CN116883576A - TBR+PT-based collaborative rendering method and device - Google Patents

TBR+PT-based collaborative rendering method and device Download PDF

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Publication number
CN116883576A
CN116883576A CN202310851608.4A CN202310851608A CN116883576A CN 116883576 A CN116883576 A CN 116883576A CN 202310851608 A CN202310851608 A CN 202310851608A CN 116883576 A CN116883576 A CN 116883576A
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rendering
gpu
tbr
tiles
tile
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王峥
郭建君
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Beijing Weiling Times Technology Co Ltd
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Beijing Weiling Times Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/06—Ray-tracing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/005—General purpose rendering architectures
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Computer Graphics (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Generation (AREA)

Abstract

The application provides a cooperative rendering method based on TBR+PT, which comprises the following steps: decomposing an image to be rendered into a plurality of tiles with equal sizes; dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to calculate the calculation results of intersection and refraction of the rays of one or more tiles; and synchronizing the calculation result back to the main GPU, and calculating the rendering result. According to the application, rays generated by illumination during image rendering are segmented according to the tile, and distributed to each GPU in the plurality of GPUs for calculation, so that the tile is not required to be distributed to the GPUs, and the expenditure of the GPU is reduced.

Description

TBR+PT-based collaborative rendering method and device
Technical Field
The application relates to the field of delivery image rendering, in particular to a TBR+PT-based collaborative rendering method. The application also relates to a cooperative rendering device based on TBR+PT.
Background
Path Tracking (PT) is a type of Ray Tracing (Ray Tracing), and is also a global illumination algorithm in computer graphics, which can simulate many complex illumination phenomena including reflection, refraction, scattering, etc. to produce highly realistic rendering results.
The basic idea of path tracking is to start from a camera, project a ray in the direction of the line of sight, calculate the intersection point when the ray intersects an object in the scene, and randomly generate a new ray from the intersection point, repeating this process until a set tracking depth is reached or a light source object is encountered, where the color can be directly calculated.
In each intersection process of the ray and the object, the color of the point is calculated, and then all colors are added according to weights to obtain the final pixel color. This effectively simulates the multiple reflections and refractions of light in a scene, and thus can produce a depth and realism rich image.
However, since path tracking requires modeling the propagation of a large number of rays, and each ray may require multiple reflections and refractions, the computation is very computationally intensive, requiring high hardware performance and optimization techniques to achieve results in a reasonable time.
TBR (Tile Based Rendering) is to decompose the image to be rendered into tiles with equal size and render one tile by one, and the core of the conventional TBR scheme is that the rendered area is small enough to fully utilize the GPU cache advantage.
This approach is advantageous for multi-GPU parallel rendering, where each GPU can compute one or n tiles. But in a rasterized TBR scheme, there are many more difficult points to handle, such as GI (Global Il lumination) and post-effects, etc. However, it is difficult to evaluate whether the overhead caused by rasterization is large or copy overhead caused by merging after tile rendering is large.
Meanwhile, with the increase of PT effect and demand, the complexity of the scene directly influences PT performance cost, and the more the number of ray refraction is, the larger the cost is, so that the demand of a single GPU is difficult to meet.
Disclosure of Invention
The application aims to solve the problem of high GPU (graphics processing Unit) overhead caused by complex rendering scene in the prior art and provides a cooperative rendering method based on TBR+PT. The application also relates to a cooperative rendering device based on TBR+PT.
The application provides a cooperative rendering method based on TBR+PT, which comprises the following steps:
decomposing an image to be rendered into a plurality of tiles with equal sizes;
dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to calculate the calculation results of intersection and refraction of the rays of one or more tiles;
and synchronizing the calculation result back to the main GPU, and calculating the rendering result.
Optionally, the rendering the image includes: and (5) frame buffering.
Optionally, a plurality of tiles are equally distributed to each GPU.
Optionally, the GPU calculates the ray intersection and refraction of the tile in parallel.
Optionally, the rendering result includes: game scenes, movie scenes, and sense of reality scenes.
The application also provides a cooperative rendering device based on TBR+PT, which comprises:
the segmentation module is used for decomposing the image to be rendered into a plurality of tiles with the same size;
the computing module is used for dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to compute the computation results of intersection and refraction of the rays of one or more tiles;
and the rendering module is used for synchronizing the calculation result back to the main GPU and calculating the rendering result.
Optionally, the rendering the image includes: and (5) frame buffering.
Optionally, the distributing to the GPUs includes: and a plurality of tiles are evenly distributed to each GPU.
Optionally, each GPU calculates a result of the intersection and refraction of the rays of one or more tiles, including:
the GPU calculates the ray intersection and refraction of the tile in parallel.
Optionally, the rendering result includes: game scenes, movie scenes, and sense of reality scenes.
The application has the advantages and beneficial effects that:
the application provides a cooperative rendering method based on TBR+PT, which comprises the following steps: decomposing an image to be rendered into a plurality of tiles with equal sizes; dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to calculate the calculation results of intersection and refraction of the rays of one or more tiles; and synchronizing the calculation result back to the main GPU, and calculating the rendering result. According to the application, rays generated by illumination during image rendering are segmented according to the tile, and distributed to each GPU in the plurality of GPUs for calculation, so that the tile is not required to be distributed to the GPUs, and the expenditure of the GPU is reduced.
Drawings
Fig. 1 is a schematic diagram of a collaborative rendering flow based on tbr+pt in the present application.
FIG. 2 is a schematic diagram of a rendered image divided into tiles according to the present application.
FIG. 3 is a schematic diagram of ray-splitting according to tile in the present application.
Fig. 4 is a schematic diagram of path tracing in the present application.
Fig. 5 is a schematic diagram of a cooperative rendering apparatus based on tbr+pt in the present application.
Detailed Description
The present application is further described in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art may better understand the present application and practice it.
The following is a detailed description of the embodiments of the present application, but the present application may be implemented in other ways than those described herein, and those skilled in the art can implement the present application by different technical means under the guidance of the inventive concept, so that the present application is not limited by the specific embodiments described below.
The application provides a cooperative rendering method based on TBR+PT, which comprises the following steps: decomposing an image to be rendered into a plurality of tiles with equal sizes; dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to calculate the calculation results of intersection and refraction of the rays of one or more tiles; and synchronizing the calculation result back to the main GPU, and calculating the rendering result. According to the application, rays generated by illumination during image rendering are segmented according to the tile, and distributed to each GPU in the plurality of GPUs for calculation, so that the tile is not required to be distributed to the GPUs, and the expenditure of the GPU is reduced.
Fig. 1 is a schematic diagram of a collaborative rendering flow based on tbr+pt in the present application.
Referring to fig. 1, S101 decomposes an image to be rendered into a plurality of tiles of equal size.
The rendering of the image refers to performing final processing of light and color on the constructed three-dimensional image to obtain an image similar or similar to the real world image.
The image to be rendered may be a buffered frame of a game picture, a movie picture, and a realistic scene.
The buffered frames refer to one frame in a frame buffer generated by combining color buffer, depth buffer and template buffer.
As shown in fig. 2, the Tile is Based on a concept of TBR (Tile-Based Rendering), and the image to be rendered is divided into multiple tiles of the same size.
The TBR procedure is as follows:
s201, decomposing an image to be rendered into a plurality of tiles with equal sizes.
The segmentation is to segment the image according to a preset size, and the image can be rectangular, square or other shapes, and the selection of the shapes can be carried out according to actual needs.
S202, submitting triangular patch data to be rendered to a GPU through a CPU, and processing each triangular patch by the GPU to call a Vertex loader to obtain a specific position in a projection space corresponding to the triangular patch.
S203, according to the triangular patches and the specific positions of the triangular patches, the triangular patches associated with the tiles are collected, and rendering processing is carried out.
For step S203, the existing rendering method: and for each tile, putting the corresponding triangle patch list and the corresponding data into the GPU for rendering. Overhead is difficult to reduce because the data for rendering must be put into the GPU entirely.
The tile can be acquired by a local processing device or a cloud device, wherein the cloud device is a processing device deployed in a cloud server and can be connected with a user terminal in a wireless or wired mode for communication.
The processing device at least comprises a buffer unit, a processing unit and a rendering unit, wherein the buffer unit is used for buffering the frame image, and the processing unit is used for acquiring and dividing the frame image.
Specifically, after a pair of buffered frames, the processing unit may divide the buffered frames based on a preset dividing rule, or may divide the buffered frames based on a preset parameter.
For example: the image is uniformly divided into 9 tiles, or the image is divided into images of a specific size for each tile.
Referring to fig. 1, S102 divides the ray generated by illumination during image rendering according to the tile, and distributes the divided ray to each GPU of the multiple GPUs to calculate the calculation result of intersection and refraction of one or more rays of the tile.
As shown in fig. 3, in the present application, the triangle patch list corresponding to each tile and the data corresponding to the triangle patch list are not put into the GPU for rendering, but the ray generated by illumination is split according to the tile, and the calculation results of ray intersection and refraction are performed.
The processing unit mentioned above, after dividing the buffered frame, allocates according to the ratio of the number of tiles to the number of GPUs.
It should be noted that, in the rendering unit of the present application, the GPUs have a plurality of GPUs, and each GPU is connected to a master GPU, where the master GPU may be one or a plurality of GPUs.
And the processing unit distributes the calculation of ray intersection and refraction to each GPU according to a path tracking method.
As shown in fig. 4, the present application adopts PT (path tracking) method to calculate the intersection and refraction of the rays, and combines the contributions of multiple light paths to the illumination effect according to the occurrence probability.
Specifically, based on the Monte Carlo sampling algorithm, the specific flow of the PT algorithm is as follows:
a plurality of light rays are emitted from each pixel point of the camera plane to find a light source;
when the light intersects with and reflects from an object in a scene, selecting a direction from the hemispherical surface to be emitted according to a preset probability distribution function;
the energy distribution of the outgoing light is distributed according to the BRDF function.
The rest parts are as follows:
a light is emitted from each pixel point on the camera plane, which will undergo a series of reflections, refractions, and reach the light source or background in the scene.
Eventually, the light reaching the background assumes the color of the corresponding location of the background (multiplied by a series of factors on the path) at that pixel point, while the light reaching the light source assumes the light source color there. And combining the contributions of the light paths to the illumination effect according to the occurrence probability of the light paths, so as to realize rendering.
In the application, based on the process of the PT algorithm, each GPU only performs the computation of intersection and refraction of the light rays, does not perform further rendering, and only generates a computation result.
Referring to fig. 1, S103 synchronizes the calculation result back to the master GPU to calculate the rendering result.
And finally, returning the calculation results to the main GPU, and rendering the calculation results according to the received calculation results by the main GPU to obtain a final rendered image.
As mentioned above, the master GPU may be one or more. Based on the above, when the GPU is one, all data needs to be generated into the one master GPU for rendering, otherwise, the number of GPUs needed to be adopted needs to be judged, and the determination is performed according to the judgment result and the total number of master GPUs.
Specifically, load comparison is performed first, namely:
P＝F 1 -F 2
wherein the saidF 1 Is the required load, said F 2 Is the total load of all master GPUs.
When p is less than or equal to 0, then the computing task is averagely performed to each master GPU, and when p is more than 0, then:
wherein Z-q is at least the number of master GPUs needed, Z is the number of master GPUs, F 3 Is the load of a single master GPU.
Further, when p is less than 0, the total required load may be split, and two renderings may be performed, where the expression is as follows:
and s is the number of the needed main GPUs, and the rendering load is uniformly distributed to the main GPU for rendering.
According to the application, the real-time PT is realized by decomposing the image into tiles with the same size and parallelly calculating the ray refraction effect in a plurality of GPUs.
Simultaneously realizing parallelization of multiple GPUs: the truly time-consuming calculations are distributed.
The method and the device utilize the TBR+PT scheme to distribute the most time-consuming calculation to a plurality of GPUs for cooperation, and avoid copy cost caused by the traditional rasterization TBR.
The application also provides a cooperative rendering device based on TBR+PT, which comprises:
the segmentation module 301 is configured to decompose an image to be rendered into a plurality of tiles with equal sizes;
the computing module 302 is configured to segment a ray generated by illumination during image rendering according to the tile, and distribute the segment to each GPU of the multiple GPUs to compute a computation result of intersection and refraction of one or more rays of the tile;
and the rendering module 303 is used for synchronizing the calculation result back to the main GPU and calculating the rendering result.
In the segmentation module 301:
the rendering of the image refers to performing final processing of light and color on the constructed three-dimensional image to obtain an image similar or similar to the real world image.
The image to be rendered may be a buffered frame of a game picture, a movie picture, and a realistic scene.
The buffered frames refer to one frame in a frame buffer generated by combining color buffer, depth buffer and template buffer.
As shown in fig. 2, the Tile is Based on a concept of TBR (Tile-Based Rendering), and the image to be rendered is divided into multiple tiles of the same size.
The TBR procedure is as follows:
s201, decomposing an image to be rendered into a plurality of tiles with equal sizes.
The segmentation is to segment the image according to a preset size, and the image can be rectangular, square or other shapes, and the selection of the shapes can be carried out according to actual needs.
S202, submitting triangular patch data to be rendered to a GPU through a CPU, and processing each triangular patch by the GPU to call a Vertex loader to obtain a specific position in a projection space corresponding to the triangular patch.
S203, according to the triangular patches and the specific positions of the triangular patches, the triangular patches associated with the tiles are collected, and rendering processing is carried out.
For step S203, the existing rendering method: and for each tile, putting the corresponding triangle patch list and the corresponding data into the GPU for rendering. Overhead is difficult to reduce because the data for rendering must be put into the GPU entirely.
The tile can be acquired by a local processing device or a cloud device, wherein the cloud device is a processing device deployed in a cloud server and can be connected with a user terminal in a wireless or wired mode for communication.
The processing device at least comprises a buffer unit, a processing unit and a rendering unit, wherein the buffer unit is used for buffering the frame image, and the processing unit is used for acquiring and dividing the frame image.
Specifically, after a pair of buffered frames, the processing unit may divide the buffered frames based on a preset dividing rule, or may divide the buffered frames based on a preset parameter.
For example: the image is uniformly divided into 9 tiles, or the image is divided into images of a specific size for each tile.
In the calculation module 302:
as shown in fig. 3, in the present application, the triangle patch list corresponding to each tile and the data corresponding to the triangle patch list are not put into the GPU for rendering, but the ray generated by illumination is split according to the tile, and the calculation results of ray intersection and refraction are performed.
The processing unit mentioned above, after dividing the buffered frame, allocates according to the ratio of the number of tiles to the number of GPUs.
It should be noted that, in the rendering unit of the present application, the GPUs have a plurality of GPUs, and each GPU is connected to a master GPU, where the master GPU may be one or a plurality of GPUs.
And the processing unit distributes the calculation of ray intersection and refraction to each GPU according to a path tracking method.
As shown in fig. 4, the present application adopts PT (path tracking) method to calculate the intersection and refraction of the rays, and combines the contributions of multiple light paths to the illumination effect according to the occurrence probability.
Specifically, based on the Monte Carlo sampling algorithm, the specific flow of the PT algorithm is as follows:
a plurality of light rays are emitted from each pixel point of the camera plane to find a light source;
when the light intersects with and reflects from an object in a scene, selecting a direction from the hemispherical surface to be emitted according to a preset probability distribution function;
the energy distribution of the outgoing light is distributed according to the BRDF function.
The rest parts are as follows:
a light is emitted from each pixel point on the camera plane, which will undergo a series of reflections, refractions, and reach the light source or background in the scene.
Eventually, the light reaching the background assumes the color of the corresponding location of the background (multiplied by a series of factors on the path) at that pixel point, while the light reaching the light source assumes the light source color there. And combining the contributions of the light paths to the illumination effect according to the occurrence probability of the light paths, so as to realize rendering.
In the application, based on the process of the PT algorithm, each GPU only performs the computation of intersection and refraction of the light rays, does not perform further rendering, and only generates a computation result.
In the rendering module 303:
and returning the calculation results to the main GPU, and rendering the calculation results according to the received calculation results by the main GPU to obtain a final rendered image.
As mentioned above, the master GPU may be one or more. Based on the above, when the GPU is one, all data needs to be generated into the one master GPU for rendering, otherwise, the number of GPUs needed to be adopted needs to be judged, and the determination is performed according to the judgment result and the total number of master GPUs.
Specifically, load comparison is performed first, namely:
P＝F 1 -F 2
wherein the F is 1 Is the required load, said F 2 Is the total load of all master GPUs.
When p is less than or equal to 0, then the computing task is averaged to occur into each master GPU when p
At > 0, then:
wherein Z-q is at least the number of master GPUs needed, Z is the number of master GPUs, F 3 Is the load of a single master GPU.
Further, when p is less than 0, the total required load may be split, and two renderings may be performed, where the expression is as follows:
and s is the number of the needed main GPUs, and the rendering load is uniformly distributed to the main GPU for rendering.
According to the application, the real-time PT is realized by decomposing the image into tiles with the same size and parallelly calculating the ray refraction effect in a plurality of GPUs.
Simultaneously realizing parallelization of multiple GPUs: the truly time-consuming calculations are distributed.
The method and the device utilize the TBR+PT scheme to distribute the most time-consuming calculation to a plurality of GPUs for cooperation, and avoid copy cost caused by the traditional rasterization TBR.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (10)

1. The cooperative rendering method based on TBR+PT is characterized by comprising the following steps:
decomposing an image to be rendered into a plurality of tiles with equal sizes;
dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to calculate the calculation results of intersection and refraction of the rays of one or more tiles;
and synchronizing the calculation result back to the main GPU, and calculating the rendering result.
2. The tbr+pt-based collaborative rendering method of claim 1, wherein the rendering an image includes: and (5) frame buffering.
3. The method of claim 1, wherein a plurality of tiles are equally allocated to each GPU.
4. The method of claim 1, wherein the GPU calculates the ray intersection and refraction of the tile in parallel.
5. The cooperative rendering method based on tbr+pt as claimed in claim 1, wherein the rendering result includes: game scenes, movie scenes, and sense of reality scenes.
6. A cooperative rendering apparatus based on tbr+pt, comprising:
the segmentation module is used for decomposing the image to be rendered into a plurality of tiles with the same size;
the computing module is used for dividing rays generated by illumination during image rendering according to the tile, and distributing the rays to each GPU in the multiple GPUs to compute the computation results of intersection and refraction of the rays of one or more tiles;
and the rendering module is used for synchronizing the calculation result back to the main GPU and calculating the rendering result.
7. The tbr+pt-based collaborative rendering apparatus of claim 1 wherein the rendered image includes: and (5) frame buffering.
8. The tbr+pt-based collaborative rendering apparatus of claim 1, wherein the allocation into a plurality of GPUs comprises: and a plurality of tiles are evenly distributed to each GPU.
9. The tbr+pt-based collaborative rendering apparatus of claim 1, wherein each GPU calculates a result of ray intersection, refraction of one or more tiles, comprising:
the GPU calculates the ray intersection and refraction of the tile in parallel.
10. The cooperative rendering method based on tbr+pt as claimed in claim 1, wherein the rendering result includes: game scenes, movie scenes, and sense of reality scenes.
CN202310851608.4A 2023-07-12 2023-07-12 TBR+PT-based collaborative rendering method and device Pending CN116883576A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117830489A (en) * 2024-03-05 2024-04-05 浙江小牛哥科技有限公司 Intelligent indoor design image rendering system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117830489A (en) * 2024-03-05 2024-04-05 浙江小牛哥科技有限公司 Intelligent indoor design image rendering system
CN117830489B (en) * 2024-03-05 2024-05-03 浙江小牛哥科技有限公司 Intelligent indoor design image rendering system

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