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Evolving the Message Passing Programming Model via a Fault-Tolerant, Object-oriented Transport Layer., , , , , and . FTXS@HPDC, page 41-46. ACM, (2015)Enabling Adaptive Scientific Workflows Via Trigger Detection., , , , and . ISAV@SC, page 41-45. ACM, (2015)Trigger detection for adaptive scientific workflows using percentile sampling., , , , , and . CoRR, (2015)Analysis of Uncertain Scalar Data with Hixels., , , , , , and . Scientific Visualization, Springer, (2014)Towards Asynchronous Many-Task in Situ Data Analysis Using Legion., , , , , , , and . IPDPS Workshops, page 1033-1037. IEEE Computer Society, (2016)Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources., , , , , , , and . Int. J. High Perform. Comput. Appl., (2020)Metaprogramming-Enabled Parallel Execution of Apparently Sequential C++ Code., , , , , and . ESPM2@SC, page 24-31. IEEE Computer Society, (2016)Scalable Collectives for Distributed Asynchronous Many-Task Runtimes., , , , and . IPDPS Workshops, page 436-445. IEEE Computer Society, (2018)Trigger Detection for Adaptive Scientific Workflows Using Percentile Sampling., , , , , and . SIAM J. Sci. Comput., (2016)Sublinear Algorithms for Extreme-Scale Data Analysis., , , and . Topological and Statistical Methods for Complex Data, Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces, Springer, (2015)