MEMORY SCHEMES FOR INFRASTRUCTURE PROCESSING UNIT ARCHITECTURES

    公开(公告)号:US20210389880A1

    公开(公告)日:2021-12-16

    申请号:US17412971

    申请日:2021-08-26

    Abstract: Systems, apparatuses, and methods provide for memory management where an infrastructure processing unit bypasses a central processing unit. Such an infrastructure processing unit determines if incoming packets of memory traffic trigger memory rules stored by the infrastructure processing unit. The incoming packets are routed to the central processing unit in a default mode when the incoming packets do not trigger the memory rules. Conversely, the incoming packets are routed to the infrastructure processing unit and bypass the central processing unit in an inline mode when the incoming packets trigger the memory rules. A memory architecture communicatively coupled to the central processing unit receives a set of atomic transactions from the infrastructure processing unit that bypasses the central processing unit and performs the set of atomic transactions from the infrastructure processing unit.

    MODEL PROPAGATION IN EDGE ARCHITECTURES

    公开(公告)号:US20210326763A1

    公开(公告)日:2021-10-21

    申请号:US17359162

    申请日:2021-06-25

    Abstract: Devices, methods, apparatus, systems, and articles of manufacture to propagate a model in edge architecture are disclosed. An example device includes an interface to access a model received via the edge architecture; at least one memory; instructions in the device; and one or more processors to execute the instructions to: determine a number of attestation responses based on a blockchain associated with the model; determine if the number satisfies a threshold number; initiate an execution of the model in response to verifying that the number satisfies the threshold number; and transmit the model to a plurality of edge appliances in response the number not satisfying the threshold number.

    LOW OVERHEAD MEMORY CONTENT ESTIMATION

    公开(公告)号:US20210109679A1

    公开(公告)日:2021-04-15

    申请号:US17127915

    申请日:2020-12-18

    Abstract: Systems, apparatuses and methods may provide for technology that samples machine learning (ML) data from a local memory in accordance with a specified configuration, wherein the ML data is associated with one or more tasks submitted by one or more processor cores. The technology may also estimate the complexity of the sampled ML data based on one or more thresholds and schedule the task(s) for execution by one or more accelerators based on the complexity and telemetry data associated with a link to the accelerator(s).

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