77results about "Multiprocessor based energy comsumption reduction" patented technology

A cloud management system can determine if the operational state of the virtual machines and/or the computing systems needs to be altered in order to instantiate virtual machines. If the operational state of the computing systems needs to be altered, the cloud management system retrieves an identification of the power management systems supporting the computing systems. The cloud management system can utilize the identification of the power management systems to instruct the power management systems to alter the power state of the computing system in order to instantiate the virtual machines.

An object of the invention is to reduce the electric power consumption resulting from temporarily activating a processor requiring a large electric power consumption, out of a plurality of processors. A multiprocessor system (1) includes: a first processor (141) which executes a first instruction code; a second processor (151) which executes a second instruction code, a hypervisor (130) which converts the second instruction code into an instruction code executable by the first processor (141); and a power control circuit (170) which controls the operation of at least one of the first processor (141) and the second processor (151). When the operation of the second processor (151) is suppressed by the power control circuit (170), the hypervisor (130) converts the second instruction code into the instruction code executable by the first processor (141), and the first processor (141) executes the converted instruction code.

Embodiments that dynamically check availability of hardware resources for applications of virtual environments are contemplated. Various embodiments comprise one or more computing devices having various hardware resources available to applications of a virtual environment. Hardware resources may comprise, for example, amounts of memory, amounts or units of processing capability of one or more processors, and various types of peripheral devices. The embodiments may store hardware data pertaining to a specified amount of hardware recommended or required for an application to execute within the virtual environment. The embodiments may generally monitor for changes to the hardware configuration, which may affect amount of hardware available to the virtual environment and/or application. If the changes to the hardware reduce the amount of available hardware to a point beyond the specified amount of hardware, the embodiments may prevent the application from being executed or prevent the changes to the hardware configuration.

A data processing device assigns tasks to processor cores in a more distributed fashion. In one embodiment, the data processing device can schedule tasks for execution amongst the processor cores in a pseudo-random fashion. In another embodiment, the processor core can schedule tasks for execution amongst the processor cores based on the relative amount of historical utilization of each processor core. In either case, the effects of bias temperature instability (BTI) resulting from task execution are distributed among the processor cores in a more equal fashion than if tasks are scheduled according to a fixed order. Accordingly, the useful lifetime of the processor unit can be extended.

Disclosed is a method and apparatus for performing tile-based rendering. A sequence of tiles to be processed may be determined based on a locality among the tiles. A tile dispatch unit selects a subsequent tile to be dispatched, based on the determined sequence. The tile dispatch unit may check whether an idle fragment processor exists among the plurality of fragment processors, and may dynamically dispatch the selected tile to an idle fragment processor

Embodiments of the present invention provide a method, system and computer program product for power optimization via virtualization opportunity determination. In an embodiment of the invention, a method for power optimization via virtualization opportunity determination can be provided. The method can include monitoring power utilization in individual server hosts in a cluster and determining a set of the server hosts in the cluster demonstrating low power utilization. The method also can include selecting a subset of server hosts in the set and migrating each VM in non-selected server hosts in the set to the subset of server hosts. Finally, the method can include powering down the non-selected server hosts.

A data processor with a plurality of processor cores. Accumulated usage information of each of the plurality of processor cores is stored in a storage device within the data processor, wherein the accumulated usage information is indicative of accumulated usage of each processor core of the plurality of processor cores. The processor uses the accumulated usage information in selecting processor cores to perform processor operations.

A load distribution apparatus includes: a control unit that refers to a load information storage unit that stores load values of a plurality of information processing apparatuses, selects an information processing apparatus with the load value smaller than a predetermined threshold from the plurality of information processing apparatuses, and determines the information processing apparatus with the load value smaller than a predetermined threshold as an allocation destination of processing requests until the load value of the information processing apparatus reaches the predetermined threshold; and a transmitting unit that transmits the processing requests to the allocation destination determined by the control unit.

A method dynamically adjusts the resources available to a processing unit of a distributed computer process executing on a multi-node computer system. The resources for the processing unit are adjusted based on the data other processing units handle or the execution path of code in an upstream or downstream processing unit in the distributed process or application.

Systems and methods of monitoring, analyzing, optimizing and controlling data centers and data center operations are disclosed. The system includes data collection and storage hardware and software for harvesting operational data from data center assets and operations. Intelligent analysis and optimization software enables identification of optimization and/or control actions. Control software and hardware enables enacting a change in the operational state of data centers.

In an HPC system, a Resource Manager deliberately introduces heterogeneities to the execution speeds of some, but not all, of the nodes allocated to an application during the application's execution. These heterogeneities may cause changes to the amount of time spent waiting on coordination points: computation intensive applications will be most affected by these changes, IO bound applications less so. By monitoring wait time reports received from a Communications library, the Manager can discriminate between these two types of applications and suitable power states can be applied to the nodes allocated to the application. If the application is IO bound then nodes can be switched to a lower-power state to save energy. This can be applied at any point during application execution so that the hardware configuration can be adjusted to keep optimal efficiency as the application passes through phases with different energy use and performance characteristics.

A Resource Manager is provided for managing a plurality of computers. Each of the computers is operable in one of a plurality of power configurations, including a high-power configuration and low-power configurations. The Manager exchanges messages with a Manager Proxy in each computer. Responsive to notifications from Manager Proxies of changes in execution state of an application, the Manager determines a power configuration applicable for the computer of that Manager Proxy, or for a set of computers executing the application. The Manager indicates the power configuration to the Manager Proxy which then decides whether to implement a change.

One embodiment provides a computer-implemented method for enforcing a temperature limit of a client computer. The method includes receiving a request for computer-executable work to be executed on a client computer. If executing all of the requested work on the client computer would cause the client computer to exceed the temperature limit, a portion of the requested work may be selectively redirected to a remote computer in an amount selected to enforce the temperature limit of the client computer. Simultaneously, the remainder of the requested work may be executed on the client computer. The output of the redirected work may be communicated from the remote computer back to the client computer over a network.

A method, a system and a computer program product for controlling the hardware priority of hardware threads in a data processing system. A Thread Priority Control (TPC) utility assigns a primary level and one or more secondary levels of hardware priority to a hardware thread. When a hardware thread initiates execution in the absence of a system call, the TPC utility enables execution based on the primary level. When the hardware thread initiates execution within a system call, the TPC utility dynamically adjusts execution from the primary level to the secondary level associated with the system call. The TPC utility adjusts hardware priority levels in order to: (a) raise the hardware priority of one hardware thread relative to another; (b) reduce energy consumed by the hardware thread; and (c) fulfill requirements of time critical hardware sections.

The system and method generally relate to reducing heat dissipated within a data center, and more particularly, to a system and method for reducing heat dissipated within a data center through service level agreement analysis, and resultant reprioritization of jobs to maximize energy efficiency. A computer implemented method includes performing a service level agreement (SLA) analysis for one or more currently processing or scheduled processing jobs of a data center using a processor of a computer device. Additionally, the method includes identifying one or more candidate processing jobs for a schedule modification from amongst the one or more currently processing or scheduled processing jobs using the processor of the computer device. Further, the method includes performing the schedule modification for at least one of the one or more candidate processing jobs using the processor of the computer device.