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.

A multiprocessing system is disclosed. The system includes a multithreading microprocessor having a plurality of thread contexts (TCs), a translation lookaside buffer (TLB) shared by the plurality of TCs, and an instruction scheduler, coupled to the plurality of TCs, configured to dispatch to execution units, in a multithreaded fashion, instructions of threads executing on the plurality of TCs. The system also includes a multiprocessor operating system (OS), configured to schedule execution of the threads on the plurality of TCs, wherein a thread of the threads executing on one of the plurality of TCs is configured to update the shared TLB, and prior to updating the TLB to disable interrupts, to prevent the OS from unscheduling the TLB-updating thread from executing on the plurality of TCs, and disable the instruction scheduler from dispatching instructions from any of the plurality of TCs except from the one of the plurality of TCs on which the TLB-updating thread is executing.

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 multiprocessing system is disclosed. The system includes a multithreading microprocessor, including a plurality of thread contexts (TCs), each comprising a first control indicator for controlling whether the TC is exempt from servicing interrupt requests to an exception domain for the plurality of TCs, and a virtual processing element (VPE), comprising the exception domain, configured to receive the interrupt requests, wherein the interrupt requests are non-specific to the plurality of TCs, wherein the VPE is configured to select a non-exempt one of the plurality of TCs to service each of the interrupt requests, the VPE further comprising a second control indicator for controlling whether the VPE is enabled to select one of the plurality of TCs to service the interrupt requests. The system also includes a multiprocessor operating system (OS), configured to initially set the second control indicator to enable the VPE to service the interrupts, and further configured to schedule execution of threads on the plurality of TCs, wherein each of the threads is configured to individually disable itself from servicing the interrupts by setting the first control indicator, rather than by clearing the second control indicator.

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.

A data processing node includes a management environment, an application environment, and a shared memory segment (SMS). The management environment includes at least one management services daemon (MSD) running on one or more dedicated management processors thereof. One or more application protocols are executed by the at least one MSD on at least one of the dedicated management processors. The management environment has a management interface daemon (MID) running on one or more application central processing unit (CPU) processors thereof. The SMS is accessible by the at least one MSD and the MID for enabling communication of information of the one or more application protocols to be provided between the at least one MSD and the MID. The MID provides at least one of management service to processes running within the application environment and local resource access to one or more processes running on another data processing node.

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.

According to one embodiment of the present invention, there is provided a data center comprising: a plurality of data center sections, each section having a different predefined level of reliability; and a plurality of sets of applications, each set of applications being populated on one of the plurality of data center sections.

A method and apparatus for estimating virtual machine energy consumption, and in particular, a method and apparatus for estimating virtual machine energy consumption in a computer system. The method includes: obtaining system energy consumption of the system hardware resources; obtaining event information of a plurality of functional units into which the system hardware resources are divided, and mapping the event information to the respective virtual machines; and calculating energy consumption of the virtual machines according to a plurality of energy consumption coefficients corresponding to the plurality of functional units and according to the event information mapped to the functional units of the respective virtual machines.

A method of implementing virtualization involves an improved approach to resource management. A virtualizing subsystem is capable of creating separate environments that logically isolate applications from each other. Some of the separate environments share physical resources including physical memory. When a separate environment is configured, properties for the separate environment are defined. Configuring a separate environment may include specifying a physical memory usage cap for the separate environment. A global resource capping background service enforces physical memory caps on any separate environments that have specified physical memory caps.

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.

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 and mobile terminal for determining a power efficiency of an application installed in and executed by a mobile terminal. The method includes: determining power consumption per unit time according to units of the installed and executed application; and determining a power efficiency level of the installed and executed application based on the determined power consumption per unit time. The mobile terminal includes: a power consumption determiner configured to determine power consumption per unit time according to units of the installed and executed application; and a level determiner configured to determine a power efficiency level of the installed and executed application based on the determined power consumption per unit time.

Systems and methods are disclosed for determining a current machine state of a processing device, predicting a future processing task to be performed by the processing device at a future time, and predicting a list of intervening processing tasks to be performed by a first time (e.g. a current time) and the start of the future processing task. The future processing task has an associated initial state. A feed-forward thermal prediction model determines a predicted future machine state at the time for starting the future processing task. Heat mitigation processes can be applied in advance of the starting of the future processing task, to meet the future initial machine state for starting the future processing task.

A method for managing resource allocation in a hierarchical quota system, comprising n layers of quota nodes, n being a positive integer greater than 1, and comprises at a first quota node in an ith layer of quota nodes, in response to receiving a resource allocation request from a user, determining whether an amount of requested resources exceeds a first quota; if the amount of requested resources does not exceed the first quota, determining whether the first node holds a quota delegation for the first quota node; if the first node holds the quota delegation, determining whether the amount of requested resources exceeds a second quota specified by the quota delegation for the first quota node; if the amount of requested resources does not exceed the second quota, allocating the requested resources to the user.

A processor includes an instruction schedule and dispatch (schedule / dispatch) unit to receive a single instruction multiple data (SIMD) instruction to perform an operation on multiple data elements stored in a storage location indicated by a first source operand. The instruction schedule / dispatch unit is to determine a first of the data elements that will not be operated to generate a result written to a destination operand based on a second source operand. The processor further includes multiple processing elements coupled to the instruction schedule / dispatch unit to process the data elements of the SIMD instruction in a vector manner, and a power management unit coupled to the instruction schedule / dispatch unit to reduce power consumption of a first of the processing elements configured to process the first data element.

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.

An apparatus and system for throttling I / O devices in a computer system is provided. In an example, a method for throttling device power demand during critical power events. The method includes detecting a critical power event and issuing a signal to system devices to defer optional transactions during the critical power event.

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.

A relay user equipment (UE) executes a capability discovery method. The relay UE receives a trigger for delivery of a UE capability message. The relay UE reports UE capabilities of the relay UE by transmitting the UE capabilities in the UE capability message in response to the trigger to the request source. The UE capability message may comprise information to address at least network slicing or advanced power saving. For example, the UE capability message may comprise a field for accommodating network controlled power saving capability which reflects whether a power saving state of the relay UE is network controllable.

Systems, apparatuses, and methods for performing temperature-aware task scheduling and proactive power management. A SoC includes a plurality of processing units and a task queue storing pending tasks. The SoC calculates a thermal metric for each pending task to predict an amount of heat the pending task will generate. The SoC also determines a thermal gradient for each processing unit to predict a rate at which the processing unit's temperature will change when executing a task. The SoC also monitors a thermal margin of how far each processing unit is from reaching its thermal limit. The SoC minimizes non-uniform heat generation on the SoC by scheduling pending tasks from the task queue to the processing units based on the thermal metrics for the pending tasks, the thermal gradients of each processing unit, and the thermal margin available on each processing unit.