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      <div class="TdmEntry">Research Program<ul><li><a href="uid12.html&#10;&#9;&#9;  ">Algorithms for probabilistic environments</a></li><li><a href="uid15.html&#10;&#9;&#9;  ">Platform-aware scheduling strategies</a></li><li><a href="uid18.html&#10;&#9;&#9;  ">High-performance computing and linear algebra</a></li><li><a href="uid25.html&#10;&#9;&#9;  ">Compilers, code optimization and
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      <div class="TdmEntry">New Results<ul><li><a href="uid54.html&#10;&#9;&#9;  ">Acyclic partitioning of large directed acyclic graphs </a></li><li><a href="uid55.html&#10;&#9;&#9;  ">Further notes on Birkhoff-von Neumann decomposition of doubly stochastic matrices</a></li><li><a href="uid56.html&#10;&#9;&#9;  ">Low-Cost Approximation Algorithms for Scheduling Independent Tasks on Hybrid Platforms</a></li><li><a href="uid57.html&#10;&#9;&#9;  ">Memory-aware tree partitioning on homogeneous platforms </a></li><li><a href="uid58.html&#10;&#9;&#9;  ">Parallel scheduling of DAGs under memory constraints.</a></li><li><a href="uid59.html&#10;&#9;&#9;  ">On the Complexity of the Block Low-Rank Multifrontal Factorization</a></li><li><a href="uid60.html&#10;&#9;&#9;  ">Large-scale 3-D EM modelling with a Block Low-Rank multifrontal direct solver</a></li><li><a href="uid61.html&#10;&#9;&#9;  ">On exploiting sparsity of multiple right-hand sides in sparse direct solvers</a></li><li><a href="uid62.html&#10;&#9;&#9;  ">Revisiting temporal failure independence
in large scale systems</a></li><li><a href="uid63.html&#10;&#9;&#9;  ">Co-scheduling Amdahl applications on cache-partitioned systems</a></li><li><a href="uid64.html&#10;&#9;&#9;  ">Coping with silent and fail-stop errors at scale by combining replication and checkpointing</a></li><li><a href="uid65.html&#10;&#9;&#9;  ">Optimal checkpointing period
with replicated execution on heterogeneous platforms</a></li><li><a href="uid66.html&#10;&#9;&#9;  ">A Failure Detector for HPC Platforms</a></li><li><a href="uid67.html&#10;&#9;&#9;  ">Budget-aware scheduling algorithms
for scientific workflows on IaaS cloud platforms</a></li><li><a href="uid68.html&#10;&#9;&#9;  ">Resilience for stencil computations with latent errors</a></li><li><a href="uid69.html&#10;&#9;&#9;  ">Checkpointing workflows for fail-stop errors</a></li><li><a href="uid70.html&#10;&#9;&#9;  ">Optimal Cooperative Checkpointing for Shared High-Performance Computing Platforms</a></li><li><a href="uid71.html&#10;&#9;&#9;  ">Parallel Code Generation of Synchronous Programs for a Many-core Architecture</a></li><li><a href="uid72.html&#10;&#9;&#9;  ">Optimizing Affine Control with Semantic Factorizations</a></li><li><a href="uid73.html&#10;&#9;&#9;  ">Improving Communication Patterns in Polyhedral Process Networks</a></li><li><a href="uid74.html&#10;&#9;&#9;  ">Static Analyses of pointers</a></li><li><a href="uid75.html&#10;&#9;&#9;  ">Dataflow static analyses and optimisations</a></li></ul></div>
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	    2017</a> | <a href="http://www.inria.fr/en/teams/roma">Presentation of the Project-Team ROMA</a> | <a href="http://www.ens-lyon.fr/LIP/ROMA/">ROMA Web Site
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        <div class="Titrepage1">2017 Project-Team Activity Report
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        <div class="Projetpage1">
          <div class="ProjetCourtpage1">ROMA</div>
          <div class="ProjetLongpage1">Optimisation des ressources : modèles, algorithmes et ordonnancement<div class="DescriptionTeam"/></div>
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          <span class="definition">Research centre: </span>
          <a href="http://www.inria.fr/centre/grenoble">Grenoble - Rhône-Alpes</a>
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        <div class="partner"><span class="definition">In partnership with: </span>CNRS, Ecole normale supérieure de Lyon, Université Claude Bernard (Lyon 1)<br/><span class="definition">In collaboration with: </span>Laboratoire de l'Informatique du Parallélisme (LIP)<br/><br/></div>
        <div class="domainepage1"><span class="definition">Field: </span><a href="&#10;&#9;      http://www.inria.fr/en/domains/Networks-Systems-and-Services-Distributed-Computing">Networks, Systems and Services, Distributed Computing</a><br/><span class="definition">Theme: </span>Distributed and High Performance Computing</div>
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          <span class="definition">Keywords: </span>
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            <a href="/keywords/2017/computing">Computer Science and Digital Science: </a>
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          <ul>
            <li>A1.1.1. - Multicore, Manycore</li>
            <li>A1.1.2. - Hardware accelerators (GPGPU, FPGA, etc.)</li>
            <li>A1.1.3. - Memory models</li>
            <li>A1.1.4. - High performance computing</li>
            <li>A1.1.5. - Exascale</li>
            <li>A1.1.9. - Fault tolerant systems</li>
            <li>A1.6. - Green Computing</li>
            <li>A6.1. - Mathematical Modeling</li>
            <li>A6.2.3. - Probabilistic methods</li>
            <li>A6.2.5. - Numerical Linear Algebra</li>
            <li>A6.2.6. - Optimization</li>
            <li>A6.2.7. - High performance computing</li>
            <li>A6.3. - Computation-data interaction</li>
            <li>A7.1. - Algorithms</li>
            <li>A8.1. - Discrete mathematics, combinatorics</li>
            <li>A8.2. - Optimization</li>
            <li>A8.7. - Graph theory</li>
            <li>A8.9. - Performance evaluation</li>
          </ul>
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            <a href="/keywords/2017/other">Other Research Topics and Application Domains: </a>
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          <ul>
            <li>B3.2. - Climate and meteorology</li>
            <li>B3.3. - Geosciences</li>
            <li>B4. - Energy</li>
            <li>B4.1. - Fossile energy production (oil, gas)</li>
            <li>B4.5.1. - Green computing</li>
            <li>B5.2.3. - Aviation</li>
            <li>B5.5. - Materials</li>
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