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14 条记录 (耗时 0.031 秒)

    Load balancing and conflict processing in workflow with task dependencies
    2.
    发明授权
    Load balancing and conflict processing in workflow with task dependencies 有权

    公开(公告)号：US09811391B1

    公开(公告)日：2017-11-07

    申请号：US15449579

    申请日：2017-03-03

    申请人： Ryan Barrett ,  Taylor Sittler ,  Krishna Pant ,  Zhenghua Li

    发明人： Ryan Barrett ,  Taylor Sittler ,  Krishna Pant ,  Zhenghua Li

    IPC分类号： G06F19/24 ,  G06F19/22 ,  G06F19/18 ,  G06F9/52 ,  G06F9/48

    CPC分类号： G06F19/18 ,  G06F9/5083 ,  G06F19/22 ,  G06F19/24

    摘要： Embodiments in the disclosure are directed to the use of distributed computing to align reads against multiple portions of a reference dataset. Aligned portions of the reference dataset that correspond with an above-threshold alignment score can be assessed for the presence of sparse indicators that can be categorized and used to influence a determination of a state transition likelihood. Various tasks associated with the processing of reads (e.g., alignment, sparse indicator detection, and/or determination of a state transition likelihood) may be able to take advantage of parallel processing and can be distributed among the machines while considering the resource utilization of those machines. Different load-balancing mechanisms can be employed in order to achieve even resource utilization across the machines, and in some cases may involve assessing various processing characteristics that reflect a predicted resource expenditure and/or time profile for each task to be processed by a machine.

    Duplication and deletion detection using transformation processing of depth vectors
    3.
    发明授权
    Duplication and deletion detection using transformation processing of depth vectors 有权

    公开(公告)号：US09773031B1

    公开(公告)日：2017-09-26

    申请号：US15489473

    申请日：2017-04-17

    申请人： Krishna Pant ,  Taylor Sittler ,  Ryan Barrett

    发明人： Krishna Pant ,  Taylor Sittler ,  Ryan Barrett

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30303 ,  G06F17/30312 ,  G06F17/30569 ,  G06K9/00483 ,  G06K9/6249

    摘要： Techniques for accurately identifying duplications and deletions using depth vectors. A depth vector is generated for each of multiple clients based on a set of reads that is received and aligned to a reference data set. A transformation processing of the depth vectors is performed to produce multiple components. Each of the components is assigned an order based on the extent to which it accounts for cross-client differences in the depth vectors. Each of the components includes an intensity, multiple values, and multiple client weights. A subset of the components is identified based on the order. A sparse indicator and positional data for the sparse indicator can be determined from the components in the subset, and one or more clients can be identified as being associated with the components.

    Functional testing of code modifications for read processing systems
    8.
    发明授权
    Functional testing of code modifications for read processing systems 有权

    公开(公告)号：US09811439B1

    公开(公告)日：2017-11-07

    申请号：US15489492

    申请日：2017-04-17

    申请人： Ryan Barrett ,  Krishna Pant

    发明人： Ryan Barrett ,  Krishna Pant

    IPC分类号： G06F9/44 ,  G06F11/36 ,  G06F11/26

    CPC分类号： G06F11/3612 ,  G06F11/26

    摘要： Techniques for using functional testing to detect run-time impacts of code modifications. A method includes accessing a workflow including a plurality of stages for processing reads. The stages are defined based on modifiable code and include a first stage for aligning reads with a corresponding portion of a reference data set and a second stage for collectively analyzing data corresponding to the aligned reads. The method includes identifying functional testing specifications to correspond with the workflow, including a definition of which stages are to be performed during functional testing, a reduced reference data set, and a set of reads. The method includes performing the functional testing using the reduced reference data set and the set of reads, detecting a result generated via the performance, and outputting the result.