Actionable notifications
    43.
    发明授权

    公开(公告)号:US10802681B2

    公开(公告)日:2020-10-13

    申请号:US14165163

    申请日:2014-01-27

    Abstract: An actionable event notification disclosed herein provides actionable push notifications that allow an application server to collect information from end users. The actionable event notification includes a notification server that receives notification requests from application servers and communicates notifications to users where the notifications include specification for a notification UI form. In one implementation, the notification server modifies the callback identification on the notification from identification for the application server to identification for the notification server. A client device presents the notification UI form to a user to receive user responses. The user responses are communicated back to the notification server. The notification server processes the user responses and communicates them to the application server as necessary. Alternatively, the user responses are communicated directly to the application server requesting the notifications.

    Tool for investigating the performance of a distributed processing system

    公开(公告)号:US10686869B2

    公开(公告)日:2020-06-16

    申请号:US14500222

    申请日:2014-09-29

    Abstract: A performance investigation tool (PIT) is described herein for investigating the performance of a distributed processing system (DPS). The PIT operates by first receiving input information that describes a graph processing task to be executed using a plurality of computing units. The PIT then determines, based on the input information, at least one time-based performance measure that describes the performance of a DPS that is capable of performing the graphical task. More specifically, the PIT can operate in a manual mode to explore the behavior of a specified DPS, or in an automatic mode to find an optimal DPS from within a search space of candidate DPSs. A configuration system may then be used to construct a selected DPS, using the plurality of computing units. In one case, the graph processing task involves training a deep neural network model having a plurality of layers.

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