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TZID:Europe/Paris
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BEGIN:VEVENT
UID:2637@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20181214T140000
DTEND;TZID=Europe/Paris:20181214T150000
DTSTAMP:20181129T130000Z
URL:https://www.i2m.univ-amu.fr/evenements/data-compression-for-high-perfo
 rmance-computational-fluid-dynamics/
SUMMARY: (...): Data compression for high-performance computational fluid d
 ynamics
DESCRIPTION:: High-performance computing can produce large volumes of outpu
 t data. A computational fluid dynamics simulation using several hundred or
  thousands of processor cores would allocate three-dimensional fields of m
 any Gigabytes per hydrodynamic variable. Even though data reduction may be
  performed during the course of computation in order to only store the qua
 ntities of interest including hydrodynamic forces\, etc.\, it is often nec
 essary to store full three-dimensional fields for purposes such as simulat
 ion restart\, time-resolved flow visualization or exploratory analyses. In
  this talk\, I will present a wavelet-based method for compression of flui
 d flow simulation data. It is inspired by image compression\, and it consi
 sts of discrete wavelet transform\, quantization adapted for floating-poin
 t data\, and entropy coding. I will discuss different aspects of these num
 erical methods\, open-source software implementation and show example nume
 rical tests\, ranging from idealized configurations to realistic global we
 ather simulation data.http://www.jamstec.go.jp/souran/html/Dmitry_Kolomens
 kiy004012-e.html
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:STANDARD
DTSTART:20181028T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
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