP by 2025, we expect to handle around 1 PiB of mo
 del data per day and generate 100's of millions daily products. This poses
  a strong challenge to a complex workflow that is already facing I/O bottl
 enecks. To help tackle this challenge, ECMWF is developing multiple soluti
 ons and changes to its workflows, and incrementally bringing them into ope
 rations. For example, it has developed a high-performance distributed obje
 ct-store that manages the model output, for the needs of our NWP and Clima
 te simulations, making data available via scientific meaningful requests, 
 which integrate seamlessly with the rest of the operational workflow. We w
 ill present how ECMWF is leveraging this and other technologies to address
  current performance issues in our operations, while at the same time prep
 aring for technology changes in the hardware and system landscape and the 
 convergence between HPC and Cloud provisioning.
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