Speaker 1: Okay, let's unpack this. We've got some great source material
Speaker 1: here for a deep dive into well, really the engine
Speaker 1: room of modern computer graphics. We're talking GLSL, the OPENNGL
Speaker 1: shading language.
Speaker 2: And how it basically ripped up the old rule book
Speaker 2: for the rendering pipeline.
Speaker 1: Yeah, exactly. And this info comes from excerpts of GLSL
Speaker 1: Essentials by Jacobo Rodriguez.
Speaker 2: Right, a really solid book on the topic.
Speaker 1: And it's worth saying upfront this isn't really for total beginners.
Speaker 2: Is.
Speaker 1: It's aimed more at people who've maybe dabbled in computer
Speaker 1: graphics before.
Speaker 2: Yeah, folks who want to get up to speed with
Speaker 2: modern OPENNGL or maybe make that jump from the old way,
Speaker 2: the fixed pipeline.
Speaker 1: To the programmable pipeline, which the book calls And I
Speaker 1: love this phrase, the biggest revolution in real time graphics
Speaker 1: programming history.
Speaker 2: It's not an exaggeration really. It unlocks so much visual potential.
Speaker 1: And the author, Jocobo Rodriguez, he wasn't just writing about it.
Speaker 1: He was like building tools for GLSL shaders super early on.
Speaker 2: Yeah, even before some but the big hardware guys had
Speaker 2: their own tools ready. So he's got that real hands
Speaker 2: on pioneer perspective definitely.
Speaker 1: So our goal today digging into this for you is
Speaker 1: to pull out those core ideas. We wanted to explain
Speaker 1: the architecture, what the different shaders actually.
Speaker 2: Do, and show why this programmable stuff is such a
Speaker 2: game changer. Think of this as your essential guide to
Speaker 2: programmable graphics concepts.
Speaker 1: Perfect. So where do we start, Maybe the absolute basics
Speaker 1: CPU versus GPU, good place.
Speaker 2: Yeah, it really boils down to how they think, how
Speaker 2: they process things. Your CPU, your main processor. It's great
Speaker 2: at doing tasks one after another, sequential stuff.
Speaker 1: Scaler processing right, yeah, for general task exactly.
Speaker 2: But the GPU it's a different beast. It's all about
Speaker 2: parallel power, vectorial. It can chew through hundreds, maybe thousands
Speaker 2: of similar calculations all at the same time.
Speaker 1: Using all those little specialized cores. It has not great
Speaker 1: for everything, but for graphics math unbeatable.
Speaker 2: Yeah, and that parallel must is what drives the graphics
Speaker 2: rendering pipeline, which.
Speaker 1: The book describes as like a pipe where we insert
Speaker 1: some data into one end vertices texture shaders and they
Speaker 1: start to travel through some small machines.
Speaker 2: It's a good analogy an assembly line for pixels almost
Speaker 2: each stage does its specific job on the data flowing through.
Speaker 1: And for a long time that assembly line was completely fixed,
Speaker 1: same steps, same order, every time.
Speaker 2: Predictable, sure, but really inflexible. That started changing what early
Speaker 2: two thousands, two thousand and four, maybe.
Speaker 1: Yeah, around them the pipeline started opening up. You could
Speaker 1: replace some of those fixed stages with small, low level
Speaker 1: programs early shaders.
Speaker 2: But writing those was kind of a nightmare. Initially, differed
Speaker 2: hardware vendors had completely different assembly languages.
Speaker 1: Right Moving code between say, an Nvidia card and an
Speaker 1: ATI card was a major.
Speaker 2: Headache, which led pretty quickly to a need for a standard,
Speaker 2: something common, and that's where GLSL came in around two thousand.
Speaker 1: And four, a high level shader language like C but
Speaker 1: designed for GPUs and meant to work across different platforms.
Speaker 2: Initially, GLSL let you program two key parts, transforming the
Speaker 2: three D geometry.
Speaker 1: That became the vertex shader YEP.
Speaker 2: And then figuring out the color for each pixel.
Speaker 1: The fragment shader exactly.
Speaker 2: Those were the first two big programmable stages. Later on,
Speaker 2: things like the geometry shader and the compute shader got added,
Speaker 2: pushing what the BPU could do even further.
Speaker 1: Okay, so that's the pipeline's evolution. What about GLSL itself,
Speaker 1: the language, what's it like.
Speaker 2: It feels a lot like C or C plus plus a,
Speaker 2: which is nice and familiar for many programmers. But there
Speaker 2: are some pretty big differences under the hood, and.
Speaker 1: The book flag's one huge one right away. GLSL does
Speaker 1: not have pointers.
Speaker 2: That's a big ee yeah, no messing with memory addresses directly.
Speaker 2: It simplifies things a lot, avoids a ton of potential bugs,
Speaker 2: and honestly makes it easier to manage thousands of threads
Speaker 2: running in parallel safely makes sense.
Speaker 1: So syntactically, it's c like Semicolon's curly braces for blocks
Speaker 1: standard variable scoping. But the data types are where the
Speaker 1: real graphics power comes in.
Speaker 2: Absolutely, you have your standard ball and float, but then
Speaker 2: you get specialized types types for handling textures called samplers,
Speaker 2: and crucially built in vectors like vec two.
Speaker 1: Vec three, vec four for two D three D four
Speaker 1: y values.
Speaker 2: And matrix's matt two mat three mat four. These are
Speaker 2: native types, and.
Speaker 1: Doing math with these vectors and matrices it's like super optimized.
Speaker 1: The book says they map right to the hardware costs
Speaker 1: way less than doing the same math on the CPU.
Speaker 2: Massively less. It's fundamental to GPU performance. Think about calculating
Speaker 2: a cross product between two three D vectors on a CPU.
Speaker 2: That's several multiplication subtractions in GLSL.
Speaker 1: It's cross vaca vecu often.
Speaker 2: Yeah, it can be a single hardware instruction because the
Speaker 2: GPU is built for that kind of linear algebra.
Speaker 1: Wow, Okay, that explains a lot about the speed definitely.
Speaker 2: And there's another cool vector thing, swizzling.
Speaker 1: Ah yeah, swizzling super handy. Lets you rearrange your pickout
Speaker 1: components of a vector to make a new.
Speaker 2: One, right exactly, using things like dot xyzw dot RGBA.
Speaker 2: You can grab the red, green blue components like mycolor
Speaker 2: dot RGB, or you could reverse them mycolor dot bgr,
Speaker 2: or even make a vector of just the alpha value
Speaker 2: my color dot aaa.
Speaker 1: It's a really compact syntax for manipulating vector data. What
Speaker 1: else does the language have? Standard stuff like variable initializers.
Speaker 2: YEP initializers, explicit casting if you need to convert between
Speaker 2: types like into float to handle precision, standard comments and whoop.
Speaker 1: And control flow, ifels loops.
Speaker 2: All there Ifel's switch case, which the book notes can
Speaker 2: sometimes be nicely optimized by the driver, so worth using
Speaker 2: and loops for wild do wild.
Speaker 1: You can group variables together using structures just like can C.
Speaker 1: Give them a custom type name like struct material VEC three,
Speaker 1: color float, shininess.
Speaker 2: And arrays for multiple items of the same type accessed
Speaker 2: with square brackets, and you can often get the length
Speaker 2: with length there.
Speaker 1: And functions for reusable code blocks yep.
Speaker 2: Functions are key for organization. But remember no pointers. So
Speaker 2: how do you pass data back out of a function?
Speaker 1: Ah? Right, use those qualifiers in out, in out exactly.
Speaker 2: In is the default pass by value. Out means the
Speaker 2: function will write to that variable, and in out means
Speaker 2: it can read and write. It's kind of like passed
Speaker 2: by reference, but without actual pointers.
Speaker 1: Okay, a different way of thinking about function parameters. And
Speaker 1: there's a preprocessor.
Speaker 2: Too, yeah, standard C style preprocessor stuff. Hashtag version is crucial.
Speaker 2: You have to declare which GLSL version you're writing for
Speaker 2: right at the top. Then you have hashtag defined for macros,
Speaker 2: hashtag if, hashtag if deaf for conditional compilation. Pretty standard.
Speaker 1: So this GLSL code runs on the GPU. How does
Speaker 1: my main program running on the CPU actually feed data
Speaker 1: into these shaders like the position of a light or
Speaker 1: the main camera's view matrix.
Speaker 2: That's where uniform variables come in. These are variables you
Speaker 2: declare in your shader code marked with the uniform keyword, but.
Speaker 1: Their values aren't set in the shader. They come from
Speaker 1: outside exactly.
Speaker 2: Your CPU side application code uses OpenGL API calls like
Speaker 2: glow uniform matrix for a fee to send up a
Speaker 2: four by four matrix or glow uniform three for a
Speaker 2: three component vector to set the value of these uniforms, and.
Speaker 1: Once set they're constant for like that whole draw call right,
Speaker 1: read only inside the shader.
Speaker 2: Correct global and read only for that shader execution. This
Speaker 2: is the main pipe for getting dynamic data and light positions, colors,
Speaker 2: time transformation matrices, texture units.
Speaker 1: All that stuff. For textures, specifically, you declare a uniform
Speaker 1: sampler two D or similar in the shader.
Speaker 2: And then on the CPU side you bind a texture
Speaker 2: to a texture unit and tell the shader uniform which
Speaker 2: unit to use via gleet uniform one.
Speaker 1: I got it. That makes the connection between CPU and
Speaker 1: GPU much clearer. Okay, let's trace a data flow. First,
Speaker 1: stop the vertex shader right.
Speaker 2: The first programmable stage your vertex data hits. It's a
Speaker 2: pervertex operation. That means the code you write here runs
Speaker 2: once and only once, for each vertex you send to
Speaker 2: the graphics card.
Speaker 1: So if I have a Toddle with say ten thousand vertices,
Speaker 1: this shader runs ten thousand times every single frame.
Speaker 2: That's the idea. Its primary job transforming vertices, usually taking
Speaker 2: the vertex position from its local model space, applying the
Speaker 2: model view and projection matrices.
Speaker 1: The classic projection view model vertex position.
Speaker 2: Formula exactly to figure out where that vertex ends up
Speaker 2: in clip space basically screen coordinates.
Speaker 1: What does it take as input?
Speaker 2: Its main inputs are the vertex attributes, the vertex data
Speaker 2: like position may be a normal vector, textra coordinates, vertex color.
Speaker 1: Defining your vertex, bucker objects on the CPU side YEP.
Speaker 2: And those uniform variables we just discussed, like the transformation matrices.
Speaker 1: Themselves, and its main output.
Speaker 2: The one mandatory output is the final transformed vertex position.
Speaker 2: You have to write this to the special built in
Speaker 2: variable gl position.
Speaker 1: But it can output other things too.
Speaker 2: Yes, and this is super important. It can output other
Speaker 2: values using out variables. These become interbelators interpolators.
Speaker 1: Yeah, what do they do?
Speaker 2: There are values that get well interpolated across the surface
Speaker 2: of the primitive, like the triangle being drawn on after
Speaker 2: the vertex shader runs, but before the fragment shader runs.
Speaker 1: Okay, hang on. So if I have a triangle and
Speaker 1: each vertex shader outputs a different color, the fragment shader
Speaker 1: doesn't just get one of those colors.
Speaker 2: No, it gets a smoothly blended color based on where
Speaker 2: the fragment is inside the triangle. It interpolates the colors
Speaker 2: from the three vertices.
Speaker 1: Ah. Okay, that's how you get smooth the color gradients
Speaker 1: across the surface, or how texture coordinates smoothly map across
Speaker 1: a triangle even though you only define them at.
Speaker 2: The corners exactly same for normal vectors, which is crucial
Speaker 2: for smooth lighting. The book shows examples just transforming position
Speaker 2: using a matrix uniform to scale or deform the geometry.
Speaker 1: Right, it asks see how just applying the proper transform
Speaker 1: matrix we get the desired deformation.
Speaker 2: And examples passing color or texture coordinates through using those
Speaker 2: out variables which become invariables in the next stage.
Speaker 1: It also sets up lighting theory mentions the Fong model, ambient, diffuse, speculator.
Speaker 2: Light, and the key vectors needed the surface normal, the
Speaker 2: light direction, the view direction. It shows how you could
Speaker 2: calculate lighting here at each vertex that's per vertex lighting
Speaker 2: or growed shading.
Speaker 1: So the vertex shader positions the geometry and can set
Speaker 1: up data like color or normals for interpolation. What happens next.
Speaker 2: The data, including those interpolated values, flows to the fragment
Speaker 2: shader sometimes called the pixel shader.
Speaker 1: And its job is basically coloring things in pretty.
Speaker 2: Much, it's a per fragment operation. After the hardware figures
Speaker 2: out which pixels are covered by a triangle, this shader
Speaker 2: runs for each of those potential pixels or fragments to
Speaker 2: determine its final color.
Speaker 1: And the scale here is even bigger. Right the book
Speaker 1: warns it can run millions of times per frame easily.
Speaker 2: Think about a high resolution screen. That's why optimizing fragment
Speaker 2: shaders is often more critical than in the vertex shaders.
Speaker 2: Performance here directly hits your fill rate.
Speaker 1: What are its inputs?
Speaker 2: It gets uniform variables from the application, including those samplers
Speaker 2: for accessing textures using built in functions like texture.
Speaker 1: And critically, it gets the interpolated data from the vertex
Speaker 1: shader via invariables.
Speaker 2: Right, the interpolated texture coordinates, interpolated vertex colors, maybe that interpolated.
Speaker 1: Normal vector, and its output.
Speaker 2: The main output is the final color for that fragment,
Speaker 2: usually in RGBA vec four written to an out variable
Speaker 2: that's linked to the framebuffer like out vec four framebuffer color.
Speaker 2: You can also optionally write depth to gl frag depth,
Speaker 2: but there are limits. The book notes, a fragment shader
Speaker 2: generally can't read other pixel colors from the screen it's
Speaker 2: currently drawing to.
Speaker 1: Right, That's why complex effects sometimes need multiple rendering passes.
Speaker 1: Render something to a texture first, then use that texture
Speaker 1: in a later pass.
Speaker 2: And there's the discard keyword very useful.
Speaker 1: What does that do?
Speaker 2: It just tells the GPU to stop processing this specific
Speaker 2: fragment completely. The frame buffer won't be updated at all
Speaker 2: for that pixel. It's how you make parts of a
Speaker 2: triangle transparent or create cutout effects based on a texture's
Speaker 2: alpha channel for instance.
Speaker 1: Okay, the example show this progression. Well, a simple solid
Speaker 1: color color mash using a uniform.
Speaker 2: Then using interpolated vertex colors for a smooth gradient.
Speaker 1: Then using interpolated texture coordinates to look up color from
Speaker 1: a texture.
Speaker 2: Map, and then the big one fong lighting per pixel.
Speaker 1: Ah. So instead of calculating lighting at the vertices and
Speaker 1: interpolating the resulting color.
Speaker 2: You interpolate the data needed for lighting, like the normal vector,
Speaker 2: maybe the position, and then you perform the full lighting
Speaker 2: calculation inside the fragment shader for every single fragment.
Speaker 1: Which usually looks much better, right, especially for specular.
Speaker 2: Highlights, way better, the book says, Notice the specular reflections
Speaker 2: and the smooth darkening. You get much more accurate results
Speaker 2: because you're calculating with more precise per fragment data.
Speaker 1: And that final example combining texture color per pixel lighting
Speaker 1: and maybe using the texture's alpha channel to mask the specularity.
Speaker 1: That really shows how you layer things.
Speaker 2: Up for realism exactly. It's where all the pieces come
Speaker 2: together to decide that final pixel color you see.
Speaker 1: Okay, vertext shader shapes it, frag mind shader colors it.
Speaker 1: What's next? The book mentions a geometry shader. Right.
Speaker 2: This one sits after the vertex shader, but before clipping
Speaker 2: and rasterization. Its main purpose is pretty wild. It can
Speaker 2: actually create new primitives.
Speaker 1: New geometry on the fly, so it doesn't just modify vertices,
Speaker 1: it can make more exactly.
Speaker 2: That's the key difference. A vertex shader processes one vertex
Speaker 2: at a time. A geometry shader receives an entire input
Speaker 2: primitive like a point, a line, or a full triangle.
Speaker 1: Even if you send a triangle strip, it gets individual triangles. Yep.
Speaker 2: The hardware breaks down strips and fans into individual primitives
Speaker 2: before they hit the geometry shader, so it gets the
Speaker 2: whole primitive, sometimes even info about adjacent primitives. And then, crucially,
Speaker 2: it can produce new vertices and emit new primitives using
Speaker 2: commands like emitt vertex and n primitive wow.
Speaker 1: So you could feed at one point and have it
Speaker 1: output say a quad or even a more complex shape.
Speaker 2: Precisely. That's its power. It can amplify or change the
Speaker 2: geometry dramatically.
Speaker 1: That sounds computationally expensive, though it can be.
Speaker 2: Yeah, you have to be mindful of how much geometry
Speaker 2: you're generating. Some other details, The input primitive type and
Speaker 2: the output primitive type don't have to match. You tell
Speaker 2: the shader what kind of primitive to expect layout points
Speaker 2: in and what kind of will output layout triangle strip
Speaker 2: max vertices evil four including the maximum number of vertices
Speaker 2: it might.
Speaker 1: Output, and how does data get passed to and from it?
Speaker 1: You mentioned interface blocks.
Speaker 2: Yeah, for geometry shaders in later stages, simple inout variables
Speaker 2: aren't enough. Interface blocks are like name structs that group
Speaker 2: variables together for input and output. The input from the
Speaker 2: vertex shader comes in a built in block called Glenn,
Speaker 2: which is an array holding the data for each vertex
Speaker 2: of the input primitive.
Speaker 1: Okay, the book has a simple pass through example.
Speaker 2: First right, it just takes the input primitive loops through
Speaker 2: its vertices in Glenn, calls immit vertex for each one,
Speaker 2: and then n primitive to basically output the exact same
Speaker 2: primitive just shows the basic structure.
Speaker 1: The cool example is the crowd of butterflies. That sounds
Speaker 1: like a classic geometry shader use case.
Speaker 2: It really is. Imagine you want to draw thousands of butterflies.
Speaker 2: Sending the full mesh for every butterfly from the CPU
Speaker 2: would be a lot of data. You just send points.
Speaker 2: Each point represents a butterfli's position. The geometry shader receives
Speaker 2: a point primitive.
Speaker 1: And then it generates the butterfly mash exactly.
Speaker 2: Inside the shad you calculate the vertex positions needed to
Speaker 2: draw say two triangle strips for the wings, maybe apply
Speaker 2: some rotation or flapping animation based on time passes a uniform,
Speaker 2: and then you emit vertex for all those calculated wing
Speaker 2: vertices and end primitive twice once for each wing strip.
Speaker 1: So the GPU is generating complex geometry from simple point data.
Speaker 1: It's really clever offloading the CPU significantly precisely.
Speaker 2: It shows how you can use the GPU to offload
Speaker 2: the CPU and some rendering tasks, especially for things involving
Speaker 2: lots of repeated, procedurally generated geometry.
Speaker 1: Amazing. One more shader type mentioned, the compute shader. This
Speaker 1: one sounds different outside the rendering pipeline rules.
Speaker 2: Yeah, this one breaks the mold computechhaters. Let you use
Speaker 2: the GPU's massive parallel processing power for well pretty much
Speaker 2: anything generic computations. This is GPGPU general purpose computation on GPUs.
Speaker 1: So not tied to drawing triangles or pixels, just raw
Speaker 1: computation exactly.
Speaker 2: The execution model is different. You don't think in terms
Speaker 2: of vertices or fragments. You dispatch work in work groups,
Speaker 2: and each group contains many parallel work items threads.
Speaker 1: How do they know what data to work on?
Speaker 2: They get built in IDs like gel Global Invocation ID,
Speaker 2: which tells each thread its unique index within the overall
Speaker 2: computation grid. You use these IDs to figure out which
Speaker 2: piece of data to read or write. Work items within
Speaker 2: a group can communicate and synchronize using shared local memory.
Speaker 1: What's the advantage of using GLSL compute chats over something
Speaker 1: like CUDA or OPENZL.
Speaker 2: The big plus is integration because it's part of OPENNGL. Well,
Speaker 2: a compute shader has seamless access to all your OPENNGL resources, textures, buffers,
Speaker 2: using familiar GLSL types and functions. It's really powerful for say,
Speaker 2: running a physics simulation on the GPU and then directly
Speaker 2: using the results to render geometry or doing complex image
Speaker 2: processing effects.
Speaker 1: The book mentions it's a synchronous though, like you dispatch
Speaker 1: the compute job, gl dispatch compute and the CPU code
Speaker 1: continues immediately.
Speaker 2: That's right, which means synchronization is absolutely critical. You need
Speaker 2: to make sure the compute shader has finished writing its
Speaker 2: results before another shader or the CPU tries to read them.
Speaker 2: How do you do that using functions like yel memory barrier,
Speaker 2: it tells the GPU to ensure certain types of memory
Speaker 2: operations are complete before preceding. Getting synchronization right is key
Speaker 2: for correctness and performance.
Speaker 1: What kind of examples did the book show for compute?
Speaker 2: One was basically rendering to a texture, using each work
Speaker 2: item to calculate the color for a specific pixel, and
Speaker 2: an output image buffer could be image filter, procedural generation, whatever.
Speaker 2: And the other was pure number crunching, taking two big
Speaker 2: arrays of numbers, having each work item ad corresponding elements together,
Speaker 2: and writing the result to a third array.
Speaker 1: Zero graphics involved just using the GPU as a massively
Speaker 1: parallel math coprocessor.
Speaker 2: Exactly, and the book highlights that for tasks like that,
Speaker 2: you can potentially make mathematical algorithms two orders of magnitude
Speaker 2: faster than doing it simply in CPU.
Speaker 1: Wow, one hundred times faster ye, just by running it
Speaker 1: on the GPU using a compute shader.
Speaker 2: That's the promise of GPGPU.
Speaker 1: Yeah, okay, So wrapping this all up, we've journeyed through
Speaker 1: this programmable pipeline vertex shads, transforming points.
Speaker 2: Fragment shaders, coloring pixels.
Speaker 1: Geometry, shads creating new shapes on the fly.
Speaker 2: And compute shaders breaking free for general purpose parallel tasks.
Speaker 1: It really feels like understanding these stages and how to
Speaker 1: program them with GLSL is like getting the keys to
Speaker 1: the kingdom for modern graphics.
Speaker 2: It absolutely is. You're directly instructing these credibly powerful specialized processors.
Speaker 2: You're tapping into performance for graphics and computation that's just
Speaker 2: impossible on a CPU alone.
Speaker 1: And for you listening, this tech is behind almost everything
Speaker 1: visually impressive you see today, games, simulations, visual effects.
Speaker 2: It's the foundation. Knowing how these shaders work gives you
Speaker 2: the power to understand and eventually create those effects yourself.
Speaker 1: So thinking about the big picture for you based on
Speaker 1: this deep tive, what's the takeaway?
Speaker 2: The takeaway is that the GPU isn't just a dumb
Speaker 2: display device anymore. It's a programmable powerhouse. Vertex, fragment, geometry, compute.
Speaker 2: Each offers a unique way to leverage that power, which leads.
Speaker 1: To that final really provocative thought from the book's conclusion.
Speaker 1: It basically says, with the mechanisms that this book provides,
Speaker 1: any visual effect that you may have seen in a
Speaker 1: video game or even in a CG movie can be achieved.
Speaker 2: That's a huge claim, but you know, fundamentally, the potential
Speaker 2: is there. The complex, beautiful visuals we see, they're built
Speaker 2: by cleverly binding and programming these different shader stages.
Speaker 1: So this knowledge is your starting point, that power, that
Speaker 1: potential the book talks about. It's there for you to
Speaker 1: explore and build upon. Go experiment,