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TZNAME:CDT
DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20230124T171523Z
LOCATION:C143-149
DTSTART;TZID=America/Chicago:20221113T111500
DTEND;TZID=America/Chicago:20221113T112500
UID:submissions.supercomputing.org_SC22_sess426_ws_isav113@linklings.com
SUMMARY:A PSNR-Based Image Selection Approach Targeting Smart In Situ Visu
 alization
DESCRIPTION:Workshop\n\nA PSNR-Based Image Selection Approach Targeting Sm
 art In Situ Visualization\n\nYamaoka, Iwata, Sakamoto, Nonaka\n\nAlthough 
 in situ visualization can reduce the amount of data written to the storage
 , in situ visualization can still generate large amount of data for subseq
 uent analysis. For instance,  from different viewpoints at every visualiza
 tion time step. Considering that some of these images can be similar, an a
 ppropriate image selection to reduce the total number of images would be b
 eneficial to minimize the analysis time for understanding the underlying s
 imulation phenomena without missing important features. As an approach for
  such smart in situ visualization, we have worked on adaptive time step se
 lection for skipping time steps with small amount of change between time s
 teps. In this lightning talk, focusing on the set of images which can be g
 enerated from different viewpoints at every time step, we will present a P
 SNR-based image selection approach for eliminating similar images to furth
 er reduce the total number of images, targeting smarter in situ visualizat
 ion.\n\nSession Format: Recorded\n\nTag: Accelerator-based Architectures, 
 Data Analytics, In Situ Processing, Scientific Computing, Visualization, W
 orkflows\n\nRegistration Category: Workshop Reg Pass
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