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Durango: Scalable Synthetic Workload Generation for Extreme-Scale Application Performance Modeling and Simulation.

, , , , , , and . SIGSIM-PADS, page 97-108. ACM, (2017)

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Durango: Scalable Synthetic Workload Generation for Extreme-Scale Application Performance Modeling and Simulation., , , , , , and . SIGSIM-PADS, page 97-108. ACM, (2017)LORAIN: a step closer to the PDES 'holy grail'., , and . SIGSIM-PADS, page 3-14. ACM, (2014)Using quality of service lanes to control the impact of raid traffic within a burst buffer., , , , , and . WSC, page 932-943. IEEE, (2017)Automatic Model Generation for Gate-Level Circuit PDES with Reverse Computation., , and . ACM Trans. Model. Comput. Simul., 27 (2): 12 (2017)Toward an End-to-End Framework for Modeling, Monitoring and Anomaly Detection for Scientific Workflows., , , , , , , , , and 7 other author(s). IPDPS Workshops, page 1370-1379. IEEE Computer Society, (2016)Improving Accuracy and Performance Through Automatic Model Generation for Gate-Level Circuit PDES with Reverse Computation., , and . SIGSIM-PADS, page 87-96. ACM, (2015)Warp speed: executing time warp on 1, 966, 080 cores., , , and . SIGSIM-PADS, page 327-336. ACM, (2013)Efficient Migration of Complex Off-Line Computer Vision Software to Real-Time System Implementation on Generic Computer Hardware., , , , and . IEEE Trans. Information Technology in Biomedicine, 8 (2): 142-153 (2004)Advanced optimizations for large scale parallel discrete event simulations.. Rensselaer Polytechnic Institute, USA, (2015)Time warp state restoration via delta encoding., , , , , and . WSC, page 3025-3036. IEEE/ACM, (2015)