Parallelism: Graphics Card Programming

CS 301 Lecture, Dr. Lawlor, 2005/12/02

Graphics Card Performance

Graphics cards are now several times faster than the CPU.  How do they achieve this speed? 

It's not because graphics card designers are better paid or smarter than CPU designers, or that the industry is so much bigger:
The difference is that graphics cards run "pixel programs"--a sequence of instructions to calculate the color of one pixel.  The programs for two adjacent pixels cannot interact with one another, which means that all the pixel programs are independent of each other.  This implies all the pixels can be rendered in parallel, with no waiting or synchronization between pixels.

Read that again.  That means graphics cards execute a parallel programming language. 

Parallelism theoretically allows you to get lots of computing done at a very low cost.  For example, say you've got a 1000x1000 pixel image.  That's a million pixels.  If you can build a circuit to do one floating-point operation to those pixels in 1ns (one billionth of a second, a typical flop speed nowadays), and you can fit a million of those circuits on one chip (this is the part that can't be done at the moment), you've just built a 1,000 teraflop computer.  That's three times faster than the fastest computer in the world, the $100 million dollar, 128,000-way parallel Blue Gene.  We're not there yet, because we can't fit that much floating-point circuitry on one chip, but this is the advantage of parallel execution.

As of 2005, the fastest graphics cards on the market render 16 or 24 pixels simultaneously.  Values stored at each pixel consist of four 32-bit IEEE floating-point numbers.  This means every clock cycle, the cards are operating on 64 or 96 floats at once.  The "LRP" instruction does about 3 flops per float, and executes in a single clock.  At 430MHz, the $500 24-pipe nVidia GeForce 7800 GTX thus does:
     3 flops/float*4 floats/pixel*24 pixels/clock*430 Mclocks/second=124 billion flops/second (124 gigaflops)

Recall that a regular FPU only handles one or two (with superscalar execution) floats at a time, and the SSE/AltiVec extensions only handle four floats at a time.  Even with SSE, the Pentium 4 theoretical peak performance is about 15 gigaflops, but I can't get more than about 3 gigaflops doing any real work.  By contrast, the now-obsolete Mobility Radeon 9600 graphics card in my laptop handles 4 pixels (16 floats) simultaneously, and pulls about 16 gigaflops, handily beating the Pentium 4.

Graphics Card Programming

Back in 2002, if you wanted to write a "pixel program" to run on the graphics card, you had to write nasty, unportable and very low-level code that only worked with one manufacturer's cards.  Today, you can write code using the OpenGL ARB_fragment_program extension, and run the exact same code on your ATI and nVidia cards, on your Window machine, Linux box, or Mac OS G5. 

The languages available are:
OpenGL ARB_fragment_program code is just another assembly code.  The biggest difference is that your program runs for each *pixel*, not just top-down.  All variables and accesses are done on four-float "vectors".  You can think of these vectors as storing "RGBA" colors, "XYZW" 3D positions, or you can just think of them as four floats.

The calling convention for a pixel program in NetRun is slightly simplified from the general case used for real graphics programs:
So the simplest OpenGL fragment program is this:
(Executable NetRun Link)
	MOV out,in;
Note there's no loop here, but this program by definition runs on every pixel.  In general, you control the pixels you want drawn using some polygon geometry, and the program runs on every pixel touched by that geometry.

Note that the output goes on the *left* in this assembly, so this means "for each pixel, set the output color equal to the input onscreen pixel location".  0 means black, and 1 means fully saturated color (all colors saturated means white).  The X coordinate of the onscreen location becomes the Red component of the output color--note how the image gets redder from left to right.  The Y coordinate of the onscreen location becomes the Green component of the output color--note how the image gets greener from bottom to top.  Red and green add up to yellow, so the top-right corner (where X=Y=1) is yellow.

Arithmetic

You can do arithmetic using the usual RISC-like instructions "ADD", "SUB", and "MUL", all of which take 1 clock cycle.  For example, consider the program
  ADD out,in,0.5; # out=in+0.5
This results in the output getting brighter, since we've added 0.5 to all the colors.  Note that anything less than 0 counts as black, and anything more than 1 counts as white.  This means if you screw up the range of your output values, you'll get a pure black or white screen!

There's also a 3-input "MAD" multiply-add instruction.  There's no "DIV", but there is a scalar "RCP" reciprocal estimate.  See the ARB_fragment_program cheat sheet for the complete (and long) list of instructions.

Writemasking

You can also do math where you only modify a few of the output values.  This is called "writemasking".  For example, to set the x component of "in" to 0.0, you can do:
  MOV in.x,0.0;  # Set input component to 0
  MOV out,in;
All the arithmetic instructions work with writemasks, so you can add 0.5 to just the x coordinate using:
  ADD in.x,in.x,0.5; # in.x=in.x+0.5
  MOV out,in; # out=in

Swizzling

You can rearrange the set of input components to any operation.  This is called "swizzling", where you tack on a 4-character string to describe how to rearrange the input floats. Each position in the string corresponds to an output float, and the letter (one of the letters "xyzw" or "rgba") in the position tells which component of the input to read from.  For example, to copy the x coordinate of the input to all components of the output, you'd do:
  MOV out,in.xxxx;
To interchange the x and y coordinates, you'd do: 
  MOV out,in.yxzw;
You can also use the color names, like "rgba" in swizzles--they're equivalent to the "xyzw" coordinate names.

The swizzle ".xyzw" or ".rgba" doesn't do anything--it rearranges the components into the same order they started in!

Texturing

The pixel program equivalent of a memory read is a "texture lookup".  Textures are just 2D arrays containing pixels.  You give the texture a coordinate, and it returns you the color at that position in the texture.  The whole array runs from 0 to 1 in both x and y, so the "texture coordinate" (0.5,0.5) is always the center of the texture image.  This matches up nicely with the "in" coordinates, so you can see what's in the 1st texture with one instruction:
  TEX out,in,texture[1],2D; # out = texture[1] at coordinate "in".
I can also do postprocesing on the result of the texture lookup, for example by shifting colors around:
(Executable NetRun Link)
  TEX out,in,texture[1],2D; # out = texture[1] at coordinate "in".
  ADD out.r,out,0.8; # out.r=out.r+0.8
This makes the output image redder, by adding 0.8 to the red component.

I can also change the input coordinates around any way I want, for example by raising the input x coordinate to the 4th power, which means I read from texture coordinate (0.125,0.5) (the texture's left edge) when I give the input coordinate (0.5,0.5) (the screen's center) like this:
(Executable NetRun Link)<> 
  MUL in.x,in,in; # Square x once
  MUL in.x,in,in; # Square x again
  TEX out,in,texture[1],2D; # load texture at modified coordinate
All 3D effects (perspective, lighting, parallax, shading) are created as simple mathematical transformations of the input coordinates and output colors!

In general, textures can be used almost anywhere you'd use an array in a sequential program:
The one thing you can't do in a pixel program is write to anything outside the pixel!  This means there's no easy way to, say, sum up all the elements of an array, or build a histogram of the elements, or even do "ripple carry" multiprecision addition.  Why not?  Because variable writes would create dependencies between pixels, and destroy parallelism!

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