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TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
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DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
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BEGIN:VEVENT
DTSTAMP:20210402T160556Z
LOCATION:Track 5
DTSTART;TZID=America/New_York:20201112T145700
DTEND;TZID=America/New_York:20201112T152300
UID:submissions.supercomputing.org_SC20_sess211_ws_pdsw102@linklings.com
SUMMARY:Pangeo Benchmarking Analysis: Object Storage vs. POSIX File System
DESCRIPTION:Workshop\n\nPangeo Benchmarking Analysis: Object Storage vs. P
 OSIX File System\n\nXu, Paul, Banihirwe\n\nPangeo is a community of scient
 ists and software developers collaborating to enable Big Data Geoscience a
 nalysis interactively in the public cloud and on high-performance computin
 g (HPC) systems.  At the core of the Pangeo software stack is (1) Xarray, 
 which adds labels to metadata such as dimensions, coordinates and attribut
 es for raw array-oriented data, (2) Dask, which provides parallel computat
 ion and out-of-core memory capabilities, and (3) Jupyter Lab which offers 
 the web-based interactive environment to the Pangeo platform.\n\nGeoscient
 ists now have a strong candidate software stack to analyze large datasets,
  and they are very curious about performance differences between the Zarr 
 and NetCDF4 data formats on both traditional file storage systems and obje
 ct storage.  We have written a benchmarking suite for the Pangeo stack tha
 t can measure scalability and performance information of both input/output
  (I/O) throughput and computation.  We will describe how we performed thes
 e benchmarks, analyzed our results, and we will discuss the pros and cons 
 of the Pangeo software stack in terms of I/O scalability on both cloud and
  HPC storage systems.\n\nTag: Big Data, Data Analytics, Compression, and M
 anagement, Data Movement, File Systems and I/O, Storage\n\nRegistration Ca
 tegory: Workshop Reg Pass
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