Phrase based unstructured content parsing

    公开(公告)号:US12061627B2

    公开(公告)日:2024-08-13

    申请号:US17179614

    申请日:2021-02-19

    摘要: From an unstructured content using an ontology, a forward materialization graph is generated. The forward materialization graph is converted to a set of vector representations comprising multidimensional numbers representing elements of the forward materialization graph. A set of inference paths is computed for the set of vector representations. An inference path in the set of inference paths connecting a first vector representation with a second vector representation. Based on a set of features, the set of vector representations is formed into clusters, a feature in the set of features comprising a relevance probability, the relevance probability corresponding to a relevance of a portion of the unstructured content according to a relevance metric. A structured representation of the unstructured content is placed at an edge location of a content delivery network determined using the set of clusters.

    ISA-based compression in distributed training of neural networks

    公开(公告)号:US12039439B2

    公开(公告)日:2024-07-16

    申请号:US17129038

    申请日:2020-12-21

    摘要: An overall gradient vector is computed at a server from a set of ISA vectors corresponding to a set of worker machines. An ISA vector of a worker machine including ISA instructions corresponding to a set of gradients, each gradient corresponding to a weight of a node of a neural network being distributedly trained in the worker machine. A set of register values is optimized for use in an approximation computation with an opcode to produce an x-th approximate gradient of an x-th gradient. A server ISA vector is constructed in which a server ISA instruction in an x-th position corresponds to the x-th gradient in the overall gradient vector. A processor at the worker machine is caused to update a set of weights of the neural network, using the set of optimized register values and the server ISA vector, thereby completing one iteration of training.

    Hypervisor having local keystore
    8.
    发明授权

    公开(公告)号:US11809568B2

    公开(公告)日:2023-11-07

    申请号:US17318655

    申请日:2021-05-12

    摘要: An embodiment includes executing, by a hypervisor, a bootloader with access to a first logical partition of a non-volatile memory, the first logical partition storing a keystore. The embodiment also includes loading, by the bootloader, a kernel with access to the first logical partition of the non-volatile memory. The embodiment also includes receiving, by the bootloader, an encryption key from the keystore. The embodiment also includes performing, by the bootloader, a cryptographic algorithm using the encryption key on the kernel. The embodiment also includes executing, by the bootloader in an event that the performing of the cryptographic algorithm produces a first result, the kernel with access to the first logical partition of the non-volatile memory. The embodiment also includes halting, by the bootloader in an event that the performing of the cryptographic algorithm fails to produce the first result, booting of the kernel and generating an error message.

    Application refactoring with explainability

    公开(公告)号:US11782704B1

    公开(公告)日:2023-10-10

    申请号:US17845267

    申请日:2022-06-21

    IPC分类号: G06F8/72

    CPC分类号: G06F8/72

    摘要: By analyzing transaction data of an executing application, an application graph is constructed, the application graph comprising a plurality of nodes and a plurality of edges connecting pairs of the plurality of nodes, a node in the application graph corresponding to a module of the application. The plurality of nodes is clustered into a set of clusters. Formation of a cluster in the set of clusters is analyzed, the analyzing identifying a central node of the cluster, a feature importance in placing a node into the cluster, and an edge importance in placing the node into the cluster. Responsive to a confidence value in the cluster being above a threshold confidence value, using the central node of the cluster, the application is refactored into a set of microservices, the cluster corresponding to a microservice, the central node of the cluster corresponding to a component of the microservice.