SCHEDULING APPLICATIONS IN PROCESSING DEVICES BASED ON PREDICTED THERMAL IMPACT

• US 20160085219A1
• Filed: 09/22/2014
• Published: 03/24/2016
• Est. Priority Date: 09/22/2014
• Status: Abandoned Application

• Current Assignee: Advanced Micro Devices, Inc.
• Original Assignee: Advanced Micro Devices, Inc.
• Inventors: Paul, Indrani, Arora, Manish, Eckert, Yasuko, Manne, Srilatha
• Application Number:
  US14/493,189
• Publication Number:
  US 20160085219A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 1/206 comprising thermal management
• CPC Class Codes: G06F 1/329 by task scheduling
• 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: G06N 5/04 Inference or reasoning models
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

A processing device includes a plurality of components and a system management unit to selectively schedule an application phase to one of the plurality of components based on one or more comparisons of predictions of a plurality of thermal impacts of executing the application phase on each of the plurality of components. The predictions may be generated based on a thermal history associated with the application phase, thermal sensitivities of the plurality of components, or a layout of the plurality of components in the processing device.

Claims

1. A method comprising:

selectively scheduling an application phase to one of a plurality of components of a processing device based on at least one comparison of predictions of a plurality of thermal impacts of executing the application phase on each of the plurality of components.

2. The method of claim 1, further comprising:

generating the predictions of the plurality of thermal impacts based on at least one of a thermal history associated with the application phase, thermal sensitivities of the plurality of components, and a layout of the plurality of components in the processing device.

3. The method of claim 2, wherein generating the predictions of the plurality of thermal impacts based on the thermal history associated with the application phase comprises generating the predictions of the plurality of thermal impacts based on at least one of predicted thermal rise times, predicted durations of the application phase, and predicted thermal profiles associated with the application phase for each of the plurality of components.

4. The method of claim 2, wherein generating the predictions of the plurality of thermal impacts based on the layout of the plurality of components comprises predicting the thermal impacts based on proximity of the plurality of components to heat sinks or other components.

5. The method of claim 1, further comprising:

generating the predictions of the plurality of thermal impacts based on at least one frequency of thermal emergencies associated with the plurality of components.

6. The method of claim 1, further comprising:

generating the predictions of the plurality of thermal impacts based on at least one of predicted durations of active events during the application phase, predicted durations of idle events during the application phase, and whether the application phase is compute intensive or memory bounded.

7. The method of claim 1, wherein selectively scheduling the application phase to one of the plurality of components comprises selectively scheduling the application phase to one of the plurality of components based on a thermal density map of the processing device.

8. The method of claim 7, wherein selectively scheduling the application phase comprises scheduling the application phase to a first component that is at a lower temperature than a second component.

9. A processing device comprising:

a plurality of components; and

a system management unit to selectively schedule an application phase to one of the plurality of components based on at least one comparison of predictions of a plurality of thermal impacts of executing the application phase on each of the plurality of components.

10. The processing device of claim 9, wherein the system management unit is to generate the predictions of the plurality of thermal impacts based on at least one of a thermal history associated with the application phase, thermal sensitivities of the plurality of components, and a layout of the plurality of components in the processing device.

11. The processing device of claim 10, wherein the system management unit is to generate the predictions of the plurality of thermal impacts based on at least one of predicted thermal rise times, predicted durations of the application phase, and predicted thermal profiles associated with the application phase for each of the plurality of components.

12. The processing device of claim 10, wherein the system management unit is to predict the thermal impacts based on proximity of the plurality of components to heat sinks or other components.

13. The processing device of claim 10, wherein the system management unit is to generate the predictions of the plurality of thermal impacts based on at least one frequency of thermal emergencies associated with the plurality of components.

14. The processing device of claim 10, wherein the system management unit is to generate the predictions of the plurality of thermal impacts based on at least one of predicted durations of active events during the application phase, predicted durations of idle events during the application phase, and whether the application phase is compute-intensive or memory-bounded.

15. The processing device of claim 9, wherein the system management unit is to selectively schedule the application phase to one of the plurality of components based on a thermal density map of the processing device.

16. The processing device of claim 15, wherein the system management unit is to schedule the application phase to a first component that is at a lower temperature than a second component.

17. A non-transitory computer readable storage medium embodying a set of executable instructions, the set of executable instructions to manipulate at least one processor to:

selectively schedule an application phase to one of a plurality of components of a processing device based on at least one comparison of predictions of a plurality of thermal impacts of executing the application phase on each of the plurality of components.

18. The non-transitory computer readable storage medium of claim 17, further comprising executable instructions to manipulate the at least one processor to:

generate the predictions of the plurality of thermal impacts based on at least one of a thermal history associated with the application phase, thermal sensitivities of the plurality of components, and a layout of the plurality of components in the processing device.

19. The non-transitory computer readable storage medium of claim 17, further comprising executable instructions to manipulate the at least one processor to:

generate the predictions of the plurality of thermal impacts based on at least one of a frequency of thermal emergencies, predicted durations of active events during the application phase, predicted durations of idle events during the application phase, and whether the application phase is compute-intensive or memory-bounded.

20. The non-transitory computer readable storage medium of claim 17, further comprising executable instructions to manipulate the at least one processor to:

selectively schedule the application phase to one of the plurality of components based on a thermal density map of the processing device.