System for correlation of operating system and hardware trace events

    公开(公告)号:US10430313B2

    公开(公告)日:2019-10-01

    申请号:US14864597

    申请日:2015-09-24

    Abstract: Generally, this disclosure provides systems, methods and computer readable media for correlation of OS and hardware events to provide a corrected trace sequence. A system may include a processor configured to receive an OS event at a first time, generate a first timestamp based on a first clock associated with the OS, buffer the OS event until a second time, and generate a second timestamp based on the first clock. The system may also include a trace generation circuit configured to receive the OS event from the processor after the second time and generate a third timestamp based on a second clock associated with the trace generation circuit. The system may further include a trace correction circuit configured to calculate a corrected timestamp for the OS event based on differences between the first, second and third timestamps and further based on the relative frequency between the first and second clocks.

    DEEP LEARNING INFERENCE EFFICIENCY TECHNOLOGY WITH EARLY EXIT AND SPECULATIVE EXECUTION

    公开(公告)号:US20190180168A1

    公开(公告)日:2019-06-13

    申请号:US16266880

    申请日:2019-02-04

    Abstract: Systems, apparatuses and methods may provide for technology that processes an inference workload in a first subset of layers of a neural network that prevents or inhibits data dependent branch operations, conducts an exit determination as to whether an output of the first subset of layers satisfies one or more exit criteria, and selectively bypasses processing of the output in a second subset of layers of the neural network based on the exit determination. The technology may also speculatively initiate the processing of the output in the second subset of layers while the exit determination is pending. Additionally, when the inference workloads include a plurality of batches, the technology may mask one or more of the plurality of batches from processing in the second subset of layers.

    Deep learning inference efficiency technology with early exit and speculative execution

    公开(公告)号:US11562200B2

    公开(公告)日:2023-01-24

    申请号:US16266880

    申请日:2019-02-04

    Abstract: Systems, apparatuses and methods may provide for technology that processes an inference workload in a first subset of layers of a neural network that prevents or inhibits data dependent branch operations, conducts an exit determination as to whether an output of the first subset of layers satisfies one or more exit criteria, and selectively bypasses processing of the output in a second subset of layers of the neural network based on the exit determination. The technology may also speculatively initiate the processing of the output in the second subset of layers while the exit determination is pending. Additionally, when the inference workloads include a plurality of batches, the technology may mask one or more of the plurality of batches from processing in the second subset of layers.

    Deep learning inference efficiency technology with early exit and speculative execution

    公开(公告)号:US12211260B2

    公开(公告)日:2025-01-28

    申请号:US18519674

    申请日:2023-11-27

    Abstract: Systems, apparatuses and methods may provide for technology that processes an inference workload in a first subset of layers of a neural network that prevents or inhibits data dependent branch operations, conducts an exit determination as to whether an output of the first subset of layers satisfies one or more exit criteria, and selectively bypasses processing of the output in a second subset of layers of the neural network based on the exit determination. The technology may also speculatively initiate the processing of the output in the second subset of layers while the exit determination is pending. Additionally, when the inference workloads include a plurality of batches, the technology may mask one or more of the plurality of batches from processing in the second subset of layers.

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