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        <identifier>oai:www.ideals.illinois.edu:2142/101213</identifier>
        <datestamp>2023-07-11</datestamp>
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        <thesis xmlns="http://www.ndltd.org/standards/metadata/etdms/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.ndltd.org/standards/metadata/etdms/1.1/ http://www.ndltd.org/standards/metadata/etdms/1.1/etdms11.xsd http://purl.org/dc/elements/1.1/ http://www.ndltd.org/standards/metadata/etdms/1.1/etdmsdc.xsd">
          <dc:contributor>Gupta, Indranil</dc:contributor>
          <dc:creator>Bhatt, Mayank</dc:creator>
          <dc:date>2018-09-04T20:36:52Z</dc:date>
          <dc:date>2018-09-04T20:36:52Z</dc:date>
          <dc:date>2020-09-05T09:15:32Z</dc:date>
          <dc:date>2018-04-24</dc:date>
          <dc:date>2018-05</dc:date>
          <dc:description>Cloud applications have burgeoned over the last few years, but they are typically written for loosely-coupled clusters such as datacenters.  In this thesis we investigate how one can run  cloud  applications  in  tightly-coupled  clusters  and  network  topologies,  namely  super-computers.  Specifically,  we look at a class of distributed machine learning systems called distributed graph processing systems, and run them on NCSA Blue Waters.  Partitioning the graph is key to achieving performance in distributed graph processing systems.  We present new topology-aware partitioning techniques that better exploit the structure of the network topologies in supercomputers.  Compared to existing work, our new Restricted Oblivious and Grid  Centroid  partitioning  approaches  produce  25-33%  improvement  in  makespan,  along with  a  sizable  reduction  in  network  traffic.   We  also  discuss  optimizations  such  as  smart network  buffers  that  further  amplify  the improvement.   To  help  operators  select  the  best graph partitioning technique, we culminate our experimental results into a decision tree.</dc:description>
          <dc:description>Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-05-01</dc:description>
          <dc:description>The student, Mayank Bhatt, accepted the attached license on 2018-04-23 at 17:13.</dc:description>
          <dc:description>The student, Mayank Bhatt, submitted this Thesis for approval on 2018-04-23 at 17:20.</dc:description>
          <dc:description>This Thesis was approved for publication on 2018-04-24 at 15:21.</dc:description>
          <dc:description>DSpace SAF Submission Ingestion Package generated from Vireo submission #12435 on 2018-08-31 at 17:21:19</dc:description>
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BHATT-THESIS-2018.pdf: 1415794 bytes, checksum: e08311d8168967b2e47baf1ef67f7fdc (MD5)
LICENSE.txt: 4209 bytes, checksum: b810a770b0873fc45062dd7e9ce83fde (MD5)
  Previous issue date: 2018-04-24</dc:description>
          <dc:description>Embargo set by: Seth Robbins for item 107297
Lift date: 2020-09-04T20:37:00Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system</dc:description>
          <dc:description>Embargo set by: Seth Robbins for item 107297
Lift date: 2020-09-04T20:42:08Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system</dc:description>
          <dc:description>U of I Only Restriction Lifted for Item 107297 on 2020-09-05T09:15:32Z.</dc:description>
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          <dc:identifier>http://hdl.handle.net/2142/101213</dc:identifier>
          <dc:language>en</dc:language>
          <dc:rights>Copyright 2018 Mayank Bhatt</dc:rights>
          <dc:subject>graph processing</dc:subject>
          <dc:subject>supercomputers</dc:subject>
          <dc:subject>topology</dc:subject>
          <dc:title>Topology-aware distributed graph processing for tightly-coupled clusters</dc:title>
          <dc:type>text</dc:type>
          <dc:type>text</dc:type>
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            <department>Computer Science</department>
            <discipline>Computer Science</discipline>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <level>Thesis</level>
            <name>M.S.</name>
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