Method and Devices for Data Path and Compute Hardware Optimization

• US 20150046676A1
• Filed: 08/12/2013
• Published: 02/12/2015
• Est. Priority Date: 08/12/2013
• Status: Abandoned Application

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: RABII, KHOSRO M., ARCHIBALD, FITZGERALD JOHN
• Application Number:
  US13/964,290
• Publication Number:
  US 20150046676A1
• Time in Patent Office: Days
• US Class Current: 712/28
• CPC Class Codes: G06F 2209/5019 Workload prediction
• CPC Class Codes: G06F 9/5083 Techniques for rebalancing the load in a distributed system

Abstract

Methods and devices for distributing processing capacity in a multi-processor system include monitoring a data input for a feature activity with a first processor, such as a high efficiency processor. When feature activity is detected, a feature event may be predicted and processing capacity requirement may be estimated. The sufficiency of available processing capacity of the first processor to meet the estimated future processing capacity requirement and process the predicted feature event may be determined. Processing capacity of a second processor, such as a high performance processor, may be distributed along with the data input when the available processing capacity of the first processor are insufficient to meet the processing capacity requirement and process the predicted feature event.

Claims

1. A method of distributing processing in a multi-processor system, comprising:

processing a data input to detect a feature activity with a first processor, the first processor comprising a high efficiency processor;

estimating a future processing capacity requirement in response to detecting the feature activity;

determining whether available processing capacity of the first processor is sufficient to meet the estimated future processing capacity requirement; and

signaling that processing the data input on a second processor will be required in response to determining that the available processing capacity of the first processor is insufficient to meet the estimated future processing capacity requirement, the second processor comprising a high performance processor.

2. The method of claim 1, wherein the multi-processor system includes N processing units, the method further comprising:

determining whether available processing capacities of the first processor and the second processor are sufficient to meet the estimated future processing capacity requirement; and

processing the data input on one or more of the N processing units in response to determining that the available processing capacities of the first processor and the second processor are insufficient to meet the estimated future processing capacity requirement.

3. The method of claim 1, wherein signaling that processing the data input on a second processor will be required comprises:

sending a message that processing capacity of the second processor will be required in response to determining that the available processing capacity of the first processor is insufficient to meet the future processing capacity requirement; and

designating the processing capacity of the second processor to process the data input in response to sending the message.

4. The method of claim 1, wherein the data input comprises a data output from a hardware device under control of the first processor, the method further comprising taking control of the hardware device from the first processor by the second processor.

5. The method of claim 4, wherein the hardware device comprises a sensor selected from a group consisting of:

an image sensor, an infrared sensor, a light sensor, an ultrasound sensor, and an audio sensor.

6. The method of claim 1, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image frame; and

the feature activity comprises visual-feature activity associated with the image frame.

7. The method of claim 1, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image histogram associated with an image frame; and

the feature activity comprises visual-feature activity associated with the image histogram.

8. The method of claim 1, further comprising:

estimating a current processing capacity requirement based on the processing of data input by the second processor;

determining whether an available processing capacity of the first processor is sufficient to meet the estimated current processing capacity requirement; and

processing the data input on the first processor and transitioning the second processor to a low power state in response to determining that available processing capacity of the first processor is sufficient to meet the estimated current processing capacity requirement.

9. The method of claim 1, wherein the data input comprises an image frame.

10. The method of claim 9, wherein:

processing the data input to detect the feature activity comprises processing the data input to detect an object in the image frame having a likelihood of being a start of a gesture; and

estimating a future processing capacity requirement comprises estimating the future processing capacity requirement to recognize the gesture within a series of image frames.

11. The method of claim 9, wherein:

processing the data input to detect the feature activity comprises processing the data input to detect a face in the image frame; and

estimating the future processing capacity requirement comprises estimating the future processing capacity requirement to perform facial recognition on a detected face within a series of image frames.

12. The method of claim 1, wherein the data input comprises an image histogram associated with an image frame.

13. The method of claim 1, wherein the data input includes audio data.

14. The method of claim 13, wherein:

processing the data input to detect the feature activity comprises processing the data input to detect a voice signal in the audio data; and

estimating the future processing capacity requirement comprises estimating the future processing capacity requirement to perform voice recognition on the voice signal in the audio data.

15. The method of claim 1, wherein the multi-processor system comprises a system-on-chip (SoC).

16. The method of claim 1, wherein the first processor comprises a digital signal processor (DSP).

17. The method of claim 1, wherein the second processor comprises an applications processor.

18. A multi-processor system, comprising:

a first processor comprising a high efficiency processor;

a second processor comprising a high performance processor; and

a resource manager coupled to the first and second processors, wherein at least the first processor and the resource manager are configured with processor-executable instructions to perform operations comprising;

processing a data input to detect a feature activity;

estimating a future processing capacity requirement in response to detecting the feature activity;

determining whether available processing capacity of the first processor is sufficient to meet the estimated future processing capacity requirement; and

signaling that processing capacity of the second processor will be required for processing the data input, in response to determining that the available processing capacity of the first processor is insufficient to meet the estimated future processing capacity requirement.

19. The multi-processor system of claim 18, wherein the estimated future processing capacity requirement is associated with processing a feature event and wherein the second processor is configured with processor-executable instructions to perform operations comprising processing the feature event within the data input.

20. The multi-processor system of claim 18, wherein:

the second processor comprises a multi-core processor with multiple processing cores; and

the required processing capacity of the second processor comprise at least one of the multiple processing cores.

21. The multi-processor system of claim 18, wherein at least the resource manager is configured with processor-executable instructions to perform operations such that signaling that processing the data input on a second processor will be required comprises:

sending a message that processing capacity of the second processor will be required in response to determining that the available processing capacity of the first processor is insufficient to meet the future processing capacity requirement; and

designating the processing capacity of the second processor to process the data input in response to sending the message.

22. The multi-processor system of claim 18, further comprising N processing units configured with processor executable instructions to perform operations, in connection with at least the resource manager, comprising:

determining whether available processing capacities of the first processor and the second processor are sufficient to meet the estimated future processing capacity requirement; and

processing the data input on at least one of the N processing units in response to determining that the available processing capacities of the first processor and the second processor are insufficient to meet the future processing capacity requirement.

23. The multi-processor system of claim 18, wherein:

the data input comprises a data output from a hardware device under control of the first processor; and

the second processor is configured with processor-executable instructions to perform operations comprising taking control of the hardware device from the first processor.

24. The multi-processor system of claim 23, wherein the hardware device comprises a sensor selected from a group consisting of:

an image sensor, an infrared sensor, a light sensor, an ultrasound sensor, and an audio sensor.

25. The multi-processor system of claim 18, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image frame; and

the feature activity comprises visual-feature activity associated with the image frame.

26. The multi-processor system of claim 18, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image histogram associated with an image frame; and

the feature activity comprises visual-feature activity associated with the image histogram.

27. The multi-processor system of claim 18, wherein the second processor is configured with processor-executable instructions to perform operations further comprising:

estimating a current processing capacity requirement based on the processing of the data input by the second processor;

determining whether an available processing capacity of the first processor is sufficient to meet the estimated current processing capacity requirement; and

processing the data input on the first processor and transitioning the second processor to a low power state in response to determining that available processing capacity of the first processor is sufficient to meet the estimated current processing capacity requirement.

28. The multi-processor system of claim 18, wherein the data input comprises an image frame.

29. The multi-processor system of claim 18, wherein the data input comprises an image histogram associated with an image frame.

30. The multi-processor system of claim 28, wherein at least the first processor and the resource manager are configured with processor executable instructions to perform operations such that processing the data input to detect a feature activity and estimating a future processing capacity requirement comprises:

processing the data input to detect an object in the image frame having a likelihood of being a start of a gesture; and

estimating the future processing capacity requirement to recognize the gesture within a series of image frames.

31. The multi-processor system of claim 28, wherein at least the first processor and the resource manager are configured with processor executable instructions to perform operations such that processing a data input to detect a feature activity and estimating a future processing capacity requirement comprises:

processing the data input to detect a face in the image frame; and

estimating the future processing capacity requirement to perform facial recognition on a detected face within a series of image frames.

32. The multi-processor system of claim 18, wherein the data input includes audio data.

33. The multi-processor system of claim 32, wherein at least the first processor and the resource manager are configured with processor executable instructions to perform operations such that processing the data input to detect a feature activity and estimating a future processing capacity requirement comprises:

processing the data input to detect a voice signal in the audio data; and

estimating the future processing capacity requirement to perform voice recognition on the voice signal in the audio data.

34. The multi-processor system of claim 18, comprising a system-on-chip (SoC).

35. The multi-processor system of claim 18, wherein the first processor comprises a digital signal processor (DSP).

36. The multi-processor system of claim 18, wherein the second processor comprises an applications processor.

37. A multi-processor system, comprising:

a high efficiency processor configured to detect a feature activity in a data input;

a high performance processor;

means for estimating a future processing capacity requirement in response to detecting the feature activity;

means for determining whether available processing capacity of the high performance processor is sufficient to meet the estimated future processing capacity requirement; and

means for signaling that a processing capacity of the high performance processor will be required for processing the data input, in response to determining that the available processing capacity of the high efficiency processor is insufficient to meet the estimated future processing capacity requirement.

38. The multi-processor system of claim 37, wherein:

the estimated future processing capacity requirement is associated with processing a feature event; and

the high performance processor processes the feature event within the data input.

39. The multi-processor system of claim 37, wherein:

The high performance processor comprises a multi-core processor with multiple processing cores; and

the required processing capacity comprises at least one of the multiple processing cores.

40. The multi-processor system of claim 37, wherein means for signaling that processing the data input on the high performance processor will be required for processing the data input sends a message that the processing capacity of the high performance processor will be required in response to determining that the available processing capacity of the high efficiency processor is insufficient to meet the future processing capacity requirement;

and designates the processing capacity of the high performance processor to process the data input in response to sending the message.

41. The multi-processor system of claim 37, wherein:

the means for determining whether available processing capacity of the high efficiency processor further determines whether available processing capacities of the high efficiency processor and the high performance processor are sufficient to meet the estimated future processing capacity requirement; and

the multi-processor system further comprises N means for processing the data input in response to determining that the available processing capacities of the high efficiency processor and the high performance processor are insufficient to meet the future processing capacity requirement.

42. The multi-processor system of claim 37, wherein:

the data input comprises a data output from a hardware device under control of the high efficiency processor; and

the high performance processor takes control of the hardware device from the high efficiency processor.

43. The multi-processor system of claim 42, wherein the hardware device comprises a sensor selected from a group consisting of:

an image sensor, an infrared sensor, a light sensor, an ultrasound sensor, and an audio sensor.

44. The multi-processor system of claim 37, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image frame; and

the feature activity comprises visual-feature activity associated with the image frame.

45. The multi-processor system of claim 37, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image histogram associated with an image frame; and

the feature activity comprises visual-feature activity associated with the image histogram.

46. The multi-processor system of claim 37, wherein the high performance processor estimates a current processing capacity requirement based on the processing of the data input, determines whether an available processing capacity of the high efficiency processor is sufficient to meet the estimated current processing capacity requirement, and transfers the processing the data input to the high efficiency processor, and transitions to a low power state in response to determining that available processing capacity of the high efficiency processor is sufficient to meet the estimated current processing capacity requirement.

47. The multi-processor system of claim 37, wherein the data input comprises an image frame.

48. The multi-processor system of claim 37, wherein the data input comprises an image histogram associated with an image frame.

49. The multi-processor system of claim 47, wherein:

the high efficiency processor processes the data input to detect an object in the image frame having a likelihood of being a start of a gesture; and

the means for estimating a future processing capacity requirement comprises means for estimating the future processing capacity requirement to recognize the gesture within a series of image frames.

50. The multi-processor system of claim 47, wherein:

the high efficiency processor processes the data input to detect a face in the image frame; and

means for estimating a future processing capacity requirement comprises means for estimating the future processing capacity requirement to perform facial recognition on a detected face within a series of image frames.

51. The multi-processor system of claim 37, wherein the data input includes audio data.

52. The multi-processor system of claim 51, wherein

the high efficiency processor processes the data input to detect a voice signal in the audio data;

and

means for estimating a future processing capacity requirement comprises means for estimating the future processing capacity requirement to perform voice recognition on the voice signal in the audio data.

53. The multi-processor system of claim 37, comprising a system-on-chip (SoC).

54. The multi-processor system of claim 37, wherein the high efficiency processor comprises a digital signal processor (DSP).

55. The multi-processor system of claim 37, wherein the high performance processor comprises an applications processor.

56. A non-transitory computer-readable storage medium having stored thereon processor-executable software instructions configured to cause one or more processors in a multi-processor system for distributing processing to perform operations comprising:

processing a data input to detect a feature activity with a first processor, the first processor comprising a high efficiency processor;

estimating a future processing capacity requirement in response to detecting the feature activity;

determining whether available processing capacity of the first processor is sufficient to meet the estimated future processing capacity requirement; and

signaling that processing the data input on a second processor will be required in response to determining that the available processing capacity of the first processor is insufficient to meet the estimated future processing capacity requirement, the second processor comprising a high performance processor.

57. The non-transitory computer-readable storage medium of claim 56, wherein:

the multi-processor system includes N processing units; and

the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations further comprising;

determining whether available processing capacities of the first processor and the second processor are sufficient to meet the estimated future processing capacity requirement; and

processing the data input on one or more of the N processing units in response to determining that the available processing capacities of the first processor and the second processor are insufficient to meet the estimated future processing capacity requirement.

58. The non-transitory computer-readable storage medium of claim 56, wherein the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations such that signaling that processing the data input on a second processor will be required comprises:

sending a message that processing capacity of the second processor will be required in response to determining that the available processing capacity of the first processor is insufficient to meet the future processing capacity requirement; and

designating the processing capacity of the second processor to process the data input in response to sending the message.

59. The non-transitory computer-readable storage medium of claim 56, wherein:

the data input comprises a data output from a hardware device under control of the first processor; and

the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations further comprising taking control of the hardware device from the first processor by the second processor.

60. The non-transitory computer-readable storage medium of claim 59, wherein the hardware device comprises a sensor selected from a group consisting of an image sensor, an infrared sensor, a light sensor, an ultrasound sensor, and an audio sensor.

61. The non-transitory computer-readable storage medium of claim 56, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image frame; and

the feature activity comprises visual-feature activity associated with the image frame.

62. The non-transitory computer-readable storage medium of claim 56, wherein:

the multi-processor system comprises a computer vision system;

the data input comprises an image histogram associated with an image frame; and

the feature activity comprises visual-feature activity associated with the image histogram.

63. The non-transitory computer-readable storage medium of claim 56, wherein the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations further comprising:

estimating a current processing capacity requirement based on the processing of data input by the second processor;

determining whether an available processing capacity of the first processor is sufficient to meet the estimated current processing capacity requirement; and

processing the data input on the first processor and transitioning the second processor to a low power state in response to determining that available processing capacity of the first processor is sufficient to meet the estimated current processing capacity requirement.

64. The non-transitory computer-readable storage medium of claim 56, wherein the data input comprises an image frame.

65. The non-transitory computer-readable storage medium of claim 64, wherein the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations such that processing the data input to detect the feature activity and estimating a future processing capacity requirement comprises:

processing the data input to detect an object in the image frame having a likelihood of being a start of a gesture; and

estimating a future processing capacity requirement to recognize the gesture within a series of image frames.

66. The non-transitory computer-readable storage medium of claim 64, wherein the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations such that processing a data input to detect a feature activity and estimating the future processing capacity requirement comprises:

processing the data input to detect a face in the image frame; and

estimating the future processing capacity requirement to perform facial recognition on a detected face within a series of image frames.

67. The non-transitory computer-readable storage medium of claim 56, wherein the data input comprises an image histogram associated with an image frame.

68. The non-transitory computer-readable storage medium of claim 56, wherein the data input includes audio data.

69. The non-transitory computer-readable storage medium of claim 68, wherein the stored processor-executable software instructions are configured to cause the one or more processors in the multi-processor system to perform operations such that processing the data input to detect the feature activity and estimating the future processing capacity requirement comprises:

processing the data input to detect a voice signal in the audio data; and

estimating the future processing capacity requirement to perform voice recognition on the voice signal in the audio data.

70. The non-transitory computer-readable storage medium of claim 56, wherein the multi-processor system comprises a system-on-chip (SoC).

71. The non-transitory computer-readable storage medium of claim 56, wherein the first processor comprises a digital signal processor (DSP).

72. The non-transitory computer-readable storage medium of claim 56, wherein the second processor comprises an applications processor.