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DTSTAMP:20181221T160743Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181114T083000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess342_drs110@linklings.com
SUMMARY:Productive Data Locality Optimizations in Distributed Memory
DESCRIPTION:Doctoral Showcase\nWorkshop Reg Pass, Tutorial Reg Pass, Tech 
 Program Reg Pass, Exhibits Reg Pass, Exhibits - Exhibit Hall Only Reg Pass
 \n\nProductive Data Locality Optimizations in Distributed Memory\n\nKayrak
 lioglu, El-Ghazawi\n\nWith deepening memory hierarchies in HPC systems, th
 e challenge of managing data locality gains more importance. Coincidentall
 y, increasing ubiquity of HPC systems and wider range of disciplines utili
 zing HPC introduce more programmers to the HPC community. Given these two 
 trends, it is imperative to have scalable and productive ways to manage da
 ta locality.<br /><br />In this research, we address the problem in multip
 le ways. We propose a novel language feature that programmers can use to t
 ransform shared memory applications to distributed memory applications eas
 ily. We introduce a high-level profiling tool to help understand how distr
 ibuted arrays are used in an application. As next steps, we are designing 
 a model to describe the implementation of data locality optimizations as a
 n engineering process, which can lend itself to combinatorial optimization
 . We are also implementing a profile-based automatic optimization framewor
 k that utilizes AI to replace the programmer completely in implementing op
 timizations for distributed memory.
URL:https://sc18.supercomputing.org/presentation/?id=drs110&sess=sess342
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