Method, Apparatus and Computer Program Product for an Instruction Predictor for a Virtual Machine

• US 20100241600A1
• Filed: 03/20/2009
• Published: 09/23/2010
• Est. Priority Date: 03/20/2009
• Status: Abandoned Application

• Current Assignee: Nokia Corporation
• Original Assignee: Nokia Corporation
• Inventors: Krichevskiy, Andrey
• Application Number:
  US12/408,087
• Publication Number:
  US 20100241600A1
• Time in Patent Office: Days
• US Class Current: 706/21
• CPC Class Codes: G06F 9/3802 Instruction prefetching
• CPC Class Codes: G06F 9/455 Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

An apparatus for providing an instruction predictor for a virtual machine may include a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to train a neural network to predict a future instruction corresponding to a current instruction based on past instructions provided to the neural network, and provide the future instruction predicted to a virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction. A corresponding method and computer program product are also provided.

Claims

1. A method comprising:

training a neural network to predict a future instruction corresponding to a current instruction based on past instructions provided to the neural network; and

providing the future instruction predicted to a virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction.

2. A method according to claim 1, wherein training the neural network comprises:

providing the neural network with a time series of instructions corresponding to a moving first window defining a sequence of instruction values provided to the neural network at a series of times;

providing error feedback, to the neural network, comprising an output of a comparator comparing a sequence of future instruction values relative to the instruction values of the first window and within a moving second window a fixed distance from the first window to the instruction values of the first window; and

modifying a weight value of at least one node of the neural network to reduce the error feedback.

3. A method according to claim 2, wherein modifying the weight value of at least one node of the neural network comprises making modifications to the neural network until a value of the error feedback reaches at least a predetermined value.

4. A method according to claim 1, wherein training the neural network comprises training the neural network until a training criteria is satisfied and shifting to a prediction stage in response to satisfaction of the training criteria.

5. A method according to claim 1, wherein providing the future instruction comprises providing a plurality of potential future instructions for the current instruction with each potential future instruction having a corresponding probability value defining a likelihood of each respective potential future instruction occurring.

6. A method according to claim 1, wherein providing the future instruction predicted to the virtual machine comprises providing the future instruction to the virtual machine in response to a request from the virtual machine.

7. A method according to claim 1, wherein providing the future instruction predicted to the virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction comprises enabling the virtual machine to suppress an operation determined to be unlikely to be necessary based on the future instruction.

8. A computer program product comprising at least one computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instruction comprising:

program code instructions for training a neural network to predict a future instruction corresponding to a current instruction based on past instructions provided to the neural network; and

program code instructions for providing the future instruction predicted to a virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction.

9. A computer program product according to claim 8, wherein program code instructions for training the neural network include instructions for:

providing the neural network with a time series of instructions corresponding to a moving first window defining a sequence of instruction values provided to the neural network at a series of times;

providing error feedback, to the neural network, comprising an output of a comparator comparing a sequence of future instruction values relative to the instruction values of the first window and within a moving second window a fixed distance from the first window to the instruction values of the first window; and

modifying a weight value of at least one node of the neural network to reduce the error feedback.

10. A computer program product according to claim 9, wherein program code instructions for modifying the weight value of at least one node of the neural network include instructions for making modifications to the neural network until a value of the error feedback reaches at least a predetermined value.

11. A computer program product according to claim 8, wherein program code instructions for training the neural network include instructions for training the neural network until a training criteria is satisfied and shifting to a prediction stage in response to satisfaction of the training criteria.

12. A computer program product according to claim 8, wherein program code instructions for providing the future instruction include instructions for providing a plurality of potential future instructions for the current instruction with each potential future instruction having a corresponding probability value defining a likelihood of each respective potential future instruction occurring.

13. A computer program product according to claim 8, wherein program code instructions for providing the future instruction predicted to the virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction include instructions for enabling the virtual machine to suppress an operation determined to be unlikely to be necessary based on the future instruction.

14. An apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least perform the following:

training a neural network to predict a future instruction corresponding to a current instruction based on past instructions provided to the neural network; and

providing the future instruction predicted to a virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction.

15. An apparatus according to claim 14, wherein the instructions for training the neural network comprise instructions for:

providing the neural network with a time series of instructions corresponding to a moving first window defining a sequence of instruction values provided to the neural network at a series of times;

providing error feedback, to the neural network, comprising an output of a comparator comparing a sequence of future instruction values relative to the instruction values of the first window and within a moving second window a fixed distance from the first window to the instruction values of the first window; and

modifying a weight value of at least one node of the neural network to reduce the error feedback.

16. An apparatus according to claim 15, wherein the instructions for modifying the weight value of at least one node of the neural network comprise instructions for making modifications to the neural network until a value of the error feedback reaches at least a predetermined value.

17. An apparatus according to claim 14, wherein instructions for training the neural network comprise instructions for training the neural network until a training criteria is satisfied and shifting to a prediction stage in response to satisfaction of the training criteria.

18. An apparatus according to claim 14, wherein instructions for providing the future instruction comprise instructions for providing a plurality of potential future instructions for the current instruction with each potential future instruction having a corresponding probability value defining a likelihood of each respective potential future instruction occurring.

19. An apparatus according to claim 14, wherein instructions for providing the future instruction predicted to the virtual machine comprise instructions for providing the future instruction to the virtual machine in response to a request from the virtual machine.

20. An apparatus according to claim 14, wherein instructions for providing the future instruction predicted to the virtual machine to enable the virtual machine to manage operation of the virtual machine based on the future instruction comprise instructions for enabling the virtual machine to suppress an operation determined to be unlikely to be necessary based on the future instruction.