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公开(公告)号:US20160239065A1
公开(公告)日:2016-08-18
申请号:US14621731
申请日:2015-02-13
申请人: VICTOR W. LEE , DAEHYUN KIM , YUXIN BAI , SHIHAO JI , SHENG LI , DHIRAJ D. KALAMKAR , NAVEEN K. MELLEMPUDI
发明人: VICTOR W. LEE , DAEHYUN KIM , YUXIN BAI , SHIHAO JI , SHENG LI , DHIRAJ D. KALAMKAR , NAVEEN K. MELLEMPUDI
CPC分类号: G06F1/324 , G06F1/3293 , G06F1/3296 , G06F9/5088 , G06F9/5094 , Y02D10/124 , Y02D10/126 , Y02D10/172 , Y02D10/22 , Y02D10/32
摘要: In an embodiment, a processor a plurality of cores to independently execute instructions, the cores including a plurality of counters to store performance information, and a power controller coupled to the plurality of cores, the power controller having a logic to receive performance information from at least some of the plurality of counters, determine a number of cores to be active and a performance state for the number of cores for a next operation interval, based at least in part on the performance information and model information, and cause the number of cores to be active during the next operation interval, the performance information associated with execution of a workload on one or more of the plurality of cores. Other embodiments are described and claimed.
摘要翻译: 在一个实施例中,处理器用于独立地执行指令的多个核心,所述核心包括存储性能信息的多个计数器以及耦合到所述多个核心的功率控制器,所述功率控制器具有从其中接收性能信息的逻辑 至少部分地基于性能信息和模型信息来确定多个计数器中的一些,以确定要激活的核心数量和用于下一个操作间隔的核心数量的性能状态,并且引起核心数量 在下一个操作间隔期间处于活动状态,所述性能信息与所述多个核心中的一个或多个核心上的工作负载的执行相关联。 描述和要求保护其他实施例。
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公开(公告)号:US08886641B2
公开(公告)日:2014-11-11
申请号:US12579855
申请日:2009-10-15
申请人: Anlei Dong , Yi Chang , Ruiqiang Zhang , Zhaohui Zheng , Gilad Avraham Mishne , Jing Bai , Karolina Barbara Buchner , Ciya Liao , Shihao Ji , Gilbert Leung , Georges-Eric Albert Marie Robert Dupret , Ling Liu
发明人: Anlei Dong , Yi Chang , Ruiqiang Zhang , Zhaohui Zheng , Gilad Avraham Mishne , Jing Bai , Karolina Barbara Buchner , Ciya Liao , Shihao Ji , Gilbert Leung , Georges-Eric Albert Marie Robert Dupret , Ling Liu
IPC分类号: G06F17/30
CPC分类号: G06F17/30867
摘要: In one embodiment, access a set of recency ranking data comprising one or more recency search queries and one or more recency search results, each of the recency search queries being recency-sensitive with respect to a particular time period and being associated with a query timestamp representing the time at which the recency search query is received at a search engine, each of the recency search results being generated by the search engine for one of the recency search queries and comprising one or more recency network resources. Construct a plurality of recency features from the set of recency ranking data. Train a first ranking model via machine learning using at least the recency features.
摘要翻译: 在一个实施例中,访问包括一个或多个新近度搜索查询和一个或多个新近度搜索结果的一组新近度排序数据,每个新近度搜索查询相对于特定时间段是新近敏感度,并且与查询时间戳相关联 表示在搜索引擎处接收到新近度搜索查询的时间,每个新近度搜索结果由搜索引擎为新近搜索查询之一生成,并且包括一个或多个新近网络资源。 从新近度排序数据集合构建多个新近特征。 通过机器学习,至少使用新特性来训练第一个排名榜。
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公开(公告)号:US20110029517A1
公开(公告)日:2011-02-03
申请号:US12533564
申请日:2009-07-31
申请人: Shihao Ji , Anlei Dong , Ciya Liao , Yi Chang , Zhaohui Zheng , Olivier Chapelle , Gordon Guo-Zheng Sun , Hongyuan Zha
发明人: Shihao Ji , Anlei Dong , Ciya Liao , Yi Chang , Zhaohui Zheng , Olivier Chapelle , Gordon Guo-Zheng Sun , Hongyuan Zha
IPC分类号: G06F17/30
CPC分类号: G06F16/951
摘要: To estimate, or predict, the relevance of items, or documents, in a set of search results, relevance information is extracted from user click data, and relational information among the documents as manifested by an aggregation of user clicks is determined from the click data. A supervised approach uses judgment information, such as human judgment information, as part of the training data used to generate a relevance predictor model, which minimizes the inherent noisiness of the click data collected from a commercial search engine.
摘要翻译: 为了在一组搜索结果中估计或预测项目或文档的相关性,从用户点击数据中提取相关性信息,并且从点击数据确定由用户点击的聚合表现的文档之间的关系信息 。 受监督的方法使用诸如人类判断信息之类的判断信息作为用于生成相关性预测器模型的训练数据的一部分,其使从商业搜索引擎收集的点击数据的固有噪声最小化。
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公开(公告)号:US20110093459A1
公开(公告)日:2011-04-21
申请号:US12579855
申请日:2009-10-15
申请人: Anlei Dong , Yi Chang , Ruiqiang Zhang , Zhaohui Zheng , Gilad Avraham Mishne , Jing Bai , Karolina Barbara Buchner , Ciya Liao , Shihao Ji , Gilbert Leung , Georges-Eric Albert Marie Robert Dupret , Ling Liu
发明人: Anlei Dong , Yi Chang , Ruiqiang Zhang , Zhaohui Zheng , Gilad Avraham Mishne , Jing Bai , Karolina Barbara Buchner , Ciya Liao , Shihao Ji , Gilbert Leung , Georges-Eric Albert Marie Robert Dupret , Ling Liu
IPC分类号: G06F17/30
CPC分类号: G06F17/30867
摘要: In one embodiment, access a set of recency ranking data comprising one or more recency search queries and one or more recency search results, each of the recency search queries being recency-sensitive with respect to a particular time period and being associated with a query timestamp representing the time at which the recency search query is received at a search engine, each of the recency search results being generated by the search engine for one of the recency search queries and comprising one or more recency network resources. Construct a plurality of recency features from the set of recency ranking data. Train a first ranking model via machine learning using at least the recency features.
摘要翻译: 在一个实施例中,访问包括一个或多个新近度搜索查询和一个或多个新近度搜索结果的一组新近度排序数据,每个新近度搜索查询相对于特定时间段是新近敏感度,并且与查询时间戳相关联 表示在搜索引擎处接收到新近度搜索查询的时间,每个新近度搜索结果由搜索引擎为新近搜索查询之一生成,并且包括一个或多个新近网络资源。 从新近度排序数据集合构建多个新近特征。 通过机器学习,至少使用新特性来训练第一个排名榜。
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