当前位置: 首页 > article >正文

Filament引擎分析--command抽象设备API

1. 前言

Filament中使用了FrameGraph来管理渲染管线,需要准备两点:

  • 设备接口抽象:设备API抽象为Command
  • 资源抽象:使用虚拟资源,在实际用到时再创建,方便剔除无用资源

下面就围绕Filament中设备API抽象为Command代码部分做一个解读:

2. 代码分析

先贴一段创建顶点缓冲的接口调用堆栈:

[Inlined] filament::backend::CommandBase::CommandBase(void (*)(filament::backend::Driver &, filament::backend::CommandBase *, int *)) CommandStream.h:63
[Inlined] filament::backend::CommandType<void (filament::backend::Driver::*)(filament::backend::Handle<filament::backend::HwVertexBuffer>, unsigned char, unsigned char, unsigned int, std::__ndk1::array<filament::backend::Attribute, 16u>)>::Command<&filament::backend::Driver::createVertexBufferR(filament::backend::Handle<filament::backend::HwVertexBuffer>, unsigned char, unsigned char, unsigned int, std::__ndk1::array<filament::backend::Attribute, 16u>)>::Command<filament::backend::Handle<filament::backend::HwVertexBuffer>, unsigned char, unsigned char, unsigned int, std::__ndk1::array<filament::backend::Attribute, 16u>>(void (*)(filament::backend::Driver&, filament::backend::CommandBase*, int*), filament::backend::Handle<filament::backend::HwVertexBuffer>&&, unsigned char&&, unsigned char&&, unsigned int&&, std::__ndk1::array<filament::backend::Attribute, 16u>&&) CommandStream.h:154
[Inlined] filament::backend::CommandStream::createVertexBuffer(unsigned char, unsigned char, unsigned int, std::__ndk1::array<>) DriverAPI.inc:169
filament::FVertexBuffer::FVertexBuffer(filament::FEngine &, const filament::VertexBuffer::Builder &) VertexBuffer.cpp:185
[Inlined] utils::Arena::make<>(filament::FEngine &, const filament::VertexBuffer::Builder &) Allocator.h:647
[Inlined] filament::FEngine::create<>(filament::ResourceList<> &, const filament::FVertexBuffer::Builder &) Engine.cpp:680
filament::FEngine::createVertexBuffer(const filament::VertexBuffer::Builder &) Engine.cpp:690
filament::FEngine::init() Engine.cpp:277
filament::FEngine::create(filament::backend::Backend, filament::backend::Platform *, void *, const filament::Engine::Config *) Engine.cpp:110
[Inlined] FilamentTest::setupFilament() FilamentTest.cpp:98
FilamentTest::init() FilamentTest.cpp:68
boxing::xr::composer::StartBase::instance(ANativeWindow *, int, int) StartBase.h:263
[Inlined] native_OnDrawFrame::$_0::operator()() const JniImpl.cpp:100
[Inlined] std::__ndk1::__invoke<>(native_OnDrawFrame::$_0 &) type_traits:3874
[Inlined] std::__ndk1::__apply_functor<>(native_OnDrawFrame::$_0 &, std::__ndk1::tuple<> &, std::__ndk1::__tuple_indices<>, std::__ndk1::tuple<> &&) functional:2853
[Inlined] std::__ndk1::__bind::operator()<>() functional:2886
[Inlined] std::__ndk1::__invoke<>(std::__ndk1::__bind<> &) type_traits:3874
std::__ndk1::__packaged_task_func::operator()() future:1817
[Inlined] std::__ndk1::__packaged_task_function::operator()() const future:1994
std::__ndk1::packaged_task::operator()() future:2214
[Inlined] std::__ndk1::__function::__value_func::operator()() const functional:1884
[Inlined] std::__ndk1::function::operator()() const functional:2556
<lambda>::operator()() const ThreadPool.h:71
[Inlined] decltype(std::__ndk1::forward<boxing::core::ThreadPool::ThreadPool(unsigned int)::'lambda'()>(fp)()) std::__ndk1::__invoke<boxing::core::ThreadPool::ThreadPool(unsigned int)::'lambda'()>(boxing::core::ThreadPool::ThreadPool(unsigned int)::'lambda'()&&) type_traits:3874
[Inlined] std::__ndk1::__thread_execute<>(std::__ndk1::tuple<> &, std::__ndk1::__tuple_indices<>) thread:273
std::__ndk1::__thread_proxy<>(void *) thread:284
__pthread_start(void*) 0x00000000eab36828
__start_thread 0x00000000eaaed5ce

渲染设备API定义:

filament\filament\backend\include\private\backend\DriverAPI.inc

DriverAPI.inc中使用大量的宏替换操作,将设备接口进行封装,或打包,这部分代码可读性极差,不过可从其调用逻辑来进行拆解和理解:
先来分析其中一个接口: createVertexBuffer 创建一个顶点缓冲

DECL_DRIVER_API_R_N(backend::VertexBufferHandle, createVertexBuffer,
        uint8_t, bufferCount,
        uint8_t, attributeCount,
        uint32_t, vertexCount,
        backend::AttributeArray, attributes)

这里不是真的创建,而要看这个宏接口在哪里使用,我们主要看看这两个地方:

  CommandStream.h  //命令流
  Driver.h   //设备接口

这两个文件中都对DriverAPI.inc进行了include,但是意义完全不一样,先看DECL_DRIVER_API_R_N:

#define DECL_DRIVER_API_R_N(R, N, ...) \
    DECL_DRIVER_API_RETURN(R, N, PAIR_ARGS_N(ARG, ##__VA_ARGS__), PAIR_ARGS_N(PARAM, ##__VA_ARGS__))

关键在DECL_DRIVER_API_RETURN这个宏,在CommandStream.h和Driver.h头文件中include文件DriverAPI.inc 之前分别定义了自己的DECL_DRIVER_API_RETURN宏,看看CommandStream.h中:

#define DECL_DRIVER_API(methodName, paramsDecl, params)                                         \
    inline void methodName(paramsDecl) {                                                        \
        DEBUG_COMMAND_BEGIN(methodName, false, params);                                         \
        using Cmd = COMMAND_TYPE(methodName);                                                   \
        void* const p = allocateCommand(CommandBase::align(sizeof(Cmd)));                       \
        new(p) Cmd(mDispatcher.methodName##_, APPLY(std::move, params));                        \
        DEBUG_COMMAND_END(methodName, false);                                                   \
    }

#define DECL_DRIVER_API_SYNCHRONOUS(RetType, methodName, paramsDecl, params)                    \
    inline RetType methodName(paramsDecl) {                                                     \
        DEBUG_COMMAND_BEGIN(methodName, true, params);                                          \
        AutoExecute callOnExit([=](){                                                           \
            DEBUG_COMMAND_END(methodName, true);                                                \
        });                                                                                     \
        return apply(&Driver::methodName, mDriver, std::forward_as_tuple(params));              \
    }

#define DECL_DRIVER_API_RETURN(RetType, methodName, paramsDecl, params)                         \
    inline RetType methodName(paramsDecl) {                                                     \
        DEBUG_COMMAND_BEGIN(methodName, false, params);                                         \
        RetType result = mDriver.methodName##S();                                               \
        using Cmd = COMMAND_TYPE(methodName##R);                                                \
        void* const p = allocateCommand(CommandBase::align(sizeof(Cmd)));                       \
        new(p) Cmd(mDispatcher.methodName##_, RetType(result), APPLY(std::move, params));       \
        DEBUG_COMMAND_END(methodName, false);                                                   \
        return result;                                                                          \
    }

上面三个宏的作用基本是一样的,都将要调用的函数和参数封装为了Command,不同之处在于DECL_DRIVER_API是command无返回值的,DECL_DRIVER_API_SYNCHRONOUS是封装为command后同步执行的,DECL_DRIVER_API_RETURN是需要返回值的
主要看看DECL_DRIVER_API_RETURN:

RetType result = mDriver.methodName##S();    

将方法名后面拼接了S,调用拿到返回类型
看看拼接S后的实现:

Handle<HwVertexBuffer> OpenGLDriver::createVertexBufferS() noexcept {
    return initHandle<GLVertexBuffer>();
}

initHandle()这句在filament内存池HandleArena上创建了一个GLVertexBuffer对象,然后根据内存地址创建了对象的唯一handeID
再看下面这句:
using Cmd = COMMAND_TYPE(methodName##R);
方法名后面拼接了R,然后获取了command的类型,没有执行方法,看看拼接R后的实现:

void OpenGLDriver::createVertexBufferR(
        Handle<HwVertexBuffer> vbh,
        uint8_t bufferCount,
        uint8_t attributeCount,
        uint32_t elementCount,
        AttributeArray attributes) {
    DEBUG_MARKER()
    construct<GLVertexBuffer>(vbh, bufferCount, attributeCount, elementCount, attributes);
}

内存池HandleArena上创建了一个GLVertexBuffer对象
再看下面一句

void* const p = allocateCommand(CommandBase::align(sizeof(Cmd)));   
new(p) Cmd(mDispatcher.methodName##_, RetType(result), APPLY(std::move, params));   

在CommandStream内部的环形缓冲上申请了一块Command对象的内存p,然后在内存p上new了对象Command
看看CommandBase* execute执行函数的实现:

inline CommandBase* execute(Driver& driver) {
    // returning the next command by output parameter allows the compiler to perform the
    // tail-call optimization in the function called by mExecute, however that comes at
    // a cost here (writing and reading the stack at each iteration), in the end it's
    // probably better to pay the cost at just one location.
    intptr_t next;
    mExecute(driver, this, &next);
    return reinterpret_cast<CommandBase*>(reinterpret_cast<intptr_t>(this) + next);
}

mExecute就是上面new(p) Cmd(mDispatcher.methodName##_, RetType(result), APPLY(std::move, params)); 后的函数和参数的封装体,然后拿到了下一个圆形缓冲中下一个command的地址偏移量next,返回下一个command地址
CommandStream中执行command,执行完然后获取下一个执行。。。

mDriver.execute([this, buffer]() {
    Driver& UTILS_RESTRICT driver = mDriver;
    CommandBase* UTILS_RESTRICT base = static_cast<CommandBase*>(buffer);
    while (UTILS_LIKELY(base)) {
        base = base->execute(driver);
    }
});

http://www.kler.cn/news/155258.html

相关文章:

  • 深入理解网络非阻塞 I/O:NIO
  • zabbix_sender——向zabbix交互的sdk
  • Pandas在Excel同一个sheet里插入多个Dataframe和行
  • Leetcode.330 按要求补齐数组
  • ★543. 二叉树的直径
  • 架构图是什么,怎么做?
  • 第六十四周周报
  • c语言-结构体
  • 慢 SQL 分析及优化
  • 项目开发维护技术文档(梳理总结中)
  • Docker + Jenkins + Nginx实现前端自动化部署
  • 大型语言模型在实体关系提取中的应用探索
  • Unity中Shader需要用到的C#脚本学习路线(个人自学路线)
  • 大小堆的实现(C语言)
  • 第九节HarmonyOS 常用基础组件2-Image
  • 基于eBPF检测非法调试行为
  • 软件工程期末复习(1)
  • 基于搜索协议实现工业设备升级
  • PyLMKit(3):基于角色扮演的应用案例
  • c语言-联合体和枚举
  • Pandas时序数据分析实践—基础(1)
  • 【数据结构/C++】树和二叉树_二叉链表
  • 工业物联网数据传输方式探究
  • 【Spring Boot 源码学习】ApplicationContextInitializer 详解
  • 超大规模集成电路设计----基本概念(二)
  • [论文笔记] tiktoken中的gpt4 tokenizer
  • Linux系列-1 Linux启动流程——init与systemd进程
  • 申请Azure学生订阅——人工验证
  • tcp/ip协议 error=10022 Winsock.reg Winsock2.reg
  • 【JavaEE】多线程(3) -- 线程等待 wait 和 notify