BUDGETED NEURAL NETWORK ARCHITECTURE SEARCH SYSTEM AND METHOD

    公开(公告)号:US20200302270A1

    公开(公告)日:2020-09-24

    申请号:US16357603

    申请日:2019-03-19

    Abstract: A neural network architecture search may be conducted by a controller to generate a neural network. The controller may perform the search by generating a directed acyclic graph across nodes in a search space, the nodes representing compute operations for a neural network. As the search is performed, the controller may retrieve resource availability information to modify the likelihood of a generated neural network architecture including previously unused nodes.

    TENANT-LEVEL SHARDING OF DISKS WITH TENANT-SPECIFIC STORAGE MODULES TO ENABLE POLICIES PER TENANT IN A DISTRIBUTED STORAGE SYSTEM

    公开(公告)号:US20200285396A1

    公开(公告)日:2020-09-10

    申请号:US16879612

    申请日:2020-05-20

    Abstract: Embodiments include receiving an indication of a data storage module to be associated with a tenant of a distributed storage system, allocating a partition of a disk for data of the tenant, creating a first association between the data storage module and the disk partition, creating a second association between the data storage module and the tenant, and creating rules for the data storage module based on one or more policies configured for the tenant. Embodiments further include receiving an indication of a type of subscription model selected for the tenant, and selecting the disk partition to be allocated based, at least in part, on the subscription model selected for the tenant. More specific embodiments include generating a storage map indicating the first association between the data storage module and the disk partition and indicating the second association between the data storage module and the tenant.

    Automated log analysis
    74.
    发明授权

    公开(公告)号:US10769152B2

    公开(公告)日:2020-09-08

    申请号:US15368373

    申请日:2016-12-02

    Abstract: There is disclosed in an example a computer-implemented method of providing automated log analysis, including: receiving a log stream comprising a plurality of transaction log entries, the log entries comprising a time stamp, a component identification (ID), and a name value pair identifying a transaction; creating an index comprising mapping a key ID to a name value pair of a log entry; and selecting from the index a key ID having a relatively large number of repetitions. There is also disclosed an apparatus and computer-readable medium for performing the method.

    OPTIMIZING SERVERLESS COMPUTING USING A DISTRIBUTED COMPUTING FRAMEWORK

    公开(公告)号:US20190303018A1

    公开(公告)日:2019-10-03

    申请号:US15943640

    申请日:2018-04-02

    Abstract: Aspects of the technology provide improvements to a Serverless Computing (SLC) workflow by determining when and how to optimize SLC jobs for computing in a Distributed Computing Framework (DCF). DCF optimization can be performed by abstracting SLC tasks into different workflow configurations to determined optimal arrangements for execution in a DCF environment. A process of the technology can include steps for receiving an SLC job including one or more SLC tasks, executing one or more of the tasks to determine a latency metric and a throughput metric for the SLC tasks, and determining if the SLC tasks should be converted to a Distributed Computing Framework (DCF) format based on the latency metric and the throughput metric. Systems and machine-readable media are also provided.

    LIGHTWEIGHT MALWARE INFERENCE ARCHITECTURE
    77.
    发明申请

    公开(公告)号:US20190294792A1

    公开(公告)日:2019-09-26

    申请号:US16102571

    申请日:2018-08-13

    Abstract: Systems, methods, computer-readable media, and devices are disclosed for creating a malware inference architecture. An instruction set is received at an endpoint in a network. At the endpoint, the instruction set is classified as potentially malicious or benign according to a first machine learning model based on a first parameter set. If the instruction set is determined by the first machine learning model to be potentially malicious, the instruction set is sent to a cloud system and is analyzed at the cloud system using a second machine learning model to determine if the instruction set comprises malicious code. The second machine learning model is configured to classify a type of security risk associated with the instruction set based on a second parameter set that is different from the first parameter set.

    VIRTUALIZED NETWORK FUNCTIONS AND SERVICE CHAINING IN SERVERLESS COMPUTING INFRASTRUCTURE

    公开(公告)号:US20190182128A1

    公开(公告)日:2019-06-13

    申请号:US16280983

    申请日:2019-02-20

    Abstract: In one embodiment, a method implements virtualized network functions in a serverless computing system having networked hardware resources. An interface of the serverless computing system receives a specification for a network service including a virtualized network function (VNF) forwarding graph (FG). A mapper of the serverless computing system determines an implementation graph comprising edges and vertices based on the specification. A provisioner of the serverless computing system provisions a queue in the serverless computing system for each edge. The provisioner further provisions a function in the serverless computing system for each vertex, wherein, for at least one or more functions, each one of said at least one or more functions reads incoming messages from at least one queue. The serverless computing system processes data packets by the queues and functions in accordance with the VNF FG. The queues and functions processes data packets in accordance with the VNF FG.

    TRAFFIC ANALYTICS SERVICE FOR TELEMETRY ROUTERS AND MONITORING SYSTEMS

    公开(公告)号:US20190149440A1

    公开(公告)日:2019-05-16

    申请号:US15810552

    申请日:2017-11-13

    Abstract: In one embodiment, a service converts a stream of network telemetry data into sketches. The stream of network telemetry data comprises a plurality of characteristics of traffic observed in a network. The service forms a time series of the sketches. The service performs anomaly detection on the time series of the sketches in part by calculating a joint distribution of ranks and frequencies of a portion of the characteristics at different points in time of the time series. The service sends an anomaly detection alert, when an anomaly is detected from the time series of the sketches.

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