Topic: Performance, Portability, and Productivity

Performance analysis of parallel scientific codes is difficult. The HAC model allows direct comparison of data across domains with data viz and analysis tools available in other domains.

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This tool that automatically diagnoses performance and correctness faults in MPI applications. It identifies abnormal MPI tasks and code regions and finds the least-progressed task.

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These techniques emulate the behavior of anticipated future architectures on current machines to improve performance modeling and evaluation.

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Olga Pearce studies how to detect and correct load imbalance in high performance computing applications.

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Todd Gamblin leads the PAVE project, which develops performance data visualization techniques that are more intuitive for application scientists.

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Kathryn Mohror develops tools that give researchers the information they need to tune their programs and maximize results. After all, she says, “It’s all about getting the answers more quickly.”

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