A trip through the Graphics Pipeline 2011, part 5

图形学基础笔记III:图形管线中的多边形裁剪算法、Sutherland-Hodgman、Guard Band Clipping 这个主要讲的是viewport 里的。 从 frustum (根据 fov 视场角 和 aspect ratio 纵横比决定 lrbt,front、near 是由摄像机距离和世界大小决定的)到 viewport 之后,能够看到的就只有投影后的 cuboid 在 viewport 里面的东西了。 问题是这个 clipping 是在 CPU 还是 GPU?实际有多个阶段,从 culling,CPU clipping 到 GPU clipping 和GPU rasterization。 ... 阅读详情

A trip through the Graphics Pipeline 2011, part 5

by fgiesen on July 5, 2011

After the last post about texture samplers, we’re now back in the 3D frontend. We’re done with vertex shading, so now we can start actually rendering stuff, right? Well, not quite. You see, there’s a bunch still left to do before we actually start rasterizing primitives. So much so in fact that we’re not going to see any rasterization in this post – that’ll have to wait until next time.

Primitive Assembly

When we left the vertex pipeline, we had just gotten a block of shaded vertices back from the shader units, with the implicit promise that this block contains an integral number of primitives – i.e., we don’t allow triangles, lines or patches to be split across multiple blocks. This is important, because it means we can truly treat each block independently and never need to buffer more than one block of shader output – we can, of course, but we don’t have to.

The next step is to assemble all the vertices belonging to a single primitive (hence “primitive assembly”). If that primitive happens to be a point, this just reads exactly one vertex and passes it on. If it’s lines, it reads two vertices. If it’s triangles, three. And so on for patches with larger numbers of control points.

In short, all that happens here is that we gather vertices. We can either do this by reading the original index buffer and keeping a copy of our vertex index->cache position map around (as I described), or we can store the indices for the fully expanded primitives along with the shaded vertex data, which might take a bit more space for the output buffer but means we don’t have to read the indices again here. Either way works fine.

And now we have expanded out all the vertices that make up a primitive. In other words, we now have complete triangles, not just a bunch of vertices. So can we rasterize them already? Not quite.

Viewport culling and clipping

Oh yeah, that. Yeah, I guess we’d better do that first, huh? This is one part of pipeline that really does exactly what you’d expect, pretty much the way you would expect it too (i.e. the way it’s explained in the docs). So I’m not gonna explain polygon clipping in general here, you can look that up in any computer graphics textbook, although most make a terrible mess of it; if you want a good explanation, use Jim Blinn’s (chapter 13 of this book), although you probably want to pass on his alternative [0,w] clip space these days, to avoid confusion if nothing else.

Anyway, clipping. The short version is this: Your vertex shader returns vertex positions on homogeneous clip space. Clip space is chosen to make the equations that describe the view frustum as simple as possible; in the case of D3D, they are -w \le x \le w, -w \le y \le w, 0 \le z \le w, and 0 < w; note that all the last equation really does is exclude the homogeneous point (0,0,0,0), which is something of a degenerate case.

We first need to find out if the triangle is partially or even completely outside any of these clip planes. This can be done very efficiently using

Cohen-Sutherland-style out-codess. You compute the clip out-code (or just clip-code) for each vertex (this can be done at vertex shading time and stored along with the positions, for example). Then, for each primitive, the bitwise AND of the clip-codes will tell you all the view-frustum planes that all vertices in the primitive are on the wrong side of (if there’s any, that means the primitive is completely outside the view frustum and can be thrown away), and the bitwise OR of the clip-codes will tell you the planes that you need to clip the primitive against. Given the clipcodes, all this is just a few gates worth of hardware – simple stuff.

Additionally, the shaders can also generate a set of “cull distances” (a triangle will be discarded if any one cull distance for all vertices is less than zero), and a set of “clip distances” (which define additional clipping planes). These get considered for primitive rejection/clip testing too.

The actual clipping process, if invoked, can take one of two forms: we can either use an actual polygon clipping algorithm (which adds extra vertices and triangles), or we can add the clipping planes as extra edge equations to the rasterizer (if that sounds like gibberish to you, wait until the next part where I explain rasterization – it’ll ask make sense eventually). The latter is more elegant and doesn’t require an actual polygon clipper at all, but we need to be able to handle all normalized 32-bit floating point values as valid vertex coordinates; there might be a trick for building a fast HW rasterizer that does this, but it seems tricky to say the least. So I’m assuming there’s an actual clipper, with all that involves (generation of extra triangles etc). This is a nuisance, but it’s also very infrequent (more so than you think, I’ll get to that in a second), so it’s not a big deal. Not sure if that’s special hardware either, or if that path grabs a shader unit to do the actual clipping; depends on whether dispatching a new vertex shading load at this stage is awkward or not, how big a dedicated clipping unit is, and how many of them you need. I don’t know the answer to these questions, but at least from the performance side of things, it doesn’t much matter: we don’t really clip that often. That’s because we can use guard-band clipping.

Guard-band clipping

The name is something of a misnomer; it’s not a fancy way of doing clipping. In fact, it’s quite the opposite: a straight-forward way of not doing clipping. :)

The underlying idea is very simple: Most primitives that are partially outside the left, right, top and bottom clip planes don’t need to be clipped at all. Triangle rasterization on GPUs works by, in effect, scanning over the full screen area (or more precisely, the scissor rect) and asking for every pixel: “is this pixel covered by the current triangle?” (In reality it’s a bit more complicated and way more efficient than that, but that’s the general idea). And that works just as well for triangles completely within the viewport as it does for triangles that extend past, say, the right and top clipping planes. As long as our triangle coverage test is reliable, we don’t need to clip against the left, right, top and bottom planes at all!

That test is usually done in integer arithmetic with some fixed precision. And eventually, as you move say one triangle vertex further and further out, you’ll get integer overflows and wrong test results. I think we can all agree that the rasterizer producing pixels that aren’t actually inside the triangle is, at the very least, extremely offensive behavior and should be illegal! Which it in fact is – hardware that does this is in violation of the spec.

There’s two solutions for this problem: The first is to make sure that your triangle tests never, ever generate the wrong results, no matter how your input triangle looks. If you manage that, then you don’t ever need to clip against the aforementioned four planes. This is called “infinite guard-band” because, well, the guard-band is effectively infinite. Solution two is to clip triangles eventually, just as they’re about to go outside the safe range where the rasterizer calculations can’t overflow. For example, say that your rasterizer has enough internal bits to deal with integer triangle coordinates that have -32768 \le X \le 32767, -32768 \le Y \le 32767 (note I’m using capital X and Y to denote screen-space positions; I’ll stick with this convention). You still do your viewport cull test (i.e. “is this triangle outside the view frustum”) with the regular view planes, but only actually clip against the guard-band clip planes which are chosen so that after the projection and viewport transforms, the resulting coordinates are in the safe range. I guess it’s time for an image:

Guard-band clipping illustration

Guard-band clipping

The small white rectangle with blue outline that’s roughly in the middle represents our viewport, while the big salmon-colored area around it is our guard band. It looks like a small viewport in this image, but I actually picked a huge one so you can see anything! With our -32768 .. 32767 guard-band clip range, that viewport would be about 5500 pixels wide – yes, that’s some huge triangles right there :). Anyway, the triangles show off some of the important cases. The yellow triangle is the most common case – a triangle that extends outside the viewport but not the guard band. This just gets passed straight through, no further processing necessary. The green triangle is fully within the guard band, but outside the viewport region, so it would never get here – it’s been rejected above by the viewport cull. The blue triangle extends outside the guard-band clip region and would need to be clipped, but again it’s fully outside the viewport region and gets rejected by the viewport cull. Finally, the purple triangle extends both inside the viewport and outside the guard band, and so actually needs to be clipped.

As you can see, the kinds of triangles you need to actually have to clip against the four side planes are pretty extreme. As said, it’s infrequent – don’t worry about it.

Aside: Getting clipping right

None of this should be terribly surprising; nor should it sound too difficult, at least if you’re familiar with the algorithms. But the devil’s in the details, always. Here’s some of the non-obvious rules the triangle clipper has to obey in practice. If it ever breaks any of these rules, there’s cases where it will produce cracks between adjacent triangles that share an edge. This isn’t allowed.

  • Vertex positions that are inside the view frustum must be preserved, bit-exact, by the clipper.
  • Clipping an edge AB against a plane must produce the same results, bit-exact, as clipping the edge BA (orientation reversed) against that plane. (This can be ensured by either making the math completely symmetric, or always clipping an edge in the same direction, say from the outside in).
  • Primitives that are clipped against multiple planes must always clip against planes in the same order. (Either that or clip against all planes at once)
  • If you use a guard band, you must clip against the guard band planes; you can’t use a guard band for some triangles but then clip against the original viewport planes if you actually need to clip. Again, failing to do this will cause cracks – and if I remember correctly there was actually a piece of graphics hardware in the bad old days that shipped with this bug enshrined in silicon. Oops. :)

Those pesky near and far planes

Okay, so we have a really nice quick solution for the 4 side planes, but what about near and far? Particularly the near plane is bothersome, since with all the stuff that’s only slightly outside the viewport handled, that’s the plane we do most of our clipping for. So what can we do? A z guard band? But how would that work – we’re not actually rasterizing along the z axis at all! In fact, it’s just some value we interpolate over the triangle, damn!

On the plus side, though, it’s just some value we interpolate over the triangle. And in fact the z-near test (Z < 0) is really easy to do once you interpolate Z – it’s just the sign bit. z-far (Z > 1) is an extra compare though (not I’m using Z not z here, i.e. these are “screen” or post-projection coordinates). But still, we’re doing Z-compares per pixel anyway (Z test!), so it’s not a big extra expense. It depends, but doing z-clip this way is definitely an option. And you need to be able to skip z-near/z-far clipping if you want to support things like NVidias ‘depth clamp’ OpenGL extension; in fact, I would argue the existence of that extension is a pretty good hint that they’re doing this, or at least used to for a while.

So we’re down to one of the regular clip planes: 0 < w. Can we get rid of this one too? The answer is yes, with a rasterization algorithm that works in homogeneous coordinates, e.g. this one. I’m not sure whether hardware uses that one though. It’s nice an elegant, but it seems like it would be hard to obey the (very strict!) D3D11 rasterization rules to the letter using that algorithm. But maybe there’s some cool tricks that I’m not aware of. Anyway, that’s about it with clipping.

Projection and viewport transform

Projection just takes the x, y and z coordinates and divides them by w (unless you’re using a homogeneous rasterizer which doesn’t actually project – but I’ll ignore that possibility in the following). This gives us normalized device coordinates, or NDCs, between -1 and 1. We then apply the viewport transform which maps the projected x and y to pixel coordinates (which I’ll call X and Y) and the projected z into the range [0,1] (I’ll call this value Z), such that at the z-near plane Z=0 and at the z-far plane Z=1.

At this point, we also snap pixels to fractional coordinates on the sub-pixel grid. As of D3D11, hardware is required to have exactly 8 bits of subpixel precision for triangle coordinates. This snapping turns some very thin slivers (which would otherwise cause problems) into degenerate triangles (which don’t need to be rendered at all).

Back-face and other triangle culling

Once we have X and Y for all vertices, we can calculate the signed triangle area using a cross product of the edge vectors. If the area is negative, the triangle is wound counter-clockwise (here, negative areas correspond to counter-clockwise because we’re now in the pixel coordinate space, and in D3D pixel space y increases downwards not upwards, so signs are inverted). If the area is positive, it’s wound clockwise. If it’s zero, it’s degenerate and doesn’t cover any pixels, so it can be safely culled. At this point, we know the triangle orientation so we can do back-face culling (if enabled).

And that’s it! We’re now ready for rasterization… almost. Actually we have to do triangle setup first. But doing that requires some knowledge of how rasterization will be performed, so I’ll put that off until the next part… see you then!

Final remarks

Again, I skipped some parts and simplified others, so here’s the usual reminder that things are a bit more complicated in reality: For example, I pretended that you just use the regular homogeneous clipping algorithm. Mostly, you do – but you can have some vertex shader attributes flagged as using screen-space linear instead of perspective-correct interpolation. Now, the regular homogeneous clip always does perspective-correct interpolation; in the case of screen-space linear attributes, you actually need to do some extra work to make it not perspective-correct. :)

I talk about primitives some of the time, but mostly I’m just focusing on triangles here. Points and lines aren’t hard, but let’s be honest, they’re not what we’re here for either. You can work out the details if you’re interested. :)

There’s tons of rasterization algorithms out there, some of which (like Olanos 2DH method that I cited) allow you to skip nearly all clipping, but as I mentioned, D3D11 has very strict requirements on the triangle rasterizer so there’s not much wiggle room for HW implementations; I’m not sure if those methods can be tweaked to exactly follow the spec (there’s a lot of subtle points that I’ll cover next time). So here and in the following I’m assuming you can’t do the ultra-sleek thing; then again, the not-quite-so-sleek approaches I’m running with have slightly less math per pixel in the rasterizer, so they might win for HW implementations anyway. And of course I might be missing the magic pixie dust right around the corner that solves all of these problems. That occurs surprisingly often in graphics. If you know an awesome solution, give me a shout in the comments!

Lastly, the triangle culling I’m describing here is the bare minimum; for example, the class of triangles that will generate zero pixels upon rasterization is much larger than just zero-area tris, and if you can find it out quickly enough (or with few enough gates), you can drop the triangle immediately and don’t need to go through triangle setup. This is the last point where you can cull cheaply before going through triangle setup and at least some rasterization – finding other ways to early-reject tris pays off handsomely here.

【信息科学与工程学】【数据中心】第三十五篇 云计算数据中心的学科知识04 编号学科(课程)核心知识点在云计算/云存储/云网络/云安全/云MaaS中的作用代表教材/资料/论文 + 数学方程式列表工业界应用D1421​云原生数据库:TiDB​HTAP(混合事务/分析处理)、分布式SQL、水平扩展、强一致(Raft)、自动故障恢复、与MySQL兼容、TiFlash列式引擎提供弹性扩展的分布式数据库;支撑高并发在线交易与实时分析教材:《TiDB in Action》PingCAP(2020) 论文:《TiDB: A Raft-based HTAP Database》(2017) 阅读详情

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内容概要:本文围绕磁流变阻尼器(MR Damper)的非线性特性开展深入研究,重点剖析其在动态载荷作用下的阻尼力响应与滞回行为所表现出的强非线性特征,并基于Matlab平台进行系统建模与数值仿真。通过建立能够准确描述MR阻尼器非线性力学行为的数学模型,模拟其在不同激励条件、电流强度和运动频率下的动态响应过程,进而对系统的非线性特性进行定性与定量分析。研究涵盖了模型构建、参数设定、仿真执行与结果可视化等全过程,突出了Matlab在处理复杂非线性系统仿真中的强大功能与工程实用性,为智能材料器件在振动控制领域的应用提供了坚实的理论支撑与技术路径。; 适合人群:具备一定控制理论、机械动力学或智能材料基础知识,熟悉Matlab编程环境的研究生、科研人员及从事振动控制、结构工程等相关领域的工程技术人员。; 使用场景及目标:①用于智能材料与结构领域的科研与教学,帮助深入理解磁流变阻尼器的工作机理与非线性动力学特性;②为车辆半主动悬架系统、建筑结构抗震减震、桥梁风振抑制等实际工程中的振动控制系统设计、仿真验证与参数优化提供技术支持;③作为非线性系统建模、动力学仿真与Matlab编程实践的经典案例,有效提升使用者的系统分析能力和工程软件应用水平。; 阅读建议:建议读者结合文中提供的Matlab代码进行动手实践,通过调整模型参数(如电流、激励幅值与频率)观察系统响应的变化规律,深入探究非线性特性的形成原因与影响因素,并可尝试将该建模方法迁移至其他智能阻尼器件(如压电、电流变阻尼器)的研究中,以拓展应用视野。

全桥LLC谐振(变频+移相混合控制)变换器闭环仿真模型(Simulink仿真实现)

内容概要:本文档详细介绍了一种基于Simulink实现的全桥LLC谐振变换器闭环仿真模型,采用变频与移相混合控制策略,重点研究系统的动态响应、稳态性能及高效软开关特性。内容涵盖系统建模、PI控制器设计、闭环反馈机制构建以及谐振参数的优化配置,全面展示了从理论分析到仿真验证的全过程。通过在不同输入电压与负载条件下进行仿真测试,验证了该模型在提升转换效率、实现零电压开通(ZVS)和精确调控输出电压方面的优越性能。同时,配套提供参数设计报告、仿真说明文档及参考文献,有助于深入理解与复现实验结果。; 适合人群:具备电力电子与电力系统基础知识,熟悉Simulink/Matlab仿真环境,从事高频DC-DC变换器、新能源电源、车载充电机或相关领域研发工作的工程师及高校研究生。; 使用场景及目标:① 掌握全桥LLC谐振变换器的建模方法与闭环控制系统设计流程;② 深入理解变频+移相混合控制在高效率电源变换中的协同作用机制;③ 用于科研项目复现、教学案例演示或工业级电源产品的前期仿真预研;④ 为实际硬件原型开发提供可靠的理论支撑与关键参数设计依据。; 阅读建议:建议结合所提供的仿真文件与设计报告同步操作,重点关注控制环路搭建、谐振腔参数选取及其对系统性能的影响,推荐通过调整负载与输入条件进行多工况仿真分析,有条件者可进一步推进至样机实验验证。

改进差分进化算法及其求解柔性作业车间调度问题(Python代码实现)

内容概要:本文系统阐述了改进差分进化算法在求解柔性作业车间调度问题中的应用,并提供了完整的Python代码实现。通过对传统差分进化算法的变异、交叉与选择操作进行优化,增强了算法的全局搜索能力与收敛效率,有效降低了生产过程中的最大完工时间,提升了调度方案的整体性能。研究结合柔性作业车间的实际调度需求,建立了相应的数学模型,并通过标准算例验证了改进算法在复杂调度场景下的优越性与实用性,体现了算法在智能制造与生产优化领域的工程应用潜力。; 适合人群:具备一定编程基础,熟悉Python语言,对智能优化算法和生产调度问题感兴趣的高校师生、科研人员及工业界工程师,尤其适合工作1-3年的研发人员。; 使用场景及目标:①学习和掌握差分进化算法的基本原理及其在组合优化问题中的改进方法;②应用于柔性作业车间调度、生产计划优化等实际工程问题,提升调度效率;③作为智能算法研究的参考案例,用于教学、科研或项目开发。; 阅读建议:建议读者结合文中的Python代码进行实践,通过调试和运行加深对算法流程的理解,同时可尝试将算法应用于其他调度场景以拓展应用范围。

【顶级EI复现】新扩展移相角下的双有源桥DC-DC 变换器优化控制策略(Simulink仿真实现)

内容概要:本文聚焦于“新扩展移相角下的双有源桥DC-DC变换器优化控制策略”,在Simulink环境中实现高性能闭环控制仿真。通过引入改进型扩展移相调制(EPS)策略,结合KKT最优性条件与分段解析优化方法,系统实现了软开关(ZVS/ZCS)的精确控制,有效降低了功率器件的电压电流应力,提升了变换器在高频、高压隔离场景下的转换效率与动态响应能力。文档详细阐述了控制逻辑的设计原理与参数整定方法,并提供完整的Matlab/Simulink仿真模型与代码,确保研究成果可复现、可拓展,已通过顶级EI期刊标准验证,具备高精度、强鲁棒性的工程应用价值。; 适合人群:电力电子、电气工程及其自动化等相关专业的研究生、高校科研人员,以及从事新能源发电、电动汽车、微电网、储能系统等领域的技术研发工程师;尤其适用于需复现高水平论文成果的研究者。; 使用场景及目标:①深入理解双有源桥(DAB)变换器的工作机理与先进移相控制策略;②掌握基于Simulink的电力电子系统建模、仿真与优化技术;③复现并验证EI级期刊论文中的控制算法,支撑学术论文撰写、课题申报或实际工程原型开发。; 阅读建议:建议读者结合“改进型EPS调制”“软开关实现条件”“最小应力优化目标”等核心技术要点,利用所提供的仿真模型进行分模块调试与参数扫描分析,深入探究控制环路设计逻辑与系统稳定性边界,同时可参考荔枝科研社资源目录获取同类案例以拓宽研究思路和技术视野。

这里提供国内期货与股指的逐笔成交量加权价格数据,覆盖商品期货和股指期货主力合约 每条数据包含合约代码、交易日期、精确到毫秒的时间戳、成交量加权价格、累计成交笔数及成交量 数据可用于回测和研究市场微观结

这里提供国内期货与股指的逐笔成交量加权价格数据,覆盖商品期货和股指期货主力合约。每条数据包含合约代码、交易日期、精确到毫秒的时间戳、成交量加权价格、累计成交笔数及成交量。数据可用于回测和研究市场微观结构,不包含未来信息。 数据源:CMES金融数据库

(Multisim课设资料)最全面函数信号发生器(三角波+正弦波+方波信号+锯齿波仿真设计+报告文档

内容概要:本文档是一份关于“(Multisim课设资料)最全面函数信号发生器”的综合性学习资源,系统介绍了三角波、正弦波、方波和锯齿波四种基本信号的Multisim仿真设计与实现方法。资源包含完整的电路设计方案、仿真操作流程及课程设计报告模板,详细阐述了各波形的生成原理、核心元器件选型依据、关键参数调节策略以及仿真结果验证过程。通过模块化电路搭建,帮助学习者掌握波形转换机制与模拟电路集成技术,涵盖从理论分析到实践操作的完整链条。此外,文档还整合了直流稳压电源、滤波器设计等相关电子系统仿真案例,形成配套丰富的课设支持体系,适用于电子类课程设计与工程实训参考。; 适合人群:电子信息工程、自动化、电气工程及其相关专业的本科学生及初级学习者,具备电路基础理论和Multisim软件基本操作能力的人员;特别适用于正在开展模拟电子技术课程设计、毕业设计或课外实践项目的使用者。; 使用场景及目标:①深入理解函数信号发生器中四种典型波形的产生机理与电路拓扑结构;②熟练掌握Multisim平台下的电路建模、仿真调试与数据分析技能;③完成高质量课程设计报告撰写,提升综合实践能力;④为后续电子系统设计与信号处理课程打下坚实基础。; 阅读建议:建议结合文档中的电路图与仿真步骤循序渐进地动手实践,重点关注不同波形间的转换关系与元件参数对输出特性的影响,同时参照所提供的报告范本规范实验记录与成果输出,强化理论与实践的深度融合。

【全局灵敏性】【蒙特卡洛敏感性指数估计和多精度策略】基于方差的全局敏感性分析(Matlab代码实现)

内容概要:本文围绕“面向城市空中交通的多无人机路径规划研究”展开,系统阐述了多无人机在复杂城市环境中进行高效、安全路径规划的理论与方法。研究首先明确了问题定义、约束条件与性能指标,提出了一套融合改进RRT算法与图论方法的全局路径规划框架,并结合动态风险场与模型预测控制(MPC)及动态窗口法(DWA)实现动态避障。为进一步提升多机协同能力,引入了基于分布式协同控制的局部冲突消解机制,确保多无人机在密集环境中的安全飞行与任务完成。通过多场景仿真实验验证了所提方法的有效性、鲁棒性与可扩展性,充分展示了其在城市物流、应急救援与智慧巡检等实际应用中的巨大潜力; 适合人群:具备一定编程基础与控制理论知识,从事无人机系统、智能交通、自动化控制、人工智能或相关领域的研究生、科研人员及工程技术开发者; 使用场景及目标:①应用于城市空中交通管理、多无人机协同配送、灾害应急响应、智能安防巡查等复杂动态环境下的任务场景;②目标在于实现高密度城市空间中无人机的安全避障、高效路径生成、多机协同调度与实时动态调整,推动城市低空智能化交通系统的构建与发展; 阅读建议:建议结合文中提供的Matlab代码进行仿真实践,深入理解算法实现细节与关键参数调优策略,同时配合相关文献拓展对路径规划、协同控制与智能决策理论的认知,以全面提升科研与工程应用能力。

上一篇: A trip through the Graphics Pipeline 2011, part 4
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