US 11,989,797 B2
Cloud-client rendering method based on adaptive virtualized rendering pipeline
Hujun Bao, Hangzhou (CN); Rui Wang, Hangzhou (CN); and Weiju Lan, Hangzhou (CN)
Assigned to ZHEJIANG UNIVERSITY, Hangzhou (CN)
Appl. No. 17/627,677
Filed by ZHEJIANG UNIVERSITY, Hangzhou (CN)
PCT Filed Jan. 6, 2021, PCT No. PCT/CN2021/070527
§ 371(c)(1), (2) Date Jan. 16, 2022,
PCT Pub. No. WO2021/179780, PCT Pub. Date Sep. 16, 2021.
Claims priority of application No. 202010166658.5 (CN), filed on Mar. 11, 2020.
Prior Publication US 2022/0261946 A1, Aug. 18, 2022
Int. Cl. G06T 1/20 (2006.01); H04L 67/10 (2022.01)
CPC G06T 1/20 (2013.01) [H04L 67/10 (2013.01)] 10 Claims
OG exemplary drawing
 
1. A cloud-client rendering computing method based on an adaptive virtualized rendering pipeline, comprising the following steps of:
defining a rendering pipeline with an explicit representation manner for a resource, comprising defining a rendering resource, a rendering algorithm, and a read-write relationship between the rendering algorithm and the rendering resource, wherein the rendering resource comprises an input scene, a middle computing result, and a final screen resource, and each rendering pipeline comprises at least one set of a plurality of rendering algorithms jointly acting on one same rendering resource;
selecting an optimal cloud-client computing distribution solution in a real-time manner from a cloud-client computing distribution solution set comprising each rendering resource that is allocated to a cloud or client for computing, based on a framework user's six self-defined optimization objectives comprised of quality, energy consumption, performance, delay, bandwidth and space, and budget of the optimization objectives; and
executing a corresponding rendering algorithm on cloud and/or on a client according to the cloud-client computing distribution solution, thereby obtaining a rendering result;
wherein the selecting an optimal cloud-client computing distribution solution in a real-time manner from a cloud-client computing distribution solution set comprising each rendering resource that is allocated to a cloud or client for computing comprises: enumeratively selecting whether to perform on-cloud computing for each rendering resource represented by a rendering pipeline, wherein a distribution of whether all rendering resources are computed on cloud forms a cloud-client computing distribution solution, thereby composing a cloud-client computing distribution solution set; removing an invalid cloud-client computing distribution solution from the cloud-client computing distribution solution set according to a read-write relationship between the rendering algorithm and the rendering resource; selecting all configurations satisfying Pareto Optimality according to the optimization objectives from a remaining cloud-client computing distribution solution, thereby obtaining a series of superior cloud-client computing distribution solutions; and upon operation, selecting one optimal cloud-client computing distribution solution from the series of superior cloud-client distribution solutions according to an operation budget.