dfanalyzer/publications.html at master · hpcdb/dfanalyzer · GitHub

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        <h1>Publications</h1>
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            <ul><a href="index.html"><strong>DfAnalyzer</strong></a></ul>
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                <p><a href="index.html">Home</a> >> <a href="publications.html">Publications</a></p>

                <a id="simulations" class="anchor" href="#publications" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a>Publications
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            <ul>
                <li>
                V. Silva, D. Oliveira, P. Valduriez, M. Mattoso.
                <b>DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance</b>.
                Demonstration Session on the International Conference on Very Large Data Bases (VLDB), Rio de Janeiro, Brazil, 2018.
                </li><br>
                <li>
                J. Camata, V. Silva, P. Valduriez, M. Mattoso, A. Coutinho. <b>In Situ Visualization and Data Analysis for Turbidity Currents Simulation</b>.
                Computers & Geosciences, v.110:23-31, 2018. <a href="https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620127/file/in-situ-visualization-data.pdf" target="_blank">[paper]</a>
                </li><br>
                <li>
                V. Silva, R. Souza, J. Camata, D. Oliveira, P. Valduriez, A. Coutinho, M. Mattoso.
                <b>Capturing Provenance for Runtime Data Analysis in Computational Science and Engineering Applications</b>.
                7th International Provenance and Annotation Workshop (IPAW), 2018, Londres, UK.
                </li><br>
                <li>
                R. Souza, V. Silva, J. Camata, A. Coutinho, P. Valduriez, M. Mattoso. <b>Data Reduction in Scientific Workflows using Provenance Monitoring and User Steering</b>.
                Future Generation Computer Systems-The International Journal of eScience, Elsevier, 2018. <a href="https://hal-lirmm.ccsd.cnrs.fr/lirmm-01679967/document">[paper]</a>
                </li><br>
                <li>
                V. Silva, J. Camata, P. Valduriez, M. Mattoso, A. Coutinho. <b>In Situ Data Steering with Provenance Data</b>. In: Minisymposium 19 Applications and Computational Strategies for Finite
                Element Computations using LibMesh, 2017, Atlanta. 2017 SIAM Conference on Computational Science and Engineering. <a href="https://hpc4e.eu/sites/default/files/files/presentations/EnablingInSituVizProvenanceData.pdf" target="_blank">[presentation]</a>
                </li><br>
                <li>
                V. Silva, J. Leite, J. Camata, D. de Oliveira, A. Coutinho, P. Valduriez, M. Mattoso. <b>Raw data queries during data-intensive parallel workflow execution</b>.
                Special Issue on Workflows in Support of Large-Scale Science, Future Generation Computer Systems, Elsevier, v.75: 402-422, 2017. <a href="http://hal.cirad.fr/lirmm-01445219/document" target="_blank">[paper]</a> <a href="http://dx.doi.org/10.1016/j.future.2017.01.016"
                    target="_blank">[doi]</a>
                </li><br>
                <li>
                R. Souza, V. Silva, J. Camata, A. L. G. A. Coutinho, P. Valduriez, M. Mattoso.
                <b>Tracking of Online Parameter Fine-tuning in Scientific Workflows</b>.
                ACM/IEEE Supercomputing Workshop on Workflows in Support of Large-Scale Science (WORKS 2017), Denver, Colorado, USA, 2017.
                </li><br>
                <li>
                V. Silva, J. Camata, D. de Oliveira, A. L. G. A. Coutinho, P. Valduriez, M. Mattoso. <b>In Situ Data Steering on Sedimentation Simulation with Provenance Data</b>.
                Supercomputing conference, Salt Lake City, 2016. <a href="http://sc16.supercomputing.org/sc-archive/tech_poster/tech_poster_pages/post152.html"
                    target="_blank">[poster and paper]</a>
                </li><br>
                <li>
                V. Silva, D. de Oliveira, P. Valduriez, M. Mattoso. <b>Analyzing Related Raw Data Files through Dataflows</b>. Concurrency and Computation: Practice and Experience, v.28(8): 2528-2545, 2016.<a href="http://onlinelibrary.wiley.com/doi/10.1002/cpe.3616/abstract"
                    target="_blank">[doi]</a>
                </li><br>
                <li>
                R. Souza, V. Silva, A. Coutinho, P. Valduriez, M. Mattoso. <b>Online Input Data Reduction in Scientific Workflows</b>. 11th Workshop on Workflows in Support of Large-Scale Science (WORKS),
                ACM/IEEE Supercomputing Conference, 2016: 44-53. <a href="https://hal.archives-ouvertes.fr/lirmm-01679967/document" target="_blank">[paper]</a>
                </li><br>
                <li>
                V. Silva, D. de Oliveira, M. Mattoso. <b>How much domain data should be in provenance databases?</b>.
                7th International Workshop on Theory and Practice of Provenance (2015), Edinburgh. <a href="https://www.usenix.org/system/files/tapp15-de-oliveira.pdf"
                    target="_blank">[paper]</a>
                </li><br>
                <li>
                V. Silva, D. de Oliveira, M. Mattoso. <b>Exploratory Analysis of Raw Data Files through Dataflows</b>.
                International Symposium on Computer Architecture and High Performance Computing Workshop, p.114 (2014), Paris. <a href="https://doi.org/10.1109/SBAC-PADW.2014.32"
                    target="_blank">[doi]</a>
            </ul>


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