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Pursuing Coordinated Trajectory Progression and Efficient Resource Utilization of GPU-Enabled Molecular Dynamics Simulations., , , , , and . IEEE Design & Test, 31 (1): 40-50 (2014)Creating a portable, high-level graph analytics paradigm for compute and data-intensive applications., , , , and . IJHPCN, 13 (1): 105-118 (2019)Machine Learning Predictions of Runtime and IO Traffic on High-End Clusters., , , , and . CLUSTER, page 255-258. IEEE Computer Society, (2016)It's a Scheduling Affair: GROMACS in the Cloud with the KubeFlux Scheduler., , , , , , and . CANOPIE-HPC@SC, page 10-16. IEEE, (2021)Benchmarking the Performance of Scientific Applications with Irregular I/O at the Extreme Scale., , and . ICPP Workshops, page 292-301. IEEE Computer Society, (2014)A Portable, High-Level Graph Analytics Framework Targeting Distributed, Heterogeneous Systems., , and . WACCPD@SC, page 79-88. IEEE Computer Society, (2016)Efficient SDS Simulations on Multi-GPU Nodes of XSEDE High-End Clusters., , , , , and . e-Science, page 116-123. IEEE Computer Society, (2013)Performance characterization of irregular I/O at the extreme scale., , , , , and . Parallel Computing, (2016)Resource Management for Running HPC Applications in Container Clouds., , , , , , , and . ISC, volume 9697 of Lecture Notes in Computer Science, page 261-278. Springer, (2016)A Two-Tiered Approach to I/O Quality of Service in Docker Containers., , and . CLUSTER, page 490-491. IEEE Computer Society, (2015)