WORKLOAD PERFORMANCE PREDICTION AND REAL-TIME COMPUTE RESOURCE RECOMMENDATION FOR A WORKLOAD USING PLATFORM STATE SAMPLING

    公开(公告)号:US20230047295A1

    公开(公告)日:2023-02-16

    申请号:US17973321

    申请日:2022-10-25

    Abstract: Embodiments described herein are generally directed to improving predictions regarding workload performance to facilitate dynamic auto device selection. In an example, based on telemetry samples collected from a computer system in real-time and indicative of a state of the computer system, one or more workload performance prediction models are built or updated for a heterogeneous set of computer resources of the computer system with reference to one or more optimization goals. At a time of execution of a workload, a particular computer resource of the heterogeneous set of computer resources on which to dispatch the workload is dynamically determined by: (i) generating multiple predicted performance scores each corresponding to one of the computer resources based on the state of the computer system and the one or more workload performance prediction models; and (ii) selecting the particular computer resource based on the predicted performance scores.

    METHODS AND APPARATUS TO SYNCHRONIZE THREADS

    公开(公告)号:US20220334888A1

    公开(公告)日:2022-10-20

    申请号:US17855314

    申请日:2022-06-30

    Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to synchronized threads. Example apparatus disclosed herein identify a first trigger frequency associated with a first application thread, the first trigger frequency corresponding to first times of first requests associated with the first application thread. Disclosed example apparatus also identify a second trigger frequency associated with a second application thread, the second trigger frequency corresponding to second times of second requests associated with the second application thread, the second trigger frequency different from the first trigger frequency. Disclosed example apparatus further determine a third trigger frequency based on the first and second trigger frequencies, and adjust at least one of the first requests or the second requests to the third trigger frequency.

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