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    • 24. 发明授权
    • Junction manager program object interconnection and method
    • 连接管理程序对象互连和方法
    • US06587889B1
    • 2003-07-01
    • US08543969
    • 1995-10-17
    • David L. Kaminsky
    • David L. Kaminsky
    • G06F954
    • G06F9/544G06F9/465G06F9/52
    • The junction manager in the present invention eliminates the need for a separate request broker or manager and eliminates, as well, the need for each junction to propagate each state change. Instead, the state change of each object to be interconnected is reported once by the junction manager function process either located in or used by each object desiring to do so, to a shared memory space. “Processes” in each object's junction manager (we use the term process to represent processes, threads or objects themselves) which are thus logically connected or “joined”, and which may depend on one another, then query the shared memory space to obtain information about the state of a junction with another object that is of interest to them.
    • 本发明中的连接管理器消除了对单独的请求代理或管理器的需要,并且消除了每个连接点传播每个状态改变的需要。 相反,要连接的每个对象的状态更改由连接管理器功能进程报告一次,位于或由希望这样做的每个对象使用,或共享内存空间使用。 每个对象的连接管理器中的“进程”(我们使用术语过程来表示进程,线程或对象本身),这些逻辑上连接或“连接”,并且可能依赖于彼此,然后查询共享内存空间以获取信息 关于与他们感兴趣的另一个对象的交界的状态。
    • 25. 发明授权
    • Automated cloud workload management in a map-reduce environment
    • 在减少地图的环境中自动化云工作负载管理
    • US08839260B2
    • 2014-09-16
    • US13434768
    • 2012-03-29
    • Ronald P. DoyleDavid L. Kaminsky
    • Ronald P. DoyleDavid L. Kaminsky
    • G06F9/46
    • H04L67/1008G06F9/5044G06F9/5072H04L67/322
    • A computing device associated with a cloud computing environment identifies a first worker cloud computing device from a group of worker cloud computing devices with available resources sufficient to meet required resources for a highest-priority task associated with a computing job including a group of prioritized tasks. A determination is made as to whether an ownership conflict would result from an assignment of the highest-priority task to the first worker cloud computing device based upon ownership information associated with the computing job and ownership information associated with at least one other task assigned to the first worker cloud computing device. The highest-priority task is assigned to the first worker cloud computing device in response to determining that the ownership conflict would not result from the assignment of the highest-priority task to the first worker cloud computing device.
    • 与云计算环境相关联的计算设备使用足够的资源来满足来自一组工作者云计算设备的第一工作者云计算设备,以满足与包括一组优先化任务的计算作业相关联的最高优先级任务所需的资源。 确定基于与计算作业相关联的所有权信息和与分配给第一工作者云计算设备的至少一个其他任务相关联的所有权信息将最高优先级任务分配给第一工作者云计算设备是否产生所有权冲突 第一个工作者云计算设备。 响应于确定所述权限冲突不会由最高优先级任务分配给第一工作者云计算设备而将最高优先级任务分配给第一工作者云计算设备。
    • 27. 发明授权
    • Energy-efficient server location determination
    • 节能服务器位置确定
    • US08522056B2
    • 2013-08-27
    • US13526785
    • 2012-06-19
    • Seraphin B. CaloDavid L. KaminskyDinesh C. VermaXiping Wang
    • Seraphin B. CaloDavid L. KaminskyDinesh C. VermaXiping Wang
    • G06F1/00
    • G06F1/22H05K7/20836
    • A heat potential value for each of a set of available server locations is calculated via a data center controller based upon at least one active server in a data center. A minimal calculated heat potential value for the set of available server locations is identified. An available server location associated with the identified minimal calculated heat potential value is selected from the set of available server locations. A maximal calculated heat potential value is identified for the set of available server locations. An available server location associated with the identified maximal calculated heat potential value is selected from the set of available server locations. A server located at the selected available server location associated with the identified maximal calculated heat potential value is automatically de-energized.
    • 基于数据中心中的至少一个活动服务器,经由数据中心控制器计算一组可用服务器位置中的每一个的热势值。 识别可用服务器位置集合的最小计算热势值。 从可用服务器位置的集合中选择与所识别的最小计算热电势值相关联的可用服务器位置。 为可用服务器位置集合确定最大计算的热势值。 从可用服务器位置的集合中选择与所识别的最大计算热电势值相关联的可用服务器位置。 位于与所识别的最大计算热电势值相关联的所选择的可用服务器位置处的服务器被自动断电。
    • 28. 发明授权
    • Policy-based program optimization to minimize environmental impact of software execution
    • 基于策略的程序优化,以最大限度地减少软件执行的环境影响
    • US08495605B2
    • 2013-07-23
    • US12140045
    • 2008-06-16
    • Neeraj JoshiDavid L. Kaminsky
    • Neeraj JoshiDavid L. Kaminsky
    • G06F9/45G06F1/32G06F11/30
    • G06F8/443G06F11/3612
    • A method for policy-based program optimization of existing software code is performed where the code is segmented into code modules. The optimization is based on a performance policy that defines a target characteristic and a sacrificial characteristic relating to the existing software code and further defines an allowable degradation of the sacrificial characteristic resulting from optimization of the target characteristic. This method may include identifying code modules that contribute to suboptimal performance of the software code with respect to the target characteristic; identifying code transformations that increase performance of the suboptimal code modules with respect to the target characteristic; and optimizing the identified code modules by selectively applying the code transformations in accordance with the performance policy to increase performance of the software code with respect to the target characteristic.
    • 执行现有软件代码的基于策略的程序优化的方法,其中代码被分割成代码模块。 优化基于定义与现有软件代码相关的目标特性和牺牲特性的性能策略,并进一步限定由目标特性的优化产生的牺牲特性的容许劣化。 该方法可以包括识别有助于相对于目标特性的软件代码的次优性能的代码模块; 识别相对于目标特征提高次优代码模块的性能的代码转换; 以及通过根据性能策略选择性地应用代码转换来优化所识别的代码模块,以增加相对于目标特性的软件代码的性能。
    • 30. 发明申请
    • OPTIMIZED RESOURCE MANAGEMENT FOR MAP/REDUCE COMPUTING
    • 优化地图/减少计算资源管理
    • US20120215920A1
    • 2012-08-23
    • US13406873
    • 2012-02-28
    • Ronald P. DoyleDavid L. Kaminsky
    • Ronald P. DoyleDavid L. Kaminsky
    • G06F15/173
    • G06F9/5066H04L41/0813H04L41/0896
    • The present invention includes a method for resource optimization of map/reduce computing in a computing cluster. The method can include receiving a computational problem for processing in a map/reduce module, subdividing the computational problem into a set of sub-problems and mapping a selection of the sub-problems in the set to respective nodes in a computing cluster, for example a cloud computing cluster, computing for a subset of the nodes in the computing cluster a required resource capacity of the subset of the nodes to process a mapped one of the sub-problems and an existing capacity of the subset of the nodes, and augmenting the existing capacity to an augmented capacity when the required resource capacity exceeds the existing capacity, and when a cost of augmenting the existing capacity to the augmented capacity does not exceed a penalty for breaching a service level agreement (SLA) for the subset of the nodes.
    • 本发明包括用于计算集群中的映射/减少计算的资源优化的方法。 该方法可以包括在地图/缩小模块中接收用于处理的计算问题,将计算问题细分为一组子问题,并将集合中的子问题的选择映射到计算集群中的相应节点,例如 云计算集群,计算群集中节点子集的一部分,节点子集的所需资源容量,以处理映射的一个子问题和节点子集的现有容量,并增加 当所需资源容量超过现有容量时,增加容量的现有容量,以及当增加容量的现有容量的成本不超过违反节点子集的服务级别协议(SLA)的惩罚。