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    • 1. 发明授权
    • Identifying task instance outliers based on metric data in a large scale parallel processing system
    • 基于大规模并行处理系统中的度量数据识别任务实例异常值
    • US09280386B1
    • 2016-03-08
    • US13183234
    • 2011-07-14
    • Robert HagmannXiao ZhangEric S. TuneVrijendra Gokhale
    • Robert HagmannXiao ZhangEric S. TuneVrijendra Gokhale
    • G06F9/46G06F9/48
    • G06F9/5038G06F9/4881G06F9/5088
    • Among other disclosed subject matter, a method includes receiving metric data associated with an execution of each of a plurality of task instances. The plurality of task instances include task instances associated with a task and the metric data for each task instance relating to execution performance of the task instance. The method includes for each task instance determining a deviation of the metric data associated with the task instance relative to an overall deviation of the metric data for the plurality of task instances of the task during each of a plurality of intervals and combining deviation measurements for the task instance that exceed a threshold deviation to obtain a combined deviation value. Each deviation measurement corresponds to the deviation of the metric data for one of the plurality of intervals. The method includes ranking the combined deviation values associated with at least a subset of the task instances.
    • 在其他公开的主题中,一种方法包括接收与多个任务实例中的每一个的执行相关联的度量数据。 多个任务实例包括与任务相关联的任务实例以及与任务实例的执行性能有关的每个任务实例的度量数据。 该方法包括:对于每个任务实例,确定与任务实例相关联的度量数据相对于多个间隔中的每个期间的任务的多个任务实例的度量数据的总体偏差的偏差,并且组合用于 任务实例超过阈值偏差以获得组合偏差值。 每个偏差测量对应于多个间隔中的一个间隔的度量数据的偏差。 所述方法包括对与所述任务实例的至少一个子集相关联的组合偏差值进行排序。
    • 2. 发明授权
    • Identifying task instances that interfere with processor performance
    • 识别干扰处理器性能的任务实例
    • US09015718B1
    • 2015-04-21
    • US13247948
    • 2011-09-28
    • Xiao ZhangEric S. TuneRohit JnagalRobert HagmannVrijendra Gokhale
    • Xiao ZhangEric S. TuneRohit JnagalRobert HagmannVrijendra Gokhale
    • G06F9/48
    • G06F9/4881G06F9/485G06F9/5022G06F2209/501G06F2209/504Y02D10/22
    • Among other disclosed subject matter, a computer-implemented method includes receiving an indication that execution of an instance of a first task is degraded relative to a performance threshold associated with the first task. Performance data associated with the execution of the instance of the first task and performance data associated with execution of a plurality of additional tasks executed on the computing device are collected. For each of the plurality of additional tasks, the method includes determining a score for the respective additional task based on the performance data associated with the execution of the instance of the first task and performance data associated with the respective additional task. The method includes identifying one or more additional tasks as a potential cause of degraded performance based on the scores associated with each of the plurality of additional tasks. The method includes modifying an execution of a particular identified task.
    • 在其他公开的主题中,计算机实现的方法包括接收关于第一任务的实例的执行相对于与第一任务相关联的性能阈值降级的指示。 收集与执行第一任务的实例相关联的性能数据和与在计算设备上执行的多个附加任务的执行相关联的性能数据。 对于多个附加任务中的每一个,所述方法包括基于与第一任务的实例的执行相关联的性能数据和与相应附加任务相关联的性能数据来确定相应附加任务的得分。 该方法包括基于与多个附加任务中的每一个相关联的分数,将一个或多个附加任务识别为性能下降的潜在原因。 该方法包括修改特定标识任务的执行。