CN112581578A - Cloud rendering system based on software definition - Google Patents
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Abstract
The cloud rendering system based on software definition comprises an application layer, a control layer, an infrastructure layer and a data layer; reconstructing a rendering software resource control method, establishing a corresponding functional module, and providing a user-defined instruction system, wherein the user-defined instruction system comprises five categories of an analysis instruction, a judgment instruction, a resource scheduling instruction, an execution instruction and a communication instruction; according to the software definition characteristics, the rendering process and the management flow are modified, so that the rendering process and the management flow are more flexible. According to the cloud rendering system, centralization, control and execution are separated, rendering resources and access modes and deployment modes thereof are decoupled and reconstructed, functions of the system are optimized while centralized resources are enhanced, the overall load is reduced, and the system can run more efficiently and in an extensible mode; meanwhile, a user can set a 3D rendering engine, a plug-in required to be used, the rendering server scale and rendering cluster management software by himself, and the customized rendering environment is controllable in cost at the same time, so that requirements of different users under various rendering scenes are met.
Description
Technical Field
The invention relates to the technical field of computer information, in particular to a cloud rendering system based on software definition.
Background
The revolution of new generation information technology represented by artificial intelligence, internet of things and block chains leads industrial economy to step towards digital economy. The technologies of digitalization, virtualization and intellectualization run through the whole life cycle of products, flexibility, networking and individualization become new mode trends, and globalization, service and platform become organization methods of new states. The creative industry of culture which develops vigorously in the digital era also presents brand new ecological appearances, digital technology promotes CG digital art creation contents represented by movie and animation to advance with time, changes the making mode and the making tool of art creation, brings new aesthetic standards at the same time, promotes the increasing demand of diversification of digital contents for people, provides higher requirements for the key link, namely rendering, and gradually trends to personalized and customized development for meeting diversified high-quality 3D visual effect experience of people.
Rendering is the process of computing and drawing a three-dimensional scene through complex graphic data. In the movie and animation rendering, in order to obtain a high-quality CG rendering effect, not only powerful design software is required as a basis, but also a hardware platform with strong computing power is required as a support. At present, in the rendering process, most rendering farms adopt a cluster rendering technology, utilize the advantages of a cluster computer, and generate a final image from a complex 3D scene through a large amount of calculation through network distribution software and parallel 3D rendering software. However, the cluster rendering system is limited by the scale of the rendering farm and the configuration of the rendering server, and the configuration of the rendering server is relatively single and is difficult to meet diversified rendering requirements; and the problems of unbalanced load, various software and functional plug-ins, low updating speed, lack of sufficient flexibility, low rendering speed, high operation and maintenance cost and the like exist.
Therefore, the cloud rendering system which is more efficient, flexible and customizable is provided, the resource utilization rate and the whole load capacity are improved by optimizing and recombining rendering resources, the operation cost of the system is reduced, the system architecture is more expandable and more available, and the requirements of diversification, individuation and high-quality rendering of users are continuously met.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a cloud rendering system based on software definition, which adopts user-defined rendering process configuration and flow management to realize rapid and flexible resource deployment of one or more rendering tasks, greatly improves the load capacity and provides high-quality rendering service with high efficiency, flexibility and low cost for users.
In order to achieve the above object, the technical solution adopted by the present invention has the following features: a cloud rendering system based on software definition comprises an application layer, a control layer, an infrastructure layer and a data layer; reconstructing a rendering software resource control method, establishing a corresponding functional module, and providing a user-defined instruction system, wherein the user-defined instruction system comprises five categories of an analysis instruction, a judgment instruction, a resource scheduling instruction, an execution instruction and a communication instruction; according to the software definition characteristics, the rendering process and the management flow are modified, so that the rendering process and the management flow are more flexible.
The system architecture consists of an application layer, a control layer, an infrastructure layer and a data layer;
further, the application layer provides rendering services, directly faces to user requirements, and provides various required rendering services for the user, including real-time rendering, offline rendering and the like;
the control layer is the core of the cloud rendering system architecture, provides an API (application programming interface) for application, is responsible for collecting and analyzing various rendering requirements, and provides resource management for rendering equipment. Internally, the information obtained from these different interfaces is translated into an optimal rendering strategy and utilized to complete task scheduling, intelligent decision making and command pushing, including the controller, custom cloud rendering management and execution scheduler.
The infrastructure layer is a resource pool for realizing a rendering function, and provides rendering equipment required by various rendering services for the application layer, wherein the rendering equipment comprises rendering software such as 3D Max, Maya Unity and the like; third party add-ins such as CG Magic, Vray, etc.; other tools, such as cloud baking tools, and the like; the rendering devices are deployed in the cloud computing environment, resource management of the rendering devices is achieved, rendering resources are flexibly scheduled according to specific rendering business requirements, efficient and customized rendering operation is conducted, meanwhile, the scale of the rendering resources can be transversely expanded according to the specific rendering business scale, and the expansibility and the usability of the resources are improved.
And the database is used for storing rendering files, rendering materials, other knowledge management and the like. Data interaction is carried out between the control layer and the application layer and between the control layer and the infrastructure layer, and the generated data are stored in a database to form a plurality of libraries, such as user-designed dynamic models of characters, water, fire, cloud and fog and the like and material files of agents, lights, maps and the like, and a 3D model library and a rendering material library can be generated; a knowledge base generated by rendering rules, rendering functions, and the like; the resource libraries are further scheduled and used, so that the personalized requirements of the users can be met.
The custom instruction set includes 5 broad classes of custom instructions:
1. analyzing the instructions: the method has the advantages that the analysis function of the rendering task provided by the user is realized, the rendering scene analysis, the rendering image quality analysis, the rendering speed analysis, the rendering combination mode analysis and the like are involved, and the user can be ensured to use the rendering tool more accurately;
further, the rendering scene comprises a common scene, a 3D scene, a circular screen scene and the like; the rendering combination mode comprises superposition, singleness and the like.
2. Judging an instruction: on the basis of comprehensively analyzing the rendering task, the judgment logic is realized, the judgment of the rendering task, the judgment of the rendering material characteristics, the judgment of the rendering file compatibility and the like are related, and the rendering management efficiency can be effectively improved;
further, the rendering tasks comprise an effect graph rendering task (offline rendering) and a movie rendering task (real-time rendering); rendering material features include vector graphics and dot matrix graphics.
3. Resource scheduling instructions: after the judgment instruction is completed, executing decision logic, relating to rendering scheme priority decision and rule base matching decision; after the decision is completed, executing a resource scheduling instruction, relating to local resource scheduling and preset resource scheduling, and optimizing the access efficiency of rendering resources;
further, the rendering scheme priority refers to the factors of inquiring and evaluating the number, scale, configuration, availability and the like of computing resources of each public cloud service provider from an execution scheduler according to the user type, the charging cost, the rendering speed and the requirements of rendering pictures, and dynamically deciding the optimal rendering scheme; and the rule base matching decision is to match the rendering resources with the rule base, execute decision logic when matching, and execute default decision logic when all the rules are not matched.
4. Executing the instructions: the system comprises a matching instruction, a scheduling instruction, a rendering instruction, a superposition and combination instruction, a verification instruction and the like, and the execution capacity of the system is improved;
further, after determining the optimal rendering scheme, executing matching operation; after the rule matching is completed, executing resource scheduling operation; after the rendering resource allocation is finished, executing rendering operation; after the rendering is completed, performing a superposition and combination operation on the rendered graphics; and finally, after a rendering result is obtained, executing verification operation, if the user requirement is not met, analyzing and judging again to form a new rendering scheme, and rendering again.
5. Communication instructions: the method comprises the steps of original data communication, process communication, state communication and the like, and ensures that rendering data and instructions are accurately transmitted among layers;
further, the raw data communication includes data transmission between an application layer and a control layer; the process communication includes command flow and scheduling instructions between the control layer and the infrastructure layer and storage and scheduling instructions between the control layer and the data layer; the status communication includes request instructions, policy feedback, behavior logs, and the like.
The method comprises the following steps of calling and executing an instruction set to complete a rendering process:
1. a user submits a rendering order, firstly, rendering scenes are classified into common scenes, 3D scenes and circular screen scenes according to the complexity (the number of geometric surfaces) of the scenes and the number of cameras corresponding to lenses, then, target scenes are analyzed to obtain parameters of the target scenes, and then, the rendering parameters are analyzed according to the rendering image quality and the rendering speed required by the user.
2. On the basis of comprehensively analyzing the rendering scene, selecting an effect graph rendering task (off-line rendering) and a movie rendering task (real-time rendering) according to whether the final rendering result of the rendering task is the animation played by continuous multiple frames; if the effect graph rendering task is the effect graph rendering task, selecting a single-frame multi-machine (distributed or partitioned rendering) rendering mode, and if the effect graph rendering task is the video rendering task, selecting a multi-frame single-machine/single-frame multi-machine rendering mode; then selecting a vector diagram and a dot matrix diagram according to the rendering material characteristics; and finally, selecting and setting parameters such as photon resolution, material, ray tracing strength and the like in the scene according to rendering image quality and rendering speed required by a user.
3. After determining a scene of a rendering task and rendering parameters required by rendering requirements such as rendering image quality and rendering speed, deciding the rendering scheme priority, and selecting different public clouds, different farms and different software and hardware resources according to the user type, the rendering speed, the rendering picture, the charging cost and the like; and then, forming an optimal rendering solution by matching the rules of the rule base, and performing matching and scheduling configuration on rendering resources.
4. And generating a detailed execution scheme according to the optimal rendering strategy, loading rendering resources into the rendering model, and starting to execute rendering and monitor after the rendering resources are distributed. And when an accident occurs, the flexible circulation of the task is realized, the rendering task file is analyzed again, and a rendering resource network is formed. And the cloud rendering resource server loads rendering resources to the rendering model according to the rendering resource network and then performs rendering operation. Finally, after the rendering operation is finished, verifying, and if the rendering effect is in accordance with the expected rendering effect, finishing the rendering; if not, calling the instruction, reforming the rendering scheme, and executing the rendering operation until the rendering scheme is qualified.
The rendering state management can check the rendering task queue, the behavior log, the scheduling configuration condition and the like, and can dynamically adjust the rendering task queue, so that the rendering service is more efficient and more intelligent.
Furthermore, the behavior log can record, check and screen historical record information of the rendering operation of the user, data tracing is achieved, and high reliability and effectiveness of the rendering service are guaranteed.
The invention has the beneficial effects that:
according to the cloud rendering system based on software definition, centralization, control and execution are separated, rendering resources and access modes, deployment modes and implementation functions of the rendering resources are decoupled and reconstructed, the centralized resources are enhanced, the functions of the system are optimized, the overall load is reduced, and the system can run more efficiently and more extendibly; meanwhile, a user can set a 3D rendering engine, a plug-in required to be used, the rendering server scale and rendering cluster management software by himself, and the customized rendering environment is controllable in cost at the same time, so that the requirements of different users in various rendering scenes are met.
Drawings
Fig. 1 is a schematic diagram of a cloud rendering system architecture based on software definition according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of custom cloud rendering management according to an embodiment of the present invention.
FIG. 3 is a flow chart of a decision logic according to an embodiment of the present invention.
FIG. 4 is a flow chart of custom instruction set execution according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
A software-defined based cloud rendering system architecture diagram of the present invention is depicted in fig. 1. As shown in the figure, the cloud rendering system based on software definition of the embodiment includes, from left to right, an application layer, a control layer, and an infrastructure layer; reconstructing a rendering software resource control method, establishing a corresponding functional module, and providing a user-defined instruction set comprising five categories of analysis instructions, judgment instructions, resource scheduling, execution instructions and communication instructions; according to the software definition characteristics, the rendering process and the management flow are modified, and one or more rendering tasks are rapidly and flexibly deployed; the application layer directly faces to the requirements of users and provides various required rendering services for the users, including real-time rendering, offline rendering and the like; the control layer is the core of the cloud rendering system architecture, provides an API (application programming interface) for application, is responsible for collecting and analyzing various rendering requirements, and provides resource management for rendering equipment. Inside, the information obtained from the different interfaces is converted into an optimal rendering strategy, and task scheduling, intelligent decision making and command pushing are completed by utilizing the information; the cloud rendering system comprises a controller, a custom cloud rendering management and an execution scheduler. The infrastructure layer is a resource pool for realizing a rendering function, and provides rendering equipment required by various rendering services for the application layer, wherein the rendering equipment comprises rendering software such as 3D Max, Maya Unity and the like; third party add-ins such as CG Magic, Vray, etc.; other tools, such as cloud baking tools, and the like; the rendering devices are deployed in the cloud computing environment, resource management of the rendering devices is achieved, rendering resources are flexibly scheduled according to specific rendering business requirements, efficient and customized rendering operation is conducted, meanwhile, the scale of the rendering resources can be transversely expanded according to the specific rendering business scale, and the expansibility and the usability of the resources are improved.
And furthermore, a database connected with the lower end of the control layer through an API (application programming interface) is used for storing rendering files, rendering materials, other knowledge management and the like. Data interaction is carried out between the control layer and the application layer and between the control layer and the infrastructure layer, and the generated data are stored in a database to form a plurality of libraries, such as user-designed dynamic models of characters, water, fire, cloud and fog and the like and material files of agents, lights, maps and the like, and a 3D model library and a rendering material library can be generated; a knowledge base generated by rendering rules, rendering functions, and the like; the resource libraries are further scheduled and used, so that the personalized requirements of the users can be met.
The custom cloud rendering management of the present invention is depicted in FIG. 2, including an application layer, an analysis decision layer, and rendering management. The application layer comprises real-time rendering and offline rendering; the analysis decision layer comprises rendering analysis, strategy management, rendering state management and a knowledge base.
In fig. 3, a logic flow diagram of the present invention is described, and on the basis of a comprehensive analysis of a rendered scene, whether conversion is required is determined according to whether rendered files are compatible; secondly, dividing the rendering task into an effect graph rendering task (off-line rendering) and an animation rendering task (real-time rendering) according to whether the final rendering result of the rendering task is the animation played by continuous multiple frames; thirdly, according to the characteristics of the rendering task, the rendering is divided into a single-frame multi-machine (distributed or partitioned) rendering mode and a multi-frame single-machine/single-frame multi-machine rendering mode; fourthly, selecting and setting parameters such as photon resolution, material quality, ray tracing strength and the like in the scene according to the rendering image quality and the rendering speed; and fifthly, selecting the vector diagram and the dot matrix diagram according to the rendering material characteristics.
The embodiment has a customized instruction set, which includes five categories of an analysis instruction, a judgment instruction, a resource scheduling instruction, an execution instruction and a communication instruction:
1. analyzing the instructions: the method has the advantages that the analysis function of the rendering task provided by the user is realized, the rendering scene analysis, the rendering image quality analysis, the rendering speed analysis, the rendering combination mode analysis and the like are involved, and the user can be ensured to use the rendering tool more accurately;
further, the rendering scene comprises a common scene, a 3D scene, a circular screen scene and the like; the rendering combination mode comprises superposition, singleness and the like.
2. Judging an instruction: on the basis of comprehensively analyzing the rendering task, the judgment logic is realized, the judgment of the rendering task, the judgment of the rendering material characteristics, the judgment of the rendering file compatibility and the like are related, and the rendering management efficiency can be effectively improved;
the rendering tasks comprise an effect graph rendering task (offline rendering) and a movie rendering task (real-time rendering); rendering material features include vector graphics and dot matrix graphics.
3. Resource scheduling instructions: after the judgment instruction is completed, executing decision logic, relating to rendering scheme priority decision and rule base matching decision; after the decision is completed, executing a resource scheduling instruction, relating to local resource scheduling and preset resource scheduling, and optimizing the access efficiency of rendering resources;
the rendering scheme priority refers to the factors of inquiring and evaluating the quantity, scale, configuration, availability and the like of computing resources of each public cloud service provider from an execution scheduler according to the user type, the charging cost, the rendering speed and the requirements of rendering pictures, and dynamically deciding the optimal rendering scheme; and the rule base matching decision is to match the rendering resources with the rule base, execute decision logic when matching, and execute default decision logic when all the rules are not matched.
4. Executing the instructions: the system comprises a matching instruction, a scheduling instruction, a rendering instruction, a superposition and combination instruction, a verification instruction and the like, and the execution capacity of the system is improved;
after determining the optimal rendering scheme, executing matching operation; after the rule matching is completed, executing resource scheduling operation; after the rendering resource allocation is finished, executing rendering operation; after the rendering is completed, performing a superposition and combination operation on the rendered graphics; and finally, after a rendering result is obtained, executing verification operation, if the user requirement is not met, analyzing and judging again to form a new rendering scheme, and rendering again.
5. Communication instructions: the method comprises the steps of original data communication, process communication, state communication and the like, and ensures that rendering data and instructions are accurately transmitted among layers;
the raw data communication comprises data transmission between an application layer and a control layer; the process communication includes command flow and scheduling instructions between the control layer and the infrastructure layer and storage and scheduling instructions between the control layer and the data layer; the status communication includes request instructions, policy feedback, behavior logs, and the like.
Fig. 4 depicts a flow chart of the custom instruction set execution of the present invention, including the following specific steps:
1. a user submits a rendering task, and a rendering scene, a rendering combination mode, a rendering image quality and a rendering speed are analyzed according to a target environment and user requirements;
2. on the basis of comprehensive analysis, judging the compatibility of rendering files, rendering tasks and rendering material characteristics;
3. determining a priority sequence, determining an optimal rendering strategy, matching a rule base, and scheduling rendering resources;
4. performing rendering operation, after the rendering is finished, verifying, and if the expected rendering effect is met, finishing the rendering; if not, calling the instruction, reforming the rendering scheme, and executing the rendering operation until the rendering scheme is qualified.
The above embodiments are only for illustrating the technical idea of the implementation of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical solution according to the technical idea of the present invention falls within the protection scope of the present invention. The technology not related to the invention can be realized by the prior art.
Claims (9)
1. A cloud rendering system based on software definition, characterized by: the system comprises an application layer, a control layer, an infrastructure layer and a data layer; reconstructing a rendering software resource control method, establishing a corresponding functional module, and providing a user-defined instruction system, wherein the user-defined instruction system comprises five categories of an analysis instruction, a judgment instruction, a resource scheduling instruction, an execution instruction and a communication instruction; according to the software definition characteristics, the rendering process and the management flow are modified, so that the rendering process and the management flow are more flexible.
2. The software-definition-based cloud rendering system of claim 1, wherein:
the application layer provides rendering services, directly faces to user requirements, and provides various required rendering services for the user, including real-time rendering and offline rendering;
the control layer is the core of a cloud rendering system architecture, provides an API (application programming interface) for application, is responsible for collecting and analyzing various rendering requirements, and provides resource management for rendering equipment; internally, the information obtained from these different interfaces is translated into an optimal rendering strategy and utilized to complete task scheduling, intelligent decision making and command pushing, including the controller, custom cloud rendering management and execution scheduler.
The infrastructure layer is a resource pool for realizing a rendering function, and provides rendering equipment required by various rendering services for the application layer, wherein the rendering equipment comprises rendering software, third-party auxiliary plug-ins, other tools and the like; the rendering devices are deployed in a cloud computing environment, resource management of the rendering devices is achieved, rendering resources are flexibly scheduled according to specific rendering service requirements, efficient and customized rendering operation is carried out, the scale of the rendering resources can be transversely expanded according to the specific rendering service scale, and the expansibility and the usability of the resources are improved;
the database is used for storing rendering files, rendering materials and other knowledge management; performing data interaction with an application layer and an infrastructure layer through a control layer, storing generated data into a database to form a plurality of libraries, and generating a 3D model library and a rendering material library; a knowledge base generated by rendering rules and rendering functions; and the resource libraries are further scheduled and used to meet the personalized requirements of users.
3. The software-definition-based cloud rendering system of claim 1, wherein:
the analysis instructions: the method has the advantages that the analysis function of the rendering task provided by the user is realized, the rendering scene analysis, the rendering image quality analysis, the rendering speed analysis, the rendering combination mode analysis and the like are involved, and the user can be ensured to use the rendering tool more accurately;
the judgment instruction is as follows: on the basis of comprehensively analyzing the rendering task, the judgment logic is realized, the judgment of the rendering task, the judgment of the rendering material characteristics, the judgment of the rendering file compatibility and the like are related, and the rendering management efficiency can be effectively improved;
the resource scheduling instructions: after the judgment instruction is completed, executing decision logic, relating to rendering scheme priority decision and rule base matching decision; after the decision is completed, executing a resource scheduling instruction, relating to local resource scheduling and preset resource scheduling, and optimizing the access efficiency of rendering resources;
the execution instructions: the system comprises a matching instruction, a scheduling instruction, a rendering instruction, a superposition and combination instruction, a verification instruction and the like, and the execution capacity of the system is improved;
the communication instructions: the method comprises original data communication, process communication, state communication and the like, and ensures that rendering data and instructions are accurately transmitted among layers.
4. The software-definition-based cloud rendering system of claim 3, wherein:
rendering scenes in the analysis instruction comprise common scenes, 3D scenes, circular screen scenes and the like; the rendering combination mode comprises superposition, singleness and the like;
rendering tasks in the judgment instruction comprise an effect graph rendering task (offline rendering) and a movie rendering task (real-time rendering); rendering material characteristics including vector diagrams and dot matrix diagrams;
the rendering scheme priority in the resource scheduling instruction is that factors such as the number, scale, configuration, availability and the like of computing resources of each public cloud service provider are inquired and evaluated from an execution scheduler according to the user type, the charging cost, the rendering speed and the requirements of rendering pictures, and an optimal rendering scheme is dynamically decided; the rule base matching decision is to match the rendering resources with the rule base, execute decision logic when matching, and execute default decision logic when all rules are not matched;
in the execution instruction, after the optimal rendering scheme is determined, matching operation is executed; after the rule matching is completed, executing resource scheduling operation; after the rendering resource allocation is finished, executing rendering operation; after the rendering is completed, performing a superposition and combination operation on the rendered graphics; finally, after a rendering result is obtained, performing verification operation, if the user requirements are not met, analyzing and judging again to form a new rendering scheme, and rendering again;
the original data communication in the communication instruction comprises data transmission between an application layer and a control layer; the process communication includes command flow and scheduling instructions between the control layer and the infrastructure layer and storage and scheduling instructions between the control layer and the data layer; the status communication includes request instructions, policy feedback, behavior logs, and the like.
5. The software-definition-based cloud rendering system of claim 3 or 4, wherein:
calling and executing an instruction set to complete a rendering process, and specifically comprising the following steps:
step one, a user submits a rendering order, firstly, rendering scenes are classified into common scenes, 3D scenes and all-round scenes according to the complexity (the number of geometric surfaces) of the scenes and the number of cameras corresponding to lenses, then, target scenes are analyzed to obtain parameters of the target scenes, and then, the rendering parameters are analyzed according to the rendering image quality and the rendering speed required by the user.
Secondly, on the basis of comprehensively analyzing the rendering scene, selecting an effect graph rendering task (off-line rendering) and a movie rendering task (real-time rendering) according to whether the final rendering result of the rendering task is the continuous multi-frame playing animation; if the effect graph rendering task is the effect graph rendering task, selecting a single-frame multi-machine (distributed or partitioned rendering) rendering mode, and if the effect graph rendering task is the video rendering task, selecting a multi-frame single-machine/single-frame multi-machine rendering mode; then selecting a vector diagram and a dot matrix diagram according to the rendering material characteristics; and finally, selecting and setting parameters such as photon resolution, material, ray tracing strength and the like in the scene according to rendering image quality and rendering speed required by a user.
After determining the scene of the rendering task and rendering parameters required by rendering requirements such as rendering image quality and rendering speed, deciding the rendering scheme priority, and selecting different public clouds, different farms and different software and hardware resources according to the user type, the rendering speed, the rendering picture, the charging cost and the like; and then, forming an optimal rendering solution by matching the rules of the rule base, and performing matching and scheduling configuration on rendering resources.
And step four, generating a detailed execution scheme according to the optimal rendering strategy, loading rendering resources into the rendering model, and starting to execute rendering and monitor after the rendering resources are distributed. And when an accident occurs, the flexible circulation of the task is realized, the rendering task file is analyzed again, and a rendering resource network is formed. And the cloud rendering resource server loads rendering resources to the rendering model according to the rendering resource network and then performs rendering operation. Finally, after the rendering operation is finished, verifying, and if the rendering effect is in accordance with the expected rendering effect, finishing the rendering; if not, calling the instruction, reforming the rendering scheme, and executing the rendering operation until the rendering scheme is qualified.
6. A cloud rendering method based on software definition comprises a component cloud rendering system, wherein the system architecture comprises an application layer, a control layer, an infrastructure layer and a data layer; reconstructing a rendering software resource control method, establishing a corresponding functional module, and providing a user-defined instruction system, wherein the user-defined instruction system comprises five categories of an analysis instruction, a judgment instruction, a resource scheduling instruction, an execution instruction and a communication instruction; according to the software definition characteristics, the rendering process and the management flow are modified, so that the rendering process and the management flow are more flexible; the method is characterized in that:
the application layer provides rendering services, directly faces to the requirements of users, and provides various required rendering services for the users, including real-time rendering and offline rendering;
the control layer is the core of the cloud rendering system architecture, provides an API (application programming interface) for application, is responsible for collecting and analyzing various rendering requirements, and provides resource management for rendering equipment; inside, information obtained from the different interfaces is converted into an optimal rendering strategy, and task scheduling, intelligent decision and command pushing are completed by utilizing the information, wherein the information comprises a controller, a custom cloud rendering management and an execution scheduler;
the infrastructure layer is a resource pool for realizing a rendering function, and provides rendering equipment required by various rendering services for the application layer, wherein the rendering equipment comprises rendering software, third-party auxiliary plug-ins, other tools and the like; the rendering devices are deployed in a cloud computing environment, resource management of the rendering devices is achieved, rendering resources are flexibly scheduled according to specific rendering service requirements, efficient and customized rendering operation is carried out, the scale of the rendering resources can be transversely expanded according to the specific rendering service scale, and the expansibility and the usability of the resources are improved;
the database is used for storing rendering files, rendering materials and other knowledge management; performing data interaction with an application layer and an infrastructure layer through a control layer, storing generated data into a database to form a plurality of libraries, and generating a 3D model library and a rendering material library; a knowledge base generated by rendering rules and rendering functions; and the resource libraries are further scheduled and used to meet the personalized requirements of users.
7. The software-definition-based cloud rendering method of claim 6, wherein:
and (3) an analysis step: the method has the advantages that the analysis function of the rendering task provided by the user is realized, the rendering scene analysis, the rendering image quality analysis, the rendering speed analysis, the rendering combination mode analysis and the like are involved, and the user can be ensured to use the rendering tool more accurately;
a judging step: on the basis of comprehensively analyzing the rendering task, the judgment logic is realized, the judgment of the rendering task, the judgment of the rendering material characteristics, the judgment of the rendering file compatibility and the like are related, and the rendering management efficiency can be effectively improved;
resource scheduling step: after the judging step is finished, executing decision logic, relating to rendering scheme priority decision and rule base matching decision; after the decision is completed, executing a resource scheduling instruction, relating to local resource scheduling and preset resource scheduling, and optimizing the access efficiency of rendering resources;
the execution steps are as follows: the method comprises a matching step, a scheduling step, a rendering step, a stacking and combining step and a verifying step, and improves the execution capacity of the system;
communication step: the method comprises original data communication, process communication and state communication, and ensures that rendering data and instructions are accurately transmitted among layers.
8. The software-definition-based cloud rendering method of claim 7, wherein:
rendering scenes including a common scene, a 3D scene, a circular screen scene and the like; the rendering combination mode comprises superposition, singleness and the like;
rendering tasks include an effect graph rendering task (offline rendering) and a movie rendering task (real-time rendering); rendering material characteristics including vector diagrams and dot matrix diagrams;
the rendering scheme priority is that according to the user type, the charging cost, the rendering speed and the requirements of the rendering picture, factors such as the number, the scale, the configuration, the availability and the like of computing resources of each public cloud service provider are inquired and evaluated from an execution scheduler, and the optimal rendering scheme is dynamically decided; the rule base matching decision is to match the rendering resources with the rule base, execute decision logic when matching, and execute default decision logic when all rules are not matched;
after determining the optimal rendering scheme, executing matching operation; after the rule matching is completed, executing resource scheduling operation; after the rendering resource allocation is finished, executing rendering operation; after the rendering is completed, performing a superposition and combination operation on the rendered graphics; finally, after a rendering result is obtained, performing verification operation, if the user requirements are not met, analyzing and judging again to form a new rendering scheme, and rendering again;
the original data communication comprises data transmission between an application layer and a control layer; the process communication includes command flow and scheduling instructions between the control layer and the infrastructure layer and storage and scheduling instructions between the control layer and the data layer; the state communication comprises a request instruction, strategy feedback and a behavior log.
9. The software-defined-based cloud rendering method of claim 8, wherein:
calling and executing an instruction set to complete a rendering process, and specifically comprising the following steps:
step one, a user submits a rendering order, firstly, rendering scenes are classified into common scenes, 3D scenes and all-round scenes according to the complexity (the number of geometric surfaces) of the scenes and the number of cameras corresponding to lenses, then, target scenes are analyzed to obtain parameters of the target scenes, and then, the rendering parameters are analyzed according to the rendering image quality and the rendering speed required by the user;
secondly, on the basis of comprehensively analyzing the rendering scene, selecting an effect graph rendering task (off-line rendering) and a movie rendering task (real-time rendering) according to whether the final rendering result of the rendering task is the continuous multi-frame playing animation; if the effect graph rendering task is the effect graph rendering task, selecting a single-frame multi-machine (distributed or partitioned rendering) rendering mode, and if the effect graph rendering task is the video rendering task, selecting a multi-frame single-machine/single-frame multi-machine rendering mode; then selecting a vector diagram and a dot matrix diagram according to the rendering material characteristics; finally, according to the rendering image quality and the rendering speed required by the user, parameters such as photon resolution, material quality, ray tracing strength and the like in the scene are selected and set;
after determining the scene of the rendering task and rendering parameters required by rendering requirements such as rendering image quality and rendering speed, deciding the rendering scheme priority, and selecting different public clouds, different farms and different software and hardware resources according to the user type, the rendering speed, the rendering picture, the charging cost and the like; then, an optimal rendering solution is formed by matching the rules of the rule base, and rendering resources are matched and scheduled;
step four, generating a detailed execution scheme according to the optimal rendering strategy, loading rendering resources into the rendering model, and starting to execute rendering and monitor after the rendering resources are distributed; when an accident occurs, the elastic circulation of the task is realized, and the rendering task file is analyzed again to form a rendering resource network; the cloud rendering resource server loads rendering resources to the rendering model according to the rendering resource network, and then performs rendering operation; finally, after the rendering operation is finished, verifying, and if the rendering effect is in accordance with the expected rendering effect, finishing the rendering; if not, calling the instruction, reforming the rendering scheme, and executing the rendering operation until the rendering scheme is qualified.
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