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DTSTAMP:20220812T074334Z
LOCATION:Osaka Room
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UID:submissions.pasc-conference.org_PASC22_sess146_msa182@linklings.com
SUMMARY:A High-Performance Post-Processing Workflow for Numerical Weather 
 Prediction Using the Maestro Middleware
DESCRIPTION:Minisymposium\n\nA High-Performance Post-Processing Workflow f
 or Numerical Weather Prediction Using the Maestro Middleware\n\nSarmany\n\
 nECMWF runs time-critical operational weather forecasts four times a day. 
 For each run, the entire workflow must complete within one hour. The foreca
 st workflow is complex and contains many components. This overall complexi
 ty makes it difficult to restructure and experiment on the workflow, and s
 o we have created a simplified benchmarking workflow that captures the mai
 n runtime and I/O characteristics. This makes it easier for us to investig
 ate emerging technologies and workflow structures.<br /><br />The worst co
 ngestion in data movement occurs between the meteorological forecast model
  and post-processing due to many simultaneous read and write operations. I
 n the recently completed Maestro H2020 project, we reworked the workflow t
 o use the Maestro middleware for its data-handling operations. Using the m
 iddleware's data-event subscription allows the workflows dependency requir
 ements to be restructured -- post-processing data consumers can now overla
 p with data producers and perform their work as data becomes available. Th
 is allows the overall computation to occur earlier, and the workflow to co
 mplete earlier.\n\nDomain: Chemistry and Materials, Climate, Weather and E
 arth Sciences, Computer Science and Applied Mathematics, Life Sciences
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