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DTSTAMP:20181221T160906Z
LOCATION:C145
DTSTART;TZID=America/Chicago:20181114T150000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess468_spost122@linklings.com
SUMMARY:Accelerating Microscope Data Analysis Using Parallel Computing
DESCRIPTION:ACM Student Research Competition, Poster\nStudent Program, Tec
 h Program Reg Pass, ACM Student Research Competition\n\nAccelerating Micro
 scope Data Analysis Using Parallel Computing\n\nRavi\n\nSingle-Molecule Lo
 calization Microscopy (SMLM) techniques deal with the diffraction limit of
  fluorescent microscopy by localizing single molecules with high precision
  by stochastically switching molecules on and off. Thousands of camera fra
 mes containing subsets of blinking molecules are recorded to obtain a sing
 le super-resolution image. Each blinking molecule in each frame is subject
 ed to localization protocols that fit the shape of the blink, assess the q
 uality of the blink and then estimate their center. The algorithm implemen
 ted originally in MATLAB and compiled CUDA C, to compute a ‘Super Resoluti
 on’ image took around 6 minutes to process 256x256 pixel images of a moder
 ately dense dataset. I ported the algorithm to C++ and parallelized it usi
 ng OpenMP to compute multiple frames in parallel.
URL:https://sc18.supercomputing.org/presentation/?id=spost122&sess=sess468
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