BrookGPU: General Purpose Programming on GPUs

An anonymous reader writes " BrookGPU is a compiler and runtime system that provides an easy, C-like programming environment (read: No GPU programming experience needed) for today's GPUs. A shader program running on the NVIDIA GeForce FX 5900 Ultra achieves over 20 GFLOPS, roughly equivalent to a 10 GHz Pentium 4. Combine this with the increased memory bandwidth, 25.3 GB/sec peak compared to the Pentium 4's 5.96 GB/sec peak, and you've got a seriously fast compute engine but programming them has been a real pain. BrookGPU adds simple data parallel language additions to C which allow programmers to specify certain parts of their code to run on the GPU. The compiler and runtime takes care of the rest. Here is the Project Page and Sourceforge page."

Comments

High Performance for General Purpose?

[tempfile]

I suspect that this high performance is only attainable for the field the GPU is specialized for, i.e. graphics-related things. Or isn't it?

Re:High Performance for General Purpose?

[Total_Wimp]

I can't help but notice the similarity between shader operations and how neurons interact. These processors might be a good platform for some AI tasks.

I especially like the idea that the GPU and CPU can work together on the task. If the GPU was handling neuron tasks and the CPU was handling other necessary tasks we could get a very big boost to desktop AI

TW

Re:High Performance for General Purpose?

[BrainInAJar]

would the percision be enough though? as far as i know, GPU's do a lot of rounding off

Re:High Performance for General Purpose?

[Directrix1]

Yes, anything computationally intensive that works over a range of data can usually find a parrallel solution. Such as image/video manipulation/encoding/decoding, encryption, and cracking (and hopefully this will give us a platform for better software RF). I've always wondered why this stuff didn't just become worked into a coprocessor. Because very little new stuff actually happened that was directly related with the video card (as in taking output from the machine and displaying it on a screen). I think the card manufacturers saw this, so they jumped on the 3d acceleration bandwagon toting it as a new video card feature, when it should've just been in the domain of a new math coprocessor.

Cool, but

[MooCows]

What kind of instructions does the GPU actually accept?
I mean, you probably just can't run any kind of algorithm on there can you?

Basically like having two processors...

[Anonymous Coward]

I wonder how long till we see a (insert worthwhile cause here)-At-Home client that supports this?

Re:Basically like having two processors...

[cybergibbons]

Ha! The C64 disk drive had it's own processor which you could use to run programs as long as you could deal with the painfully slow serial link. Beat that.

Cool ...

[torpor]

... can you say 'software synthesists' wet dream?

Oh, suddenly, that 'game investment' also gives you a few 100 extra voices of polyphony?

Sweet ... $5 to the first person to use Brooke to make a synthesizer. :)

wait a minute

[Janek Kozicki]

A shader program running on the NVIDIA GeForce FX 5900 Ultra achieves over 20 GFLOPS, roughly equivalent to a 10 GHz Pentium 4.

wait, if there is a technology that allows construction of GPU that is 3 times faster than the fastest CPUs, why Intel and AMD do not use this technology to build those 3times faster CPUs?

are you sure that you can compare the speed of GPU and CPU?

Re:wait a minute

[mdpye]

And on top of all of that I can buy 3 2.4Ghz P4s for the price of a Geforce FX5950

But you forget the 256MB (at least) RAM on a steaming fast interface that you get with the GeForce... It makes the P4s' cache look pretty paltry in size by comparison.

MP

Re:wait a minute

[barik]

Are you sure that you can compare the speed of GPU and CPU?

Professor Pat Hanrahan, of Stanford University, made a stab at answering this question in his presentation 'Why is Graphics Hardware so Fast?'. The first half of the presentation focuses on this question, while the second half of the presentation covers programming languages that utilitize this hardware. Specifically, the Stanford Real-Time Shading Language (RTSL) and Brook are discussed. Overall, it's a good presentation that should get you up to speed with the basics of what's happening in this area of research.

How does this look?

[adrianbaugh]

I'm completely new to meddling with graphics card, so apologies if this is a silly question: when programs utilising the GPU for arbitrary calculations are running does the screen go weird, or is there a way of stopping the output being displayed? A screenfull of junk might not matter to a scientist leaving their computer to crunch numbers for a few months but it wouldn't be good for a general-purpose program.

I am not an EE, but...

[unfortunateson]

It would seem to me that the GPU is not going to be as general-purpose as the CPU, but could still attain the high mathematical throughput with vector-oriented processing.

Doing string searches, complex logic analyses, etc. would probably suck, but big data manipulations, such as SETI-style wave transformations, molecular analysis, etc., might be able to take advantage of them.

Fast Fourier Transform

[HalfFlat]

I'd love to see an FFT implementation (maybe it's not so hard ... will have to download and play with it.)

A lot of scientific code is constrained by how fast you can do an FFT, perhaps of arbitrary size. And a fast graphics card is a lot cheaper than a high-end processor.

For embarassingly parallel vector problems, this is just the sort of thing for cheap, powerful clusters based around a cheap PC and a fast GPU.

Re:Fast Fourier Transform

[Kazymyr]

Not to mention that you can put several PCI video cards in the same cheap PC. Multiply power by N.

Drawing text with GPU shader units?

[jonsmirl]

Has anyone tried drawing text with GPU shader units? It would work something like this:

1) Each character would have it's own shader program.
2) You would set the shader program, draw a rectange, and the character would appear.
3) The shader programs would be automatically generated by processing TrueType files.

To implement:
1) Break Truetype outline up into a number of convex curve segments.
2) Each of these curve segments would be represented as a set of constants in the shader program
3) For each pixel, test a line from pixel to an edge.
4) If the number of segments crossed is odd the pixel is black else white.
The algorithm can be refined to add antialiasing and hinting.

What you end up with is text that is clear at any resolution. The size of the text is controlled by the rectangle you draw it in. The text can also be clearly rotated and sheared.

An obvious optimization is to get the GPU vendors to add a shader instruction to do the calculation for which side of the bezier curve segment the current point lies.

While not important for games drawing text is critical for desktops. And we all know about the current trends to draw desktops with 3D hardware.

Re:The future is the past

[Total_Wimp]

PCI-X can fix this data bus in other ways as well. Motherboards come with one AGP slot, but PCI-X can and will provide many expansion slots.

Picture five high end GPUs on the motherboard eclipsing the single high-end cpu for a fraction of the price. Intel and AMD would be forced to cut the asking price of their products to compete. We could finally see some real four-way competition for "processors".

TW

Re:I've always wondered when this would happen...

[Animats]

But what I'm really looking forward to is a Physics specific processor that sits alongside the graphics processor, and is resposible for collisions detection.

It's been done. The Havok game physics system is available for the Playstation 2, and the physics is running in the vector processors, where most of the PS2's compute power resides.

Collision detection isn't that CPU-intensive. (This may surprise people not familiar with the field. But it's true. If collision detection is using substantial CPU time, you're doing it wrong.) Correct collision resolution is where the time goes.

Physics code works better with double-precision FPUs. You need both dynamic range and long mantissas to do it well. Some of the game consoles, and most of the GPUs, only have single-precision FPUs. It's possible to make physics code work in single precision, but fast-moving objects that cover considerable distance may have problems.

Re:Research

[BiggerIsBetter]

I (and presumably others) have asked some project leaders about this, but it seems to come down to testing and support of various cards. Also, remember that this is relatively unknown technology - Amiga blitting aside ;-) - you have to be pretty sure it's going to give accurate and consistent results before using it seriously. Find-A-Drug was my project of interest, and they have a Linux version too.

GPU use for scientific programming.

[kiniry]

Researchers at Caltech and other institutions have been looking at this for about three years. See "Sparse Matrix Solvers on the GPU: Conjugate Gradients and Multigrid" by Bolz, Farmer, Grinspun and Schroder (SIGGRAPH 2003), for example. The paper, illustrations, and movies are available from Dr. Grinspun's homepage. The primary problems with the approach at the time this work was done was the limited bandwidth of texture-related operations in OpenGL based upon improper assumptions in pipeline optimization.

Imagine a Beowulf Cluster... no, seriously

[billstewart]

There's a cluster of Sony Playstations at UIUC (BBC) that's using the Emotion Engine to do numbercrunching and running Linux on the main processors to do communications and I/O. It's probably not strictly Beowulf, because it's using the Playstation version of Linux.

This cluster has 70 Playstations (one article said that they'd ordered 100, but only 70 are in the cluster... Obviously the others are being used for "research".)

Re:AT&T DSP32 Cluster Supercomputer in late 80

[billstewart]

Yes, they were 25 MFLOPS. The chip had a 12.5 MHz cycle rate (I think that was also the clock speed), and each cycle could do a 32-bit multiply, a 32-bit add, and a 24-bit simple integer operation (some integer ops took multiple clocks, I think?)

Your music application sounds like fun. I didn't know anybody was still doing anything quite like that by 1990 - there was a whole range of people around John Cage's time who did lots of prepared piano stuff.

Some of the people who were trying to sell our multi-processor supercomputer flavor came up with a music studio application, doing lots of audio processing and mixing, sort of like your device turned inside out. Don't know if they sold more than one of them before the Lucent spinoff took them away.