BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Denver
X-LIC-LOCATION:America/Denver
BEGIN:DAYLIGHT
TZOFFSETFROM:-0700
TZOFFSETTO:-0600
TZNAME:MDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0600
TZOFFSETTO:-0700
TZNAME:MST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260422T000713Z
LOCATION:710
DTSTART;TZID=America/Denver:20231113T111000
DTEND;TZID=America/Denver:20231113T113000
UID:submissions.supercomputing.org_SC23_sess445_ws_scalah101@linklings.com
SUMMARY:GPU-Based LU Factorization and Solve on Batches of Matrices with B
 and Structure
DESCRIPTION:Ahmad Abdelfattah, Stanimire Tomov, Piotr Luszczek, Hartwig An
 zt, and Jack Dongarra (University of Tennessee)\n\nThis paper presents a p
 ortable and performance-efficient approach to solve a batch of linear syst
 ems of equations using Graphics Processing Units (GPUs). Each system is re
 presented using a special type of matrices with a band structure above and
 /or below the diagonal. Each matrix is factorized using an LU factorizatio
 n with partial pivoting for numerical stability. Subsequently, the factors
  are used to find the solution for as many right hand sides as needed. The
  width of the band is often small enough that performing a fully dense LU 
 factorization results in poor performance. We follow the standard LAPACK s
 pecifications for addressing this type of problems and develop a dedicated
  solver that runs efficiently on GPUs. No similar solver is currently avai
 lable in the vendor's software stack, so performance results are shown on 
 both NVIDIA and AMD GPUs relative to a parallel CPU solution utilizing Ope
 nMP for thread-level parallelization.\n\nTag: Algorithms, Heterogeneous Co
 mputing, Large Scale Systems\n\nRegistration Category: Workshop Reg Pass\n
 \nSession Chairs: Vassil Alexandrov (Hartree Centre, STFC); Jack Dongarra 
 (University of Tennessee, Knoxville; Oak Ridge National Laboratory (ORNL))
 ; Christian Engelmann (Oak Ridge National Laboratory (ORNL)); Al Geist (Oa
 k Ridge National Laboratory (ORNL)); and Dieter A. Kranzlmueller (Ludwig-M
 axmilians-Universität München, Leibniz Supercomputing Centre (LRZ))\n\n
END:VEVENT
END:VCALENDAR