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DTSTART:19700308T020000
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DTSTAMP:20260522T150117Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess322_post226@linklings.com
SUMMARY:Floating-Point Autotuner for CPU-Based Mixed-Precision Application
 s
DESCRIPTION:Ruidong Gu, Paul A. Beata, and Michela Becchi (North Carolina 
 State University)\n\nIn this poster, we present the design and development
  of an autotuning tool for floating-point code. The goal is to balance acc
 uracy and performance in order to produce an efficient and accurate mixed-
 precision program. The tuner starts by maximizing accuracy through the use
  of a high-precision library called CAMPARY and then achieves performance 
 gains under a given error bound by tuning down groups of variables and ope
 rations from the higher precision down to double  precision. We tested our
  tuning strategy on a computational fluid dynamics benchmark where we show
  a 4x speedup relative to the fully high-precision version during the iter
 ative tuning process and achieve an average absolute error of 2.8E-16 comp
 ared with the reference solution computed using the 256-bit GNU MPFR exten
 ded precision library.\n\nRegistration Category: Tech Program Reg Pass, Ex
 hibits Reg Pass\n\n
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