Highlights include scalable deep learning, high-order finite elements, data race detection, and reduced order models.
Topic: Power Management
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AI/ML | Biology/Biomedicine | Computational Math | Computational Science | Data Science | Data-Driven Decisions | Debugging and Correctness | Deep Learning | Discrete Mathematics | HPC Systems and Software | Hydrodynamics | Open-Source Software | Performance, Portability, and Productivity | Power Management | Programming Languages and Models | Solvers | Transport
Highlights include the latest work with RAJA, the Exascale Computing Project, algebraic multigrid preconditioners, and OpenMP.
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libMSR provides a convenient interface to access Model Specific Registers and to allow tools to utilize their full functionality.
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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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