Systems and methods for scalable asynchronous computing framework

• US 9,417,911 B2
• Filed: 11/10/2014
• Issued: 08/16/2016
• Est. Priority Date: 03/12/2014
• Status: Expired due to Fees

• Current Assignee: Live Planet LLC
• Original Assignee: Live Planet LLC
• Inventors: Arun, Rohan Maroly kovumal
• Primary Examiner(s): Richer, Joni
• Application Number:
  US14/537,768
• Publication Number:
  US 20150261571A1
• Time in Patent Office: 645 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 3/1438 using more than one graphics controller
• CPC Class Codes: G06F 3/1446 display composed of modules, e.g. video walls
• CPC Class Codes: G06F 3/1454 involving copying of the display data of a local workstation or window to a remote workstation or window so that an actual copy of the data is displayed simultaneously on two or more displays, e.g. teledisplay
• CPC Class Codes: G06F 9/445 Program loading or initiating bootstrapping G06F9/4401; security arrangements for program loading or initiating G06F21/57
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/5066 Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs mappping at compile time, see G06F8/451
• CPC Class Codes: G06T 1/20 Processor architectures; Processor configuration, e.g. pipelining
• CPC Class Codes: G06T 15/005 General purpose rendering architectures
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 17/10 Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
• CPC Class Codes: G06T 2200/16 involving adaptation to the client's capabilities
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2210/52 Parallel processing
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers

Abstract

Systems and methods are described for a distributed data processing method, including, but not limited to: receiving, by a backend device, source data; partitioning, by the backend device, the source data into a plurality of data threads; sending, by the backend device, at least one of the plurality of data threads to each of a plurality of user devices; and determining, by the backend device, a job outcome for the source data based on a plurality of data thread results, each of the plurality of data thread results is determined by one of the plurality of user devices based on the at least one of the plurality of data threads.

Claims

1. A method for processing data, the method comprising:

receiving, by a backend device, source data related to a target space, the target space is defined by a plurality of vertices;

partitioning, by the backend device, the source data into a plurality of data threads, each of the plurality of data threads is associated with at least one of the plurality of vertices;

sending, by the backend device, at least one of the plurality of data threads to each of a plurality of user devices;

receiving a plurality of data thread results from the plurality of user devices, each of the plurality of data thread results corresponds to at least one of the plurality of data threads, wherein each of the plurality of data thread results comprises at least one display characteristic associated with at least one of the plurality of vertices; and

determining, by the backend device, a job outcome for the source data based on the plurality of data thread results;

wherein the job outcome comprises weighting factors for display characteristics associated with each of the plurality of vertices.

2. The method of claim 1, wherein:

the source data is a captured video frame.

3. The method of claim 2, wherein:

partitioning of the source data into the plurality of data threads comprises partitioning the captured video frame into a plurality of areas based on metadata associated with the captured video frame and the plurality of areas, each of the plurality of areas corresponds to one of the plurality of data threads.

4. The method of claim 2, wherein the partitioning of the source data into the plurality of data threads comprises partitioning the source data based on pixels of the source data.

5. The method of claim 2, wherein the frame is an image of a target space.

6. The method of claim 5, wherein;

the target space comprises of a plurality of vertices; and

each of the plurality of vertices corresponds to a 3-dimensional portion of the target space.

7. The method of claim 6, wherein:

each of the plurality of data threads is associated with at least one of the plurality of vertices; and

each of the plurality of data threads corresponds to an area of the image.

8. The method of claim 7, wherein each of the data thread results is determined by determining a weighting value associated with at least one display characteristics associated with the area of the image.

9. The method of claim 8, wherein the display characteristics comprises at least a color associated with the area of the image.

10. The method of claim 6, wherein the image captures at least some of the plurality of vertices.

11. The method of claim 1, wherein determining the job outcome comprises:

receiving, by the backend device, the plurality of data thread results from the plurality of user devices; and

determining the job outcome for the data job based on the received plurality of data thread results.

12. The method of claim 1, wherein sending the at least one of the plurality of data threads comprises:

determining at least one of processing power and network conditions for each of the plurality of user devices; and

assigning each of the plurality of user devices at least one of the plurality of data threads based on at least one of the processing power and the network conditions.

13. The method of claim 1, further comprising formatting the source data into graphic processing unit (GPU)-compatible format, wherein each of the plurality of data thread results is determined by at least one GPU associated with each of the plurality of user devices.

14. The method of claim 13, wherein the GPU-compatible format is associated with shader language.

15. The method of claim 14, wherein the source data is formatted into at least one of the following elements:

geometry, vertices, textures, normals, and code for the shader language.

16. The method of claim 1, further comprising receiving, by the backend device, the plurality of data thread results after the plurality of data thread results have been rendered to the display screen associated with each of the user devices.

17. The method of claim 1, further comprising streaming the job outcome to a Content Delivery Network (CDN) in the form of depth videos.

18. An apparatus for processing data, the apparatus comprising:

a backend device, the backend device is configured to;

receive source data related to a target space, the target space is defined by a plurality of vertices;

partition the source data into a plurality of data threads, each of the plurality of data threads is associated with at least one of the plurality of vertices;

send at least one of the plurality of data threads to each of a plurality of user devices;

receive a plurality of data thread results from the plurality of user devices, each of the plurality of data thread results corresponds to at least one of the plurality of data threads, wherein each of the plurality of data thread results comprises at least one display characteristic associated with at least one of the plurality of vertices; and

determine a job outcome for the source data based on the plurality of data thread results;

wherein the job outcome comprises weighting factors for display characteristics associated with each of the plurality of vertices.

19. A non-transitory computer-readable storage medium storing program instructions that, when executed, causes a processor to:

receive source data related to a target space, the target space is defined by a plurality of vertices;

partition the source data into a plurality of data threads, each of the plurality of data threads is associated with at least one of the plurality of vertices;

send at least one of the plurality of data threads to each of a plurality of user devices;

receive a plurality of data thread results from the plurality of user devices, each of the plurality of data thread results corresponds to at least one of the plurality of data threads, wherein each of the plurality of data thread results comprises at least one display characteristic associated with at least one of the plurality of vertices; and

determine a job outcome for the source data based on a plurality of data thread results;

wherein the job outcome comprises weighting factors for display characteristics associated with each of the plurality of vertices.

20. A method for processing data by a user device, the method comprising:

receiving, from a backend device, a data thread, the thread corresponds to at least one of an image or a video frame capturing at least one of a plurality of vertices defining a target space;

determining a data thread result, the data thread result comprising at least one display determining a data thread result, the data thread result comprising at least one display characteristic associated with each of the at least one of the plurality of vertices;

sending the data thread result to the backend device;

receiving, from the backend device, a job outcome, wherein the job outcome is determined based, at least in part, on the data thread result; and

displaying a 3-dimensional projection of the target space based on the job outcome;

wherein the job outcome comprises weighting factors for display characteristics associated with each of the plurality of vertices.

21. The method of claim 20, wherein the data thread results are determined by:

rendering the data thread results to a display screen of the user devices; and

copying the data thread results rendered to the display screen.