Apparatus and method for efficient scheduling of tasks

• US 9,135,063 B1
• Filed: 03/11/2013
• Issued: 09/15/2015
• Est. Priority Date: 07/21/2009
• Status: Active Grant

• Current Assignee: The Research Foundation for The State University of New York (State University of New York)
• Original Assignee: The Research Foundation for The State University of New York (State University of New York)
• Inventors: Ghose, Kanad
• Primary Examiner(s): PHAN, RAYMOND NGAN
• Application Number:
  US13/792,546
• Time in Patent Office: 918 Days
• Field of Search: 713300-340
• US Class Current: 1/1
• CPC Class Codes: A61K 36/185 Magnoliopsida (dicotyledons)
• CPC Class Codes: B03B 1/00 Conditioning for facilitating separation by altering physical properties of the matter to be treated
• CPC Class Codes: B03B 11/00 Feed or discharge devices integral with washing or wet-separating equipment
• CPC Class Codes: B03B 5/02 using shaken, pulsated or stirred beds as the principal means of separation B03B5/28, B03B5/48 take precedence
• CPC Class Codes: B03B 5/58 Bowl classifiers
• CPC Class Codes: G05D 23/19 characterised by the use of electric means G05D23/1393 takes precedence
• CPC Class Codes: G06F 1/20 Cooling means
• CPC Class Codes: G06F 1/206 comprising thermal management
• CPC Class Codes: G06F 1/3203 Power management, i.e. event-based initiation of a power-saving mode
• CPC Class Codes: G06F 1/3206 Monitoring of events, devices or parameters that trigger a change in power modality
• CPC Class Codes: G06F 1/3209 Monitoring remote activity, e.g. over telephone lines or network connections
• CPC Class Codes: G06F 1/3228 Monitoring task completion, e.g. by use of idle timers, stop commands or wait commands
• CPC Class Codes: G06F 13/409 Mechanical coupling back panels H05K7/1438
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06F 9/4893 taking into account power or heat criteria power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206
• CPC Class Codes: G06F 9/5094 where the allocation takes into account power or heat criteria power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206
• CPC Class Codes: G06K 19/0723 the record carrier comprising an arrangement for non-contact communication, e.g. wireless communication circuits on transponder cards, non-contact smart cards or RFIDs
• CPC Class Codes: G06K 19/07705 the visual interface being a single light or small number of lights capable of being switched on or off, e.g. a series of LEDs
• CPC Class Codes: G06K 19/07722 the record carrier being multilayered, e.g. laminated sheets flat articles in general, see B32B37/00
• CPC Class Codes: H04L 69/329 : in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 : Network security protocols
• CPC Class Codes: H05K 7/20836 : Thermal management, e.g. server temperature control
• CPC Class Codes: Y02D 10/00 : Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

A system and method of scheduling tasks, comprising receiving activity and performance data from registers or storage locations maintained by hardware and an operating system; storing calibration coefficients associated with the activity and performance data; computing an energy dissipation rate based on at least the activity and performance data; and scheduling tasks under the operating system based on the computed energy dissipation rate.

Claims

1. A method of scheduling tasks, comprising:

receiving data conveying information relating to a plurality of prospective tasks in a processing queue;

computing, with at least one automated processor, estimates of prospective energy dissipation over time for executing a load comprising the plurality of tasks, based on at least the received data and predetermined calibration parameters for associating respective tasks with a related energy dissipation over time; and

selectively scheduling the plurality of prospective tasks for processing by at least one resource which each has a respective temperature determined by different factors, based on at least the computed estimate of energy dissipation affected by the scheduled tasks, and at least a predicted load-dependent temperature associated with each at least one resource over time.

2. The method of claim 1, wherein the scheduling of the plurality of prospective tasks is further dependent on a predicted system load and the plurality of prospective tasks are distributed unevenly to the at least one resource.

3. The method of claim 1, wherein the scheduling of the plurality of prospective tasks is dependent on a predicted load-dependent temperature associated with each of at least two resources over time.

4. The method of claim 1, wherein the scheduling of the plurality of prospective tasks is based on at least the computed estimate of energy dissipation affected by the scheduled tasks, a predicted system load, and a predicted load-dependent temperature associated with each at least two resources over time.

5. The method of claim 1, further comprising coordinating a control of a dynamically controllable cooling system with the scheduling, the dynamically controllable cooling system being effective for varying a relationship between an aggregate energy dissipation over time and temperature of the at least one resource.

6. The method of claim 1, wherein the scheduling comprises reordering a plurality of elements in the processing queue.

7. The method of claim 1, further comprising selectively scheduling the plurality of prospective tasks for processing by at least one resource to meet at least one service guaranty.

8. The method of claim 1, further comprising recruiting at least one inactive resource to become available for executing tasks in dependence on a predicted temperature associated with at least one other resource, such that the predicted load dependent temperature associated with the at least one other resource does not exceed a maximum operating temperature.

9. An apparatus for scheduling tasks, comprising:

a processing queue configured to receive data conveying information relating to a plurality of prospective tasks;

at least one automated processor, configured to compute estimates of prospective energy dissipation over time for executing a load comprising the plurality of tasks based on at least the received data and predetermined calibration parameters for associating respective tasks with a related energy dissipation over time; and

a scheduler configured to schedule the plurality of prospective tasks for processing by at least one resource having a respective temperature determined by different factors, based on the computed estimate of energy dissipation affected by the scheduled tasks, and a predicted load-dependent temperature associated with each of the at least one resource over time.

10. The apparatus of claim 9, wherein the scheduler is configured to schedule the plurality of prospective tasks in dependence on at least a predicted system load, such that the plurality of prospective tasks are distributed unevenly to the at least one resource.

11. The apparatus of claim 9, wherein the scheduler is configured to schedule the plurality of prospective tasks in dependence on a predicted load-dependent temperature associated with each of at least two resources over time.

12. The apparatus of claim 9, wherein the scheduler is configured to schedule the plurality of prospective tasks in dependence on at least the computed estimate of energy dissipation affected by the scheduled tasks, a predicted system load, and a predicted load-dependent temperature associated with each of at least two resources over time.

13. The apparatus of claim 9, further comprising a control for dynamically controlling a cooling system, configured to coordinate operation of the dynamically controllable cooling system with the schedule of the plurality of tasks, and thereby selectively influence both an allocation of the plurality of prospective tasks to a respective at least one resource and a cooling of the respective at least one resource.

14. The apparatus of claim 9, wherein each respective task has a classification based on of a plurality of different classifications based on usage characteristics of the at least one resource, and the scheduler is configured to selectively schedule respective tasks having the same classification back to back.

15. The apparatus of claim 9, wherein the scheduler is further configured to selectively schedule the plurality of prospective tasks for processing by at least one resource to meet at least one service guaranty.

16. The apparatus of claim 9, further comprising at least one inactive resource, the scheduler being further configured to activate the at least one inactive resource to become available for executing tasks in dependence on a predicted temperature associated with at least one active resource, such that the predicted load dependent temperature associated with the at least one active resource does not exceed a maximum operating temperature.

17. A method of scheduling tasks, comprising:

maintaining a queue of tasks to be prospectively processed by a system having at least two processing resources;

estimating an energy dissipation over time for processing the respective tasks in the queue based on previous energy dissipation for corresponding tasks; and

reordering tasks in the queue of tasks for selective dispatch to each of the at least two processing resources, based on at least the estimated energy dissipation over time affected by the scheduled tasks, and a predicted load-dependent temperature associated with each resource over time.

18. The method of claim 17, wherein the allocating is further dependent on a predicted system load and at least one quality of service constraint.

19. The method of claim 17, further comprising coordinating a control of a dynamically controllable cooling system with the allocating, the dynamically controllable cooling system being effective for varying a relationship between an aggregate energy dissipation over time and temperature of the at least one resource.

20. The method of claim 17, further comprising activating at least one additional resource to process tasks in dependence on at least the estimated energy dissipation over time affected by the scheduled tasks, such that the predicted load dependent temperature associated with the at least two active resources does not exceed a respective maximum operating temperature.

21. The method of claim 17, wherein each respective task has a classification based on of a plurality of different classifications based on usage characteristics of the at least one resource, and the reordering of tasks in the queue of tasks for dispatch comprises reordering the tasks for dispatch to each least two alternate resources the scheduler to selectively schedule respective tasks having the same classification back to back on the same respective at least one resource.