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BEGIN:VEVENT
DTSTAMP:20190719T085743Z
LOCATION:HG E 1.2
DTSTART;TZID=Europe/Stockholm:20190612T140000
DTEND;TZID=Europe/Stockholm:20190612T143000
UID:submissions.pasc-conference.org_PASC19_sess137_msa225@linklings.com
SUMMARY:Addressing the IO Bottleneck in Seismic Processing/Imaging on the 
 Cloud
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Physi
 cs, Solid Earth Dynamics, Engineering\n\nAddressing the IO Bottleneck in S
 eismic Processing/Imaging on the Cloud\n\nClapp\n\nTraditional HPC IO appr
 oaches perform poorly in cloud environments. Object store architectures te
 nd to have high latencies and low bandwidth on a per thread basis. Perform
 ance can be improved dramatically by break a dataset into blocks that are 
 read in parallel. By caching blocks in main memory a user's data access pa
 ttern does not need to be changed. Scientific data often can be represente
 d as regularly-sampled hypercubes. Often this data can be compressed using
  lossy and lossless compression techniques. By integrating these IO techni
 ques into a library, IO performance in cloud environments can be improved 
 by more than order of magnitude with minimal changes to existing programs.
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