Microprofile

Microprofile is performance-consuming, that's why we recommend you to enable it only when you work with it and keep disabled otherwise.Microprofile消耗性能，这就是为什么我们建议您仅在使用时启用它，否则保持禁用。

One way to disable Microprofile is to untick the corresponding option before running UnigineEditor or the application:禁用Microprofile的一种方法是在运行UnigineEditor或应用程序之前取消选中相应的选项：

Another way is to use the microprofile_enabled console command.另一种方法是使用microprofile_enabled控制台命令。

注意

If you change the Microprofile status via the console, this setting is saved in the <Project_Name>/data/configs/default.user file. The state set in the user configuration file will override the state defined via SDK Browser.如果通过控制台更改Microprofile状态，则此设置将保存在<Project_Name>/data/configs/default.user文件中。 用户配置文件中设置的状态将复盖通过SDK浏览器定义的状态。

Microprofile allows saving the performance data to an HTML file and then analyzing it offline.Microprofile允许将性能数据保存到HTML文件，然后离线分析。

To output the performance data to the HTML file, perform the following:要将性能数据输出到HTML文件，请执行以下操作：

1. In the console, set the the number of frames to be profiled via the microprofile_dump_frames console command. You can skip this step: by default, 500 frames will be profiled.在控制台中，通过microprofile_dump_frames控制台命令设置要分析的帧数。 您可以跳过此步骤：默认情况下，将对500帧进行分析。
2. Run the microprofile_dump_html console command.运行microprofile_dump_html控制台命令。

The performance data will be saved to the specified HTML file.性能数据将保存到指定的HTML文件中。

注意

If the path isn't specified, the dump is saved to data/microprofile_dump_html folder.如果未指定路径，则转储将保存到data/microprofile_dump_html文件夹。

Using profiling dumps simplifies capturing performance "spikes": the engine continues rendering the application in the background even when it is out of focus, so the frame where the spike has occurred can be overwritten in case of using the Web server for performance data visualization. Also it can be used to estimate the optimization results: you can dump frames before and after optimization and compare them.使用分析转储简化了捕获性能“峰值”:引擎在后台继续呈现应用程序，即使它不在焦点上，因此在使用Web服务器进行性能数据可视化的情况下，可以覆盖发生峰值的帧。它还可以用来估计优化结果:您可以转储优化前后的帧并对它们进行比较。

To visualize the performance data using the local web server, perform the following:要使用本地Web服务器可视化性能数据，请执行以下操作：

1. In the console, set the the number of frames to be profiled via the microprofile_webserver_frames console command. You can skip this step: by default, 200 frames will be profiled.在控制台中，通过 microprofile_webserver_frames 控制台命令设置要分析的帧数。您可以跳过此步骤：默认情况下，将分析 200 个帧。

2. On the Menu Bar of UnigineEditor, choose Tools -> Microprofile.在UnigineEditor的菜单栏上，选择Tools -> Microprofile。

   

The performance data will be displayed in your Web browser.性能数据将显示在您的Web浏览器中。

For example, if you specify localhost:1337/100, only the first 100 frames will be displayed.例如，如果指定localhost:1337/100，则仅显示前100帧。

In the Main group of the performance data, the call stack of the operations (e.g., update, rendering, etc.) performed by the engine on CPU is displayed.在性能数据的Main组中，显示引擎在CPU上执行的操作的调用堆栈（例如update, rendering等）。

Performance Data on World Update Function World Update函数的性能数据

In the GPU group of the performance data, the call stack of the operations performed by the engine on GPU is displayed. In addition to the main performance data, for each function (e.g. environment rendering, post materials rendering and so on), the number of DIP calls and rendered triangles is shown. Also there can be the number of surfaces, lights, shadows rendered by this function, the number of materials and shaders used; the information on the node or material for which the function is called (identifier, name, etc.).性能数据的 GPU 组中，显示了引擎在GPU上执行的操作的调用堆栈。除了主要性能数据以外，对于每个功能（例如环境渲染，后期材质渲染等），还会显示DIP调用和渲染的三角形的数量。还可以有此功能渲染的表面，灯光，阴影的数量，所使用的材质和着色器的数量。有关调用该函数的节点或材质的信息（标识符，名称等）。

Performance Data on Deferred Lighting Rendering延迟照明渲染上的性能数据

When the region that corresponds to the certain function is pointed, the Microprofile displays when this function is called on CPU and how much time is spent on its performing. 指向与某个功能对应的区域时，将在CPU上调用此功能以及执行该功能所花费的时间时显示Microprofile。

OpenGL or DirectX commands can be combined into GPU Debug groups that are created automatically when defining a profiling scope. All graphic resources loaded from external files, such as textures, shaders, static or skinned meshes, as well as the Engine's internal resources, have their own debug names to simplify identification. This information can be useful when using Graphics API debuggers, such as NVIDIA Nsight or RenderDoc. OpenGL或DirectX命令可以组合到在定义概要分析范围时自动创建的GPU调试组。从外部文件加载的所有图形资源（例如纹理，着色器，静态或蒙皮的网格物体）以及引擎的内部资源均具有自己的调试名称，以简化识别。使用Graphics API调试器（例如NVIDIA Nsight或RenderDoc）时，此信息可能很有用。

Example of debug data viewed in RenderDoc在RenderDoc中查看的调试数据示例

The performance data on the engine threads is visualized in the CPUThread, SoundThread, AsyncQueueThread, WorldSpawnMeshClutterThread, WorldSpawnGrassThread groups. 引擎线程上的性能数据在CPUThread, SoundThread, AsyncQueueThread, WorldSpawnMeshClutterThread, WorldSpawnGrassThread组中可视化。

Performance Data on Physics Thread物理线程上的性能数据

To create several nested counters, you should use the beginMicro() and endMicro() functions. beginMicro() returns an identifier that should be passed to endMicro(). This enables to create nested and intersecting profiler counters.要创建多个嵌套计数器，应使用beginMicro()和endMicro()函数。 beginMicro()返回应传递给endMicro()的标识符。 这样就可以创建嵌套和相交的分析器计数器。

In the following example, combination of begin()/end() and beginMicro()/endMicro() is used. So, profiling of the AppWorldLogic::update() function will be available in both the Profiler and the Microprofile.在以下示例中，使用begin()/end()和beginMicro()/endMicro()的组合。 因此，AppWorldLogic::update()函数的分析将在分析器和Microprofile中都可用。

int AppWorldLogic::update()
{

	// start profiling
	Profiler::begin("AppWorldLogic::update");

	float time = Game::getTime();
	float angle_0 = time * 1.0f;
	float angle_1 = time * 1.5f;
	float angle_2 = time * 2.0f;

	// start profiling of the first light source (available in the Microprofile only)
	int id_0 = Profiler::beginMicro("1st Light Update");

	light_0->setWorldTransform(translate(Unigine::Math::Vec3(sinf(angle_0), cosf(angle_0), 1.0f) * 20.0f));

	// stop profiling of the first light source
	Profiler::endMicro(id_0);

	// start profiling of the second light source (available in the Microprofile only)
	int id_1 = Profiler::beginMicro("2nd Light Update");

	light_1->setWorldTransform(translate(Unigine::Math::Vec3(sinf(angle_1), cosf(angle_1), 1.0f) * 20.0f));

	// stop profiling of the second light source
	Profiler::endMicro(id_1);

	light_2->setWorldTransform(translate(Unigine::Math::Vec3(sinf(angle_2), cosf(angle_2), 1.0f) * 20.0f));

	// stop profiling
	Profiler::end();

	return 1;
}

注意

Use only beginMicro()/endMicro(), if you don't need the Profiler tool.如果您不需要分析器工具，请仅使用beginMicro()/endMicro()。

There are special macros to mark fragments of your code that should be inspected. They can be used instead of the beginMicro() and endMicro() functions:有特殊的宏来标记应该检查的代码片段。 它们可以用来代替beginMicro()和endMicro()函数：

• UNIGINE_PROFILER_FUNCTION to inspect performance of the function.UNIGINE_PROFILER_FUNCTION检查功能的性能。

  Using Macro	Using Functions
  源代码 (C++) void myFunction() { UNIGINE_PROFILER_FUNCTION; // your function code }	源代码 (C++) void myFunction() { int id = Profiler::beginMicro(__FUNCTION__); // your function code Profiler::endMicro(id); }

• UNIGINE_PROFILER_SCOPED to inspect only a certain part of the code.UNIGINE_PROFILER_SCOPED只检查代码的某一部分。

  Using Macro	Using Functions
  源代码 (C++) void myFunction() { // your function code { UNIGINE_PROFILER_SCOPED("Scope name"); // your function code } }	源代码 (C++) void myFunction() { // your function code { int id = Profiler::beginMicro("Scope name"); // your function code Profiler::endMicro(id); } }