Apparatus and method for approximate puzzlepiece compositing

    公开(公告)号:US12131420B2

    公开(公告)日:2024-10-29

    申请号:US17833890

    申请日:2022-06-06

    申请人: Intel Corporation

    发明人: William Usher

    IPC分类号: G06T15/06 G06T15/00 G06T15/50

    摘要: Apparatus and method for piece-wise compositing. For example, one embodiment of an apparatus comprises: a plurality of nodes to operate in parallel to render an image associated with a data set; and an interconnect to couple the plurality of nodes; a first node of the plurality of nodes to: independently march a first one or more rays through local data comprising a first portion of the data set to determine first local moments; sum the first local moments to generate a first partial moment; combine the first partial moment with one or more additional partial moments received from other nodes of the plurality of nodes to generate a global moment; re-march the first one or more rays or re-blend captured samples using the global moment to render the first portion of the image; and combine the first portion of the image with other portions of the image received from other nodes of the plurality of nodes to produce a final rendered image corresponding to the data set.

    Model-based semantic text searching

    公开(公告)号:US12130850B2

    公开(公告)日:2024-10-29

    申请号:US18147960

    申请日:2022-12-29

    申请人: Adobe Inc.

    摘要: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

    Superposition-based content serving

    公开(公告)号:US12126699B2

    公开(公告)日:2024-10-22

    申请号:US17972408

    申请日:2022-10-24

    摘要: Embodiments of the disclosed technologies receive a request including a user identifier and metadata associated with a slot available at a user system, remove the user identifier from the request to produce anonymized request data, receive, from a machine learning model, superposition data that correlates with the anonymized request data, send the superposition data for the anonymized request data to a real-time content-to-request matching process, receive, from the real-time content-to-request matching process, an identifier that identifies a content distribution selected based on the superposition data, and initiate the selected content distribution through the network to the slot in response to the request.

    Self-tuning analytics system with observed execution optimization

    公开(公告)号:US12118395B1

    公开(公告)日:2024-10-15

    申请号:US17116405

    申请日:2020-12-09

    IPC分类号: G06F9/50 G06F9/48

    摘要: Techniques for self-tuning an analytics system via observed execution optimization are described. Upon a need for execution resources, a resource manager can select a type of executor from multiple candidate executor types based at least in part on one or more of current execution data associated with the execution of tasks of a user application and/or historic execution data associated with one or more other applications. The current execution data may include event log data originated by the driver application based on the execution of the user application and/or metric data describing characteristics of one or more worker nodes involved with executing the user application or characteristics of one or more other executors implemented by the one or more worker nodes in executing the user application.

    Cooperative memory subsystem data recovery

    公开(公告)号:US12111731B2

    公开(公告)日:2024-10-08

    申请号:US18474046

    申请日:2023-09-25

    IPC分类号: G06F11/14

    CPC分类号: G06F11/1415 G06F2201/805

    摘要: Exemplary methods, apparatuses, and systems include detecting a failure of a first memory subsystem of a plurality of memory subsystems. A first recovery instruction is sent to a second memory subsystem of the plurality of memory subsystems. The first recovery instruction directs the second memory subsystem to recover a first subset of data stored by the first memory subsystem. A second recovery instruction is sent to a third memory subsystem of the plurality of memory subsystems. The second recovery instruction directs the third memory subsystem to rebuild a second subset of data stored by the first memory subsystem. The first and second subsets of data differ from one another.

    Memory bandwidth monitoring extensible counter

    公开(公告)号:US12106106B2

    公开(公告)日:2024-10-01

    申请号:US17134256

    申请日:2020-12-25

    申请人: Intel Corporation

    IPC分类号: G06F9/30 G06F9/38

    摘要: Embodiments for memory bandwidth monitoring extensible counters are described. In embodiments, an apparatus includes memory bandwidth monitoring hardware to monitor an event, a shared cache to be shared by multiple cores. At least one of the cores is to execute multiple threads and includes at least three registers. The first register is programmable by software to store a thread identifier of one of threads and an event identifier of the event during execution of the thread. At least one value of the event identifier corresponds to a shared cache miss. The second register is to provide to the software a second value corresponding to a number of bits available to represent the count. The third register is to provide to the software a count of occurrences of the event and an indicator to indicate whether the count reached a maximum count representable by the number of bits.