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On the energy footprint of I/O management in Exascale HPC systems., , , , and . Future Generation Comp. Syst., (2016)On the Performance of Spark on HPC Systems: Towards a Complete Picture., and . SCFA, volume 10776 of Lecture Notes in Computer Science, page 70-89. Springer, (2018)On the Root Causes of Cross-Application I/O Interference in HPC Storage Systems., , , , and . IPDPS, page 750-759. IEEE Computer Society, (2016)Heterogeneous Hierarchical Workflow Composition., , , , , and . Computing in Science and Engineering, 21 (4): 76-86 (2019)Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models., , , , and . BDCAT, page 1-10. IEEE Computer Society, (2018)The challenges of elastic in situ analysis and visualization., , , and . ISAV@SC, page 23-28. ACM, (2019)Damaris: Addressing Performance Variability in Data Management for Post-Petascale Simulations., , , , , , , , and . TOPC, 3 (3): 15:1-15:43 (2016)A performance and energy analysis of I/O management approaches for exascale systems., , , and . DICT@HPDC, page 35-40. ACM, (2014)Chronos: Failure-aware scheduling in shared Hadoop clusters., , , and . BigData, page 313-318. IEEE Computer Society, (2015)Toward High-Performance Computing and Big Data Analytics Convergence: The Case of Spark-DIY., , , , and . IEEE Access, (2019)