Compute Facilities Modeling

Adaptive Learning for Concept Drift in Application Performance Modeling

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Improving Computational Science Throughput via Model-Based I/O Optimization (SciDAC SUPER-SDAV)

Machine learning-based probabilistic I/O performance models that take the background traffic, and system state into account while prediciting application performance on HPC system.

Self-Aware Adaptive Workflow and Data Management Services for Future HPC Systems

Develop modular characterization approaches, where we can examine key performance parameters and application execution similarities.