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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20211207T055410Z
LOCATION:Online
DTSTART;TZID=America/Chicago:20211114T143000
DTEND;TZID=America/Chicago:20211114T150000
UID:submissions.supercomputing.org_SC21_sess424_ws_drbsd105@linklings.com
SUMMARY:Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy S
 cientific Data Compression
DESCRIPTION:Workshop\n\nUnbalanced Parallel I/O: An Often-Neglected Side E
 ffect of Lossy Scientific Data Compression\n\nWang, Wan, Chen, Gong, Whitn
 ey...\n\nLossy compression techniques have demonstrated promising results 
 in significantly reducing the scientific data size while guaranteeing the 
 compression error bounds. However, one important yet often neglected side 
 effect of lossy scientific data compression is its impact on the performan
 ce of parallel I/O. Our key observation is that the compressed data size i
 s often highly skewed across processes in lossy scientific compression. To
  understand this behavior, we apply three lossy compressors, which are spe
 cifically designed and optimized for scientific data, to three real-world 
 scientific applications. Our analysis demonstrates that the sizes of compr
 essed data are always skewed even if the original data is evenly decompose
 d among processes. We then systematically study how this side effect of lo
 ssy scientific data compression and observe that the skewness in the sizes
  of the compressed data often leads to I/O imbalance, which can significan
 tly reduce the efficiency of I/O bandwidth utilization if not properly han
 dled.\n\nTag: Online Only, Applications, Big Data, Data Analytics, Data Ma
 nagement\n\nRegistration Category: Workshop Reg Pass
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