• Publications
  • Influence
A Two-Tiered Approach to I/O Quality of Service in Docker Containers
Linux containers allow applications to run in complete isolation from one another without the extra overhead of running entirely separate operating systems. This approach eliminates memory overheadsExpand
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Resource Management for Running HPC Applications in Container Clouds
Innovations in operating-system-level virtualization technologies such as resource control groups, isolated namespaces, and layered file systems have driven a new breed of virtualization solutionsExpand
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Machine Learning Predictions of Runtime and IO Traffic on High-End Clusters
We use supervised machine learning algorithms (i.e., Decision Trees, Random Forest, and K-nearest Neighbors) to predict performance characteristics such as runtime and IO traffic of batch jobs onExpand
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Flux: Overcoming Scheduling Challenges for Exascale Workflows
Many emerging scientific workflows that target high-end HPC systems require complex interplay with the resource and job management software~(RJMS). However, portable, efficient and easy-to-useExpand
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Scalable I/O-Aware Job Scheduling for Burst Buffer Enabled HPC Clusters
The economics of flash vs. disk storage is driving HPC centers to incorporate faster solid-state burst buffers into the storage hierarchy in exchange for smaller parallel file system (PFS) bandwidth.Expand
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Evaluation of an Interference-free Node Allocation Policy on Fat-tree Clusters
Interference between jobs competing for network bandwidth on a fat-tree cluster can cause significant variability and degradation in performance. These performance issues can be mitigated orExpand
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PRIONN: Predicting Runtime and IO using Neural Networks
For job allocation decision, current batch schedulers have access to and use only information on the number of nodes and runtime because it is readily available at submission time from user jobExpand
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Performance Impact of I/O on QMCPack Simulations at the Petascale and Beyond
Traditional petascale applications, such as QMCPack, can scale their computations to completely utilize modern supercomputers like Titan, but they cannot scale their I/O. To preserve scalability,Expand
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Using surrogate-based modeling to predict optimal I/O parameters of applications at the extreme scale
On petascale systems, the selection of optimal values for I/O parameters without taking into account the I/O size and pattern can cause the I/O time to dominate the simulation time, compromising theExpand
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Pursuing Coordinated Trajectory Progression and Efficient Resource Utilization of GPU-Enabled Molecular Dynamics Simulations
To address the challenge of pursuing coordinated trajectory progression and efficient resource utilization of GPU-enabled molecular dynamics (MD) simulations on nondedicated high-end clusters, ourExpand
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