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    <completedDate>2019-02-15</completedDate>
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    <title language="eng">Parallel PIPS-SBB: Multi-Level Parallelism For Stochastic Mixed-Integer Programs</title>
    <abstract language="eng">PIPS-SBB is a distributed-memory parallel solver with a scalable data distribution paradigm. It is designed to solve MIPs with a dual-block angular structure, which is characteristic of deterministic-equivalent Stochastic Mixed-Integer Programs (SMIPs). In this paper, we present two different parallelizations of Branch &amp; Bound (B&amp;B), implementing both as extensions of PIPS-SBB, thus adding an additional layer of parallelism. In the first of the proposed frameworks, PIPS-PSBB, the coordination and load-balancing of the different optimization workers is done in a decentralized fashion. This new framework is designed to ensure all available cores are processing the most promising parts of the B&amp;B tree. The second, ug[PIPS-SBB,MPI], is a parallel implementation using the Ubiquity Generator (UG), a universal framework for parallelizing B&amp;B tree search that has been successfully applied to other MIP solvers. We show the effects of leveraging multiple levels of parallelism in potentially improving scaling performance beyond thousands of cores.</abstract>
    <parentTitle language="eng">Computational Optimization and Applications</parentTitle>
    <identifier type="doi">10.1007/s10589-019-00074-0</identifier>
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    <author>Lluis-Miquel Munguia</author>
    <submitter>Franziska Schlösser</submitter>
    <author>Geoffrey Oxberry</author>
    <author>Deepak Rajan</author>
    <author>Yuji Shinano</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
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    <collection role="institutes" number="aopt">Applied Optimization</collection>
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  <doc>
    <id>6551</id>
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    <publishedYear>2017</publishedYear>
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    <language>eng</language>
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    <issue>ZIB-Report 17-58</issue>
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    <completedDate>2017-07-11</completedDate>
    <publishedDate>2017-07-11</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Parallel PIPS-SBB: Multi-Level Parallelism For Stochastic Mixed-Integer Programs</title>
    <abstract language="eng">PIPS-SBB is a distributed-memory parallel solver with a scalable data distribution paradigm. It is designed to solve MIPs with a dual-block angular structure, which is characteristic of deterministic-equivalent Stochastic Mixed-Integer Programs (SMIPs). In this paper, we present two different parallelizations of Branch &amp; Bound (B&amp;B), implementing both as extensions of PIPS-SBB, thus adding an additional layer of parallelism. In the first of the proposed frameworks, PIPS-PSBB, the coordination and load-balancing of the different optimization workers is done in a decentralized fashion. This new framework is designed to ensure all available cores are processing the most promising parts of the B&amp;B tree. The second, ug[PIPS-SBB,MPI], is a parallel implementation using the Ubiquity Generator (UG), a universal framework for parallelizing B&amp;B tree search that has been successfully applied to other MIP solvers. We show the effects of leveraging multiple levels of parallelism in potentially improving scaling performance beyond thousands of cores.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-65517</identifier>
    <identifier type="doi">10.1007/s10589-019-00074-0</identifier>
    <enrichment key="SourceTitle">Computational Optimization and Applications</enrichment>
    <author>Lluis-Miquel Munguia</author>
    <submitter>Yuji Shinano</submitter>
    <author>Geoffrey Oxberry</author>
    <author>Deepak Rajan</author>
    <author>Yuji Shinano</author>
    <series>
      <title>ZIB-Report</title>
      <number>17-58</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>PIPS-SBB, UG, Parallel Branch and Bound</value>
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      <language>eng</language>
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      <value>PIPS-SBB, UG, Parallel Branch and Bound</value>
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    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="ccs" number="I.">Computing Methodologies</collection>
    <collection role="pacs" number="00.00.00">GENERAL</collection>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
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    <collection role="persons" number="shinano">Shinano, Yuji</collection>
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