METHOD AND APPARATUS FOR UNIFYING GRAPHICS PROCESSING UNIT COMPUTATION LANGUAGES

• US 20130321436A1
• Filed: 06/04/2012
• Published: 12/05/2013
• Est. Priority Date: 06/04/2012
• Status: Active Grant

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Systems Incorporated (Adobe Inc.)
• Inventors: Hoeg, Steven Paterson
• Granted Patent: US 9,275,426 B2
• Time in Patent Office: Days
• US Class Current: 345/522
• CPC Class Codes: G06T 1/00 General purpose image data processing

Abstract

A method and apparatus for unifying graphics processing unit (GPU) computation languages is disclosed. The method comprises identifying a GPU of a computer system; accessing a plurality of macros representing a difference in source code between a first GPU computation language and a second GPU computation language, expanding each macro in the plurality of macros based on the identified GPU and executing a kernel on the computer system using the expanded macro.

Claims

1. A method for unifying Graphics Processing Unit (GPU) computation languages comprising:

identifying a GPU on a computing device;

accessing a plurality of macros representing a difference in source code between a first GPU computation language and a second GPU computation language;

expanding each macro in the plurality of macros based on the identified GPU; and

executing a kernel on the computing device using the expanded macro.

2. The method of claim 1 wherein the first GPU computation language and the second GPU computation language are derived from a common programming language.

3. The method of claim 1, wherein the first GPU computation language is Compute Unified Device Architecture (CUDA) and the second GPU computation language is Open Computing Language (OpenCL).

4. The method of claim 1, wherein each macro represents a difference between the first GPU computation language and the second GPU computation language.

5. The method of claim 3, wherein identifying the GPU comprises determining whether a computer hardware is CUDA-based or OpenCL-based.

6. The method of claim 1, wherein expanding the macro comprises substituting language specific code into the kernel wherein the specific code is compatible with the identified GPU.

7. The method of claim 6 wherein the kernel contains tokens where the language specific code is to be substituted.

8. A non-transient computer readable medium for storing computer instructions that, when executed by at least one processor cause the at least one processor to perform a method for unifying Graphics Processing Unit (GPU) computation languages comprising:

identifying a GPU on a computing device;

accessing a plurality of macros representing a difference in source code between a first GPU computation language and a second GPU computation language;

expanding each macro in the plurality of macros based on the identified GPU; and

executing a kernel on the computing device using the expanded macro.

9. The computer readable medium of claim 8 wherein the first GPU computation language and the second GPU computation language are derived from a common programming language.

10. The computer readable medium of claim 8, wherein the first GPU computation language is Compute Unified Device Architecture (CUDA) and the second GPU computation language is Open Computing Language (OpenCL).

11. The computer readable medium of claim 8, wherein identifying the GPU comprises determining whether a computer hardware is CUDA-based or OpenCL-based.

12. The computer readable medium of claim 8, wherein expanding the macro comprises substituting language specific code into the kernel wherein the specific code is compatible with the identified GPU.

13. The computer readable medium of claim 12, wherein the kernel contains tokens where the language specific code is to be substituted.

15. The apparatus of claim 12 wherein the first GPU computation language and the second GPU computation language are derived from a common programming language.

16. The apparatus of claim 12, wherein the first GPU computation language is Compute Unified Device Architecture (CUDA) and the second GPU computation language is Open Computing Language (OpenCL).

17. The apparatus of claim 12, wherein the kernel is configured to execute operations on one or more hardware and/or software modules.

18. The apparatus of claim 16, wherein identifying the GPU comprises determining whether a computer hardware is CUDA-based or OpenCL-based.

19. The apparatus of claim 12, wherein expanding the macro comprises substituting language specific code into the kernel wherein the specific code is compatible with the identified GPU.

20. The apparatus of claim 12, wherein the kernel contains tokens where the language specific code is to be substituted.

14. An apparatus for unifying Graphics Processing Unit (GPU) computation languages comprising:

a unifying agent for identifying a GPU on a computing device, accessing a plurality of macros representing a difference in source code between a first GPU computation language and a second GPU computation language, expanding each macro in the plurality of macros based on the identified GPU, and executing a kernel using the expanded macro.