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公开(公告)号：US09052895B2
公开(公告)日：2015-06-09
申请号：US13082144
申请日：2011-04-07
CPC分类号： G06F1/3203 , G06F1/32 , G06F1/3206 , G06F1/3228 , G06F1/324 , G06F1/329 , G06F1/3296 , G06F9/4881 , G06F9/4893 , G06F9/5094 , Y02D10/00 , Y02D10/126 , Y02D10/17 , Y02D10/20 , Y02D10/22 , Y02D10/24
摘要： Systems, apparatuses, methods, and software that implement power budget allocation optimization algorithms in multi-processor systems, such as server farms. The algorithms are derived from a queuing theoretic model that minimizes the mean response time of the system to the jobs in the workload while accounting for a variety of factors. These factors include, but are not necessarily limited to, the type of power (frequency) scaling mechanism(s) available within the processors in the system, the power-to-frequency relationship(s) of the processors for the scaling mechanism(s) available, whether or not the system is an open or closed loop system, the arrival rate of jobs incoming into the system, the number of jobs within the system, and the type of workload being processed.
摘要翻译： 在多处理器系统（如服务器场）中实施功率预算分配优化算法的系统，设备，方法和软件。 这些算法是从排队理论模型中得出的，该模型最大限度地减少了系统对工作负载中的作业的平均响应时间，同时考虑了各种因素。 这些因素包括但不一定限于系统内处理器内可用的功率（频率）缩放机制的类型，用于缩放机制的处理器的功率与频率关系（s） ），无论系统是开放还是闭环系统，系统中进入作业的到达率，系统中的作业数以及正在处理的工作负载的类型。
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公开(公告)号：US08914495B2
公开(公告)日：2014-12-16
申请号：US13154825
申请日：2011-06-07
IPC分类号： G06F15/173 , H05K7/14
CPC分类号： H05K7/1498
摘要： A mechanism is provided for automatically detecting and locating equipment within an intelligent equipment rack. The intelligent equipment rack comprises a rack controller that determines whether a signal has been received indicating that a rack space in a plurality of rack spaces in the intelligent equipment rack has been occupied by a piece of electronic equipment. Responsive to receiving the signal indicating that the rack space has been occupied by the piece of electronic equipment, the rack controller updates a rack information table in the memory with occupation information related to the rack space occupied by the piece of electronic equipment.
摘要翻译： 提供了一种用于自动检测和定位智能设备机架内的设备的机构。 智能设备机架包括：机架控制器，其确定是否已经接收到指示智能设备机架中的多个机架空间中的机架空间已被一块电子设备占用的信号。 响应于接收到指示机架空间已被该电子设备占用的信号，机架控制器利用与该电子设备所占用的机架空间有关的占用信息来更新存储器中的机架信息表。
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公开(公告)号：US20130253969A1
公开(公告)日：2013-09-26
申请号：US13424964
申请日：2012-03-20
CPC分类号： G06Q10/06 , G06Q30/0208
摘要： A method for a provider to generate incentives for users to perform tasks includes the following steps. The tasks are assigned to the users to obtain a matrix of task assignments in which each of the users is assigned to at least one of the tasks and each of the tasks is assigned to at least one of the users, wherein each of the task assignments has a value and a cost to the provider, wherein for a given one of the task assignments the value less the cost to the provider is an economic utility to the provider, and wherein the step of assigning the tasks to the users is done so as to maximize a net benefit to the provider which is a sum of the economic utility for all of the task assignments. Incentives are offered to the users to perform the task assignments.
摘要翻译： 提供者为用户执行任务而产生激励的方法包括以下步骤。 将任务分配给用户以获得任务分配矩阵，其中将每个用户分配给至少一个任务，并且将每个任务分配给至少一个用户，其中每个任务分配 对于提供商来说具有价值和成本，其中对于给定的一个任务分配中，提供商的成本较低的价值是对提供商的经济效用，并且其中将任务分配给用户的步骤是这样做的： 最大化对提供者的净利益，这是所有任务任务的经济效用之和。 激励措施提供给用户执行任务分配。
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4.发明授权Saving power by placing inactive computing devices in optimized configuration corresponding to a specific constraint 有权通过将非活动计算设备置于与特定约束对应的优化配置中来节省电力公开(公告)号：US08516284B2
公开(公告)日：2013-08-20
申请号：US12939635
申请日：2010-11-04
申请人： Hoi Y. Chan , Rajarshi Das , James E. Hanson , Canturk Isci , Jeffrey O. Kephart , David W. Levine
发明人： Hoi Y. Chan , Rajarshi Das , James E. Hanson , Canturk Isci , Jeffrey O. Kephart , David W. Levine
CPC分类号： G06F1/3234 , G06F1/3206 , G06F1/3209 , G06F1/3287 , G06F1/329 , G06F9/5094 , H04L67/00 , Y02D10/171 , Y02D10/22 , Y02D10/24
摘要： A system method and computer program product for managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided, and, in each case, the tradeoff between responsiveness and power savings is formulated as an objective function with constraints, and the desired number of devices in each inactive state emerges as the solution to a constraint optimization problem.
摘要翻译： 一种用于管理多个计算设备的准备状态的系统方法和计算机程序产品。 编程处理器单元在接收到请求时操作：将一个或多个计算设备从非活动池提供到活动池，或接受一个或多个活动计算设备进入非活动池。 非活动池管理器通过以下方式主动管理每个计算设备的不活动状态：通过解决描述用户指定的权衡的约束优化问题来确定要置于每个无效状态的计算设备的期望数量（和身份） 在预期的准备状态（估计需要下一步需要激活计算设备的时间）并节约能源; 生成将当前的无效状态集合改变为所需集合的计划; 并执行该计划。 提供了量化需求浪涌的期望响应性的多种替代方法，并且在每种情况下，响应性和功率节省之间的折衷被形成为具有约束的目标函数，并且在每个非活动状态期间的期望数量的设备出现为 解决约束优化问题。
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公开(公告)号：US20120331318A1
公开(公告)日：2012-12-27
申请号：US13603170
申请日：2012-09-04
申请人： Hoi Y. Chan , Rajarshi Das , James E. Hanson , Canturk Isci , Jeffrey O. Kephart , David W. Levine
发明人： Hoi Y. Chan , Rajarshi Das , James E. Hanson , Canturk Isci , Jeffrey O. Kephart , David W. Levine
IPC分类号： G06F1/00
CPC分类号： G06F1/3234 , G06F1/3206 , G06F1/3209 , G06F1/3287 , G06F1/329 , G06F9/5094 , H04L67/00 , Y02D10/171 , Y02D10/22 , Y02D10/24
摘要： Managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. The system proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.
摘要翻译： 管理多个计算设备的准备状态。 编程处理器单元在接收到请求时操作：将一个或多个计算设备从非活动池提供到活动池，或者将一个或多个活动计算设备接纳到非活动池中。 系统通过以下方式主动地管理每个计算设备的不活动状态：通过解决约束优化问题来确定要置于每个非活动状态的计算设备的期望数量（和身份），所述约束优化问题描述用户指定的预期的权衡之间的权衡 准备（估计时间能够在下一次需要时激活计算设备）并节约能源; 生成将当前的无效状态集合改变为所需集合的计划; 并执行该计划。 提供了多种替代方法来量化对需求浪涌的期望响应。
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6.发明授权Social recommender system for generating dialogues based on similar prior dialogues from a group of users 有权用于基于来自一组用户的类似的先前对话产生对话的社会推荐系统公开(公告)号：US08275384B2
公开(公告)日：2012-09-25
申请号：US12728205
申请日：2010-03-20
IPC分类号： H04W72/00
CPC分类号： G06Q30/02
摘要： Techniques for organizing information in a user-interactive system based on user interest are provided. In one aspect, a method for operating a system having a plurality of resources through which a user can navigate is provided. The method includes the following steps. When the user accesses the system, the resources are presented to the user in a particular order. Interests of the user in the resources presented are determined. The interests of the user are compared to interests of other users to find one or more subsets of users to which the user belongs by virtue of having similar interests. Upon one or more subsequent accesses to the system by the user, the order in which the resources are presented to the user is based on interests common to the one or more subsets of users to which the user belongs.
摘要翻译： 提供了基于用户兴趣在用户交互系统中组织信息的技术。 一方面，提供了一种用于操作具有用户可以浏览的多个资源的系统的方法。 该方法包括以下步骤。 当用户访问系统时，资源以特定顺序呈现给用户。 确定用户在所呈现的资源中的兴趣。 将用户的兴趣与其他用户的兴趣进行比较，以通过具有相似的兴趣来找到用户所属的一个或多个用户子集。 在用户对系统的一个或多个后续访问之后，将资源呈现给用户的顺序是基于用户所属的一个或多个用户子集所共有的兴趣。
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7.发明授权Method and apparatus for improved reward-based learning using nonlinear dimensionality reduction 失效使用非线性维数降低改进奖励学习的方法和装置公开(公告)号：US08060454B2
公开(公告)日：2011-11-15
申请号：US11870698
申请日：2007-10-11
IPC分类号： G06F15/18
CPC分类号： G09B19/18
摘要： The present invention is a method and an apparatus for reward-based learning of management policies. In one embodiment, a method for reward-based learning includes receiving a set of one or more exemplars, where at least two of the exemplars comprise a (state, action) pair for a system, and at least one of the exemplars includes an immediate reward responsive to a (state, action) pair. A distance measure between pairs of exemplars is used to compute a Non-Linear Dimensionality Reduction (NLDR) mapping of (state, action) pairs into a lower-dimensional representation, thereby producing embedded exemplars, wherein one or more parameters of the NLDR are tuned to minimize a cross-validation Bellman error on a holdout set taken from the set of one or more exemplars. The mapping is then applied to the set of exemplars, and reward-based learning is applied to the embedded exemplars to obtain a learned management policy.
摘要翻译： 本发明是用于管理策略的奖励学习的方法和装置。 在一个实施例中，用于基于奖励的学习的方法包括接收一组一个或多个示例，其中至少两个示例包括用于系统的（状态，动作）对，并且所述示例中的至少一个包括立即 响应（状态，动作）对的奖励。 使用示范对之间的距离测量来计算（状态，动作）对的非线性尺寸减小（NLDR）映射到较低维表示，从而产生嵌入的样本，其中NLDR的一个或多个参数被调谐 以最小化从一组或多个样本组中获取的保持集上的交叉验证Bellman错误。 然后将该映射应用于一组示例，并且基于奖励的学习被应用于嵌入的示例以获得学习的管理策略。
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8.发明授权Dynamic online multi-parameter optimization system and method for autonomic computing systems 失效动态在线多参数优化系统和自主计算系统的方法公开(公告)号：US08032615B2
公开(公告)日：2011-10-04
申请号：US12126291
申请日：2008-05-23
IPC分类号： G06F15/177
CPC分类号： G06F11/3447 , G06F11/3409 , G06F11/3452 , G06F2201/81 , G06F2201/86
摘要： A method and system performs dynamic online multi-parameter optimization for autonomic computing systems. A simplex is maintained. The system's performance is measured for the particular setting of configuration parameters associated with each point in the simplex. A new sample point is determined using the geometric transformations of the simplex. A current best point in the simplex can be resampled to determine if the environment has changed. If a sufficiently different utility value is obtained from a previously sampled utility value for the point in the simplex, the simplex is expanded. If the difference is not sufficient enough, then contraction of the simplex is performed.
摘要翻译： 一种方法和系统对自主计算系统进行动态在线多参数优化。 保持简单。 系统的性能是针对单纯形中与每个点相关联的配置参数的特定设置进行测量的。 使用单纯形的几何变换确定新的采样点。 可以对单纯形中的当前最佳点进行重新采样，以确定环境是否已更改。 如果从单纯形中的点的先前采样的效用值获得足够不同的效用值，则单纯形将被扩展。 如果差异不够，则进行单纯形状的收缩。
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9.发明申请METHOD AND APPARATUS FOR REWARD-BASED LEARNING OF IMPROVED SYSTEMS MANAGEMENT POLICIES 失效改进的系统管理政策的基于学习的方法和装置公开(公告)号：US20090012922A1
公开(公告)日：2009-01-08
申请号：US12165144
申请日：2008-06-30
IPC分类号： G06F15/18
CPC分类号： G06Q10/06
摘要： In one embodiment, the present invention is a method for reward-based learning of improved systems management policies. One embodiment of the inventive method involves supplying a first policy and a reward mechanism. The first policy maps states of at least one component of a data processing system to selected management actions, while the reward mechanism generates numerical measures of value responsive to particular actions (e.g., management actions) performed in particular states of the component(s). The first policy and the reward mechanism are applied to the component(s), and results achieved through this application (e.g., observations of corresponding states, actions and rewards) are processed in accordance with reward-based learning to derive a second policy having improved performance relative to the first policy in at least one state of the component(s).
摘要翻译： 在一个实施例中，本发明是改进的系统管理策略的基于奖励学习的方法。 本发明方法的一个实施例涉及提供第一策略和奖励机制。 第一策略将数据处理系统的至少一个组件的状态映射到所选择的管理动作，而奖励机制响应于在组件的特定状态中执行的特定动作（例如，管理动作）生成值的数值测量。 第一个政策和奖励机制适用于组件，通过此应用程序实现的结果（例如，对应的状态，行动和奖励的观察）根据奖励学习进行处理，以得到改进的第二个策略 在组件的至少一个状态下相对于第一策略的性能。
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10.发明申请Dynamic Online Multi-Parameter Optimization System and Method for Autonomic Computing Systems 失效动态在线多参数优化系统和自动计算系统的方法公开(公告)号：US20080221858A1
公开(公告)日：2008-09-11
申请号：US12126291
申请日：2008-05-23
IPC分类号： G06F9/45
CPC分类号： G06F11/3447 , G06F11/3409 , G06F11/3452 , G06F2201/81 , G06F2201/86
摘要： An improved method and system for performing dynamic online multi-parameter optimization for autonomic computing systems are provided. With the method and system of the present invention, a simplex, i.e. a set of points in the parameter space that has been directly sampled, is maintained. The system's performance with regard to a particular utility value is measured for the particular setting of configuration parameters associated with each point in the simplex. A new sample point is determined using the geometric transformations of the simplex. The method and system provide mechanisms for limiting the size of the simplex that is generated through these geometric transformations so that the present invention may be implemented in noisy environments in which the same configuration settings may lead to different results with regard to the utility value. In addition, mechanisms are provided for resampling a current best point in the simplex to determine if the environment has changed. If a sufficiently different utility value is obtained from a previously sampled utility value for the point in the simplex, then rather than contracting, the simplex is expanded. If the difference between utility values is not sufficient enough, then contraction of the simplex is performed. In addition, in order to allow for both real and integer valued parameters in the simplex, a mechanism is provided by which invalid valued parameters that are generated by geometric transformations being performed on the simplex are mapped to a nearest valid value. Similarly, parameter values that violate constraints are mapped to values that satisfy constraints taking care that the dimensionality of the simplex is not reduced.
摘要翻译： 提供了一种用于自动计算系统执行动态在线多参数优化的改进方法和系统。 利用本发明的方法和系统，维持单纯形，即直接采样的参数空间中的一组点。 关于特定效用值的系统的性能是针对与单工中的每个点相关联的配置参数的特定设置进行测量的。 使用单纯形的几何变换确定新的采样点。 该方法和系统提供了用于限制通过这些几何变换产生的单工的尺寸的机制，使得本发明可以在噪声环境中实现，其中相同的配置设置可能导致关于效用值的不同结果。 此外，还提供了用于对单纯形中当前最佳点进行重新采样以确定环境是否已更改的机制。 如果从单纯形中的点的先前采样的效用值获得足够不同的效用值，则而不是收缩，则单纯形被扩展。 如果效用值之间的差异不足够，则单纯形的收缩被执行。 此外，为了允许单纯形中的实数和整数值参数，提供了一种机制，通过这种机制，通过在单纯形上执行的几何变换生成的无效值参数被映射到最接近的有效值。 类似地，违反约束的参数值被映射到满足约束的值，注意单纯形的维度不会减小。
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