초록 ▼

A system, method and computer readable medium are disclosed for reducing power consumption in clusters, grids, on-demand centers, and so forth. The principles disclosed herein can reduce both direct and indirect power consumption while maintaining either full cluster performance or adequate SLA base

A system, method and computer readable medium are disclosed for reducing power consumption in clusters, grids, on-demand centers, and so forth. The principles disclosed herein can reduce both direct and indirect power consumption while maintaining either full cluster performance or adequate SLA based cluster performance. The method includes receiving at least one state data point regarding power consumption or temperature of at least one resource within the compute environment. Using intelligent policies to control power consumption, the method implements and interfaces with power managements facilities within the cluster, grid or on-demand center to either implement policies, make dynamic changes, make predictions or actions, and so forth to reduce one or more of the direct or indirect power consumption associated with a compute environment. The method can analyze current workload, future workload or both in taking energy saving actions in the environment. An aspect can also involve reporting state information and updating algorithms based on historical experience or outside sources of information such as the news or weather.

대표청구항 ▼

1. A method comprising: receiving data about a current state of a compute environment, wherein the compute environment comprises a plurality of nodes under common management in which a workload manager schedules and distributes workload among the plurality of nodes and wherein each node of the plura

1. A method comprising: receiving data about a current state of a compute environment, wherein the compute environment comprises a plurality of nodes under common management in which a workload manager schedules and distributes workload among the plurality of nodes and wherein each node of the plurality of nodes is an independent computer that is networked with other nodes of the plurality of nodes in the compute environment;analyzing the workload that is currently consuming resources in the plurality of nodes in the compute environment to yield an analysis; andmodifying, based at least in part on the data and the analysis and in a manner related to energy consumption, use of at least one resource in the compute environment by migrating a reservation from a first group of compute resources in the compute environment to a second group of compute resources in the compute environment to yield a second reservation of the second group of resources. 2. The method of claim 1, wherein modifying at least one resource comprises placing at least one node of the plurality of nodes in a low power starting mode. 3. The method of claim 1, wherein the data is at least one of a temperature and power consumption. 4. The method of claim 1, further comprising: analyzing future workload that will be consumed in the compute environment, to yield a second analysis wherein modifying the at least one resource in the compute environment is based on the data and the analysis of the current workload and the second analysis. 5. The method of claim 1, wherein the at least one resource is a node or memory. 6. The method of claim 1, wherein the at least one resource relates to a cooling facility. 7. The method of claim 1, further comprising modifying the use of at least one resource by powering on or off the at least one resource. 8. A method of managing power consumption, the method comprising: receiving a current state of a compute environment, wherein the compute environment comprises a plurality of nodes under common management in which a workload manager schedules and distributes workload among the plurality of nodes and wherein each node of the plurality of nodes is an independent computer that is networked with other nodes of the plurality of nodes in the compute environment;analyzing workload to be consumed in the compute environment to yield an analysis;predicting at least one power consumption saving action based on the current state and the analysis; andimplementing, based on the predicting, a predicted at least one power consumption saving action in the compute environment, wherein the power consumption saving action comprises migrating a first reservation of first compute resources in the compute environment to yield a second reservation of second compute resources in the compute environment. 9. The method of claim 8, wherein the at least one power consumption saving action is at least one of: powering down a node, powering down memory, spinning down a disk, lowering a clock speed of a processor, powering down a hard drive, and placing a resource in a low power consumption mode. 10. The method of claim 8, further comprising: analyzing the compute environment and workload as the workload consumes resources in the compute environment to yield a second analysis; andadjusting the predicted at least one power consumption saving action based on the second analysis. 11. The method of claim 10, wherein the adjusting further comprises one of: (1) increasing or decreasing a number of powered down nodes from an implemented amount; or(2) increasing or decreasing an amount of powered down memory from an implemented amount. 12. A method of managing power consumption, the method comprising: receiving a current power consumption state of a compute environment, wherein the compute environment comprises a plurality of nodes under common management in which a workload manager schedules and distributes workload among the plurality of nodes and wherein each node of the plurality of nodes is an independent computer that is networked with other nodes of the plurality of nodes in the compute environment;analyzing queued jobs scheduled to consume resources in the compute environment to yield an analysis;predicting, based on the analysis, power consumption when at least one of the queued jobs is consumed in the compute environment; andconsuming the at least one job in the compute environment with at least one power consumption saving action implemented based on the predicting, wherein the power consumption saving action comprises migrating a first reservation of first compute resources in the compute environment to yield a second reservation of second compute resources in the compute environment. 13. The method of claim 12, wherein the at least one power consumption saving action is one of: job migration within the compute environment, job migration to a second compute environment, adjusting a cooling system, and adjusting power consumption of at least one resource in the compute environment. 14. The method of claim 12, wherein the at least one power consumption saving action relates to modifying use of a cooling facility associated with the compute environment. 15. The method of claim 14, wherein modifying the cooling facility includes pre-cooling resources in the compute environment prior to consuming the at least one job. 16. The method of claim 12, wherein the at least one power consumption saving action is modifying a data prestaging reservation.