3D Scene Rendering optimization (2)

Static scenarios include entity sets that generally do not change positions, such as terrain, vegetation, and buildings. Optimization of these entities is the most important part of scenario optimization. This article discusses common problems of static scenario optimization.

1 Batch Optimization

Batch is one of the most important concepts in scenario optimization. It refers to a rendering call (DP). The batch size is the number of polygon that can be rendered by this rendering call. Each batch of calls consumes a certain amount of CPU time. For the video card, the number of polygon in a batch cannot reach the maximum number of draws. Therefore, it is the basic principle of Batch Optimization to put more polygon in one batch for rendering, so as to reduce the number of batches and ultimately reduce the CPU time. However, it is often unsatisfactory. In some cases, the original batch will be broken, resulting in additional overhead, such as texture changes or different matrix states. To solve these problems, we can use some methods to avoid them as much as possible, and the batch size has been maximized.

(1) Merge multiple small textures into one large texture. In a specific scenario, there are over 10 different vegetation types on the ground. Except for different textures, the rendering statuses are the same. We can package their textures into a large texture and specify UV for each vegetation model, so that we can use a rendering call to render all objects, the number of batches is reduced from more than 10 to one. This method is suitable for objects with low texture precision requirements and few faces.

(2) vertices shader are used to unify different matrices, even if all objects in the scenario have the same material. If their matrix states are different (especially the engine for scenario graph management ), the original batch is also broken. This situation can be avoided by using the vertex shader technology, because the transformation matrix to be multiplied can be transferred to the shader program through the constant register. This unifies the matrix state of the object and can be rendered in a batch.

2. Render Status Management

The rendering state is used to control the rendering behavior of the Renderer. In d3d, It is the setrenderstate. By changing the rendering state, we can set the texture state, deep writing, and so on. Changing the rendering status is time-consuming for the video card, because the video card must strictly follow the rendering path when the rendering status changes, the video card must perform a floating point operation to change the rendering path. Therefore, it consumes time for the CPU and GPU (the CPU must wait). The larger the rendering state changes, the more floating point operations to be performed. Therefore, you can effectively manage the rendering status to minimize its changes, which has a huge impact on rendering performance. (The new six-generation video card geforce8 series stores some common state parameter sets in the core of the video card. When the rendering state changes, you can directly read the saved parameter sets, to eliminate unnecessary overhead ). Most 3D engines perform grouped rendering of pass by rendering status.

3 levels

I don't need to talk nonsense about this rotten technology that has been discussed by people. Let's talk about some practical applications. There are too many methods to deal with the details of the terrain, but I feel that the most practical method is the chain slice method. For the model's dashboard, the automatic surface reduction algorithm, such as vdpm, is not uncommon, but the effect is average. The conventional practice is to let the artist do the low-mode replacement. For complex scenarios, the effect of the model's dashboard is quite obvious. You need to use some techniques to make the texture of the object after the fog, including the terrain, into a uniform material that uses the fog color, so that the rendering state is unified, it depends on the specific situation to determine whether to package the data into a dp (it is better to turn off the illumination effect of the uniform material, which is time-consuming ). As for the role model, the level of granularity is similar to that of the common model. The low mode reduces the number of vertices and naturally reduces the amount of skin computing. In my opinion, it is not particularly necessary to look at the specific situation.

4. Scenario Management Optimization

Optimization of Scenario Management includes scenario segmentation and visibility removal. There are many reference articles, so I will not talk about them here. In today's outdoor scenarios, quadtree or REE is generally used. When we find that the process of traversing the tree is slow during performance evaluation, there may be two reasons. First, the depth setting of the tree is unreasonable. We can easily find the best depth. Another reason may be that we have allocated nodes for too many large objects, but small objects, resulting in redundancy of the number of nodes. The solution is to divide these small objects into their large nodes.

Visibility removal is the most common optimization method. We usually use cone reduction, which is also very effective. Cone Cutting is also a lot of optimization methods, which will not be detailed here. Blocking and cutting are also frequently used methods. Common methods include Horizon cutting. However, in some cases, the effect of blocking and cutting is not obvious. For example, when the CPU usage is already 100%, the CPU end is the bottleneck. In this case, blocking and cutting are performed to calculate the CPU consumption time, and the effect is not obvious. However, in some cases, some pre-generated information methods are used to reduce the complexity of occlusion reduction calculation, improve the efficiency of occlusion reduction calculation, and improve the scenario performance.