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GPUs To Power Supercomputing's Next Revolution
evanwired writes "Revolution is a word that's often thrown around with little thought in high tech circles, but this one looks real. Wired News has a comprehensive report on computer scientists' efforts to adapt graphics processors for high performance computing. The goal for these NVidia and ATI chips is to tackle non-graphics related number crunching for complex scientific calculations. NVIDIA announced this week along with its new wicked fast GeForce 8800 release the first C-compiler environment for the GPU; Wired reports that ATI is planning to release at least some of its proprietary code to the public domain to spur non-graphics related development of its technology. Meanwhile lab results are showing some amazing comparisons between CPU and GPU performance. Stanford's distributed computing project Folding@Home launched a GPU beta last month that is now publishing data putting donated GPU performance at 20-40 times the efficiency of donated CPU performance."
I was thinking about the question of what makes GPUs so great..
.. What is it that a CPU does that a GPU doesn't?
.. I know .. run windows.
I thought
Oh yeah
*I'm kidding I'm kidding*
One more step toward GPU Raytracing. We're already pushing rediculous numbers of polygons, with less and less return for our efforts. The future lies in projects like OpenRT. With any luck, we'll start being able to blow holes through levels rather than having to run the rat-maze.
Javascript + Nintendo DSi = DSiCade
Let me see if I have this down right: With the progress of multi-core CPU's, especially looking at the AMD / ATI deal, PC's are moving towards a single 'super chip' that will do everything while phasing out the use of a truly separate graphics system. Meanwhile, supercomputers are moving towards using GPU's as the main workhorse. Doesn't that strike anybody else as a little odd?
Unpleasantries.
Simple video games that run ENTIRELY on the GPU- mainly for developers. Got 3 hours (or I guess it's now going on 7 hours) to wait for an ALTER statement to a table to complete, and you're bored stiff? Fire up this video game, and while your CPU cranks away, you can be playing the video game instead with virtually NO performance hit to the background CPU task.
SJW: a person who perceives an injustice, and while correcting it, commits a greater injustice.
Great now Homeland Defence is going to buy up all the graphics cards to prevent their dangerous computing power from falling in the hands of evil script kiddies trying to crack your hotmail account...
"Serious" computers won't come with fewer than 4 16x PCI-E slots for hooking in "scientific processing units"...
We used to tell our boss that we were going to do stress-testing when we stayed late to play Q3, this takes that joke to a whole new level.
Oh, you're not stuck, you're just unable to let go of the onion rings.
"I thought .. What is it that a CPU does that a GPU doesn't?"
GPUs have dedicated circuitry to do math, math, and more math - and to do it *fast*. In a single cycle, they can perform mathematical computations that take general-purpose CPUs an eternity, in comparison.
Oh, you're not stuck, you're just unable to let go of the onion rings.
NVIDIA announced this week along with its new wicked fast GeForce 8800 release the first C-compiler environment for the GPU
"Wicked fast" GPU? And a compiler?
Sounds like a Boston C Party.
I want to drag this out as long as possible. Bring me my protractor.
The 8800 looks like the first GPU that really enters the realm of the old fashioned supercomputing architectures pioneered by Seymour Cray that I cut my teeth on in the mid 1970s. I can't wait to get my hands on their "C" compiler.
Seastead this.
Excellent news! Below is the link, registration required, for the New York Times. I will try to paste the article.
Second. Anyone out there working on books that have examples? Please reply with any good 'how to' sources.
Source: http://www.nytimes.com/2006/11/09/technology/09chi p.html?ref=technology
SAN JOSE, Calif., Nov. 8 -- A $90 million supercomputer made for nuclear weapons simulation cannot yet be rivaled by a single PC chip for a serious video gamer. But the gap is closing quickly.
Indeed, a new breed of consumer-oriented graphics chips have roughly the brute computing processing power of the world's fastest computing system of just seven years ago. And the latest advance came Wednesday when the Nvidia Corporation introduced its next-generation processor, capable of more than three trillion mathematical operations per second.
Nvidia and its rival, ATI Technologies, which was recently acquired by the microprocessor maker Advanced Micro Devices, are engaged in a technology race that is rapidly changing the face of computing as the chips -- known as graphical processing units, or G.P.U.'s -- take on more general capabilities.
In recent years, the lead has switched quickly with each new family of chips, and for the moment the new chip, the GeForce 8800, appears to give the performance advantage to Nvidia.
On Wednesday, the company said its processors would be priced at $599 and $449, sold as add-ins for use by video game enthusiasts and for computer users with advanced graphics applications.
Yet both companies have said that the line between such chips and conventional microprocessors is beginning to blur. For example, the new Nvidia chip will handle physics computations that are performed by Sony's Cell microprocessor in the company's forthcoming PlayStation 3 console.
The new Nvidia chip will have 128 processors intended for specific functions, including displaying high-resolution video.
And the next generation of the 8800, scheduled to arrive in about a year, will have "double precision" mathematical capabilities that will make it a more direct competitor to today's supercomputers for many applications.
"I am eagerly looking forward to our next generation," said Andy Keane, general manager of Nvidia's professional products division, a business the company set up recently to aim at commercial high-performance computing applications like geosciences and gene splicing.
The chips made by Nvidia and ATI are shaking up the computing industry and causing a level of excitement among computer designers, who in recent years have complained that the industry seemed to have run out of new ideas for gaining computing speed. ATI and Advanced Micro Devices have said they are working on a chip, likely to emerge in 2008, that would combine the functions of conventional microprocessors and graphics processors.
That convergence was emphasized earlier this year when an annual competition sponsored by Microsoft's research labs to determine the fastest sorting algorithm was won this year by a team that used a G.P.U. instead of a traditional microprocessor. The result is significant, according to Microsoft researchers, because sorting is a basic element of many modern computing operations.
Moreover, while innovation in the world of conventional microprocessors has become more muted and largely confined to adding multiple processors, or "cores," to single chips, G.P.U. technology is continuing to advance rapidly.
"The G.P.U. has this incredible memory bandwidth, and it will continue to double for the foreseeable future," said Jim Gray, manager of Microsoft's eScience group.
Although the comparison has many caveats, both computer scientists and game designers said that Nvidia GeForce 8800 had in some ways moved near the realm for the computing power of the supercomputing world of the last decade.
The fastest of thes
The addition of a C compiler, drivers specific to GPGPU applications and available for linux (!) as well as XP/Vista means that this is going to be seeing widespread adoption amongst the HPC crowd. There probably won't be any papers on it published at SC06 in Florida next week, but over the next year there probably will be a veritable torrent of publications (there already is a LOT being done with GPUs). The new architecture really promotes GPGPU apps, and the potential performance/$ especially factoring in the development time which should be significantly less with this toolchain. A couple 8800GTXes in SLI and I could be giving traditional clusters a run for their money when it comes to apps like FFTs etc. I can't wait till someone benchmarks FFT performance using CUDA. If anyone finds such numbers post and let me know!
"Let me see if I have this down right: With the progress of multi-core CPU's, especially looking at the AMD / ATI deal, PC's are moving towards a single 'super chip' that will do everything while phasing out the use of a truly separate graphics system. Meanwhile, supercomputers are moving towards using GPU's as the main workhorse. Doesn't that strike anybody else as a little odd?"
16789087
I picture this:
Before:
CPU makers: "Hardware's expensive, keep it simple."
GPU makers: "We can specialize the expensive hardware separatly!"
Now:
CPU makers: "Hardware's cheaper and cheaper, lets keep up our profits by making our more inclusive."
GPU makers: "We can specialize the cheap hardware in really really big number-crunch projects!"
btw, why isn't the reply button showing up? I'm too lazy to hand type the address.
Demented But Determined.
They "CUDA" come up with a better acronym.
Google "Dominik Goeddeke" and read his GPGPU tutorial. It's excellent, as far as tutorials go, and helped me bootstrap.
Ok, ok, here's the link...
You're confusing your technologies. The RAM used on video cards these days is effectively the same RAM you use with your CPU. The memory cannot lose data or very bad things will happen to the rendering pipeline.
What you're thinking of is the intentional inaccuracy of the floating point calculations done by the GPU. In order to obtain the highest absolute graphical performance, most 3D drivers optimized for gaming attempt to drop the precision of the calculations to a degree that's unacceptable for engineering uses, but perfectly acceptable for gaming. NVidia and ATI make a lot of money by selling "professional" cards like the Quadro and the FireGL to engineering companies that need the greater precision. A lot of the difference is in the drivers (especially for the low-end models), but the cards do often have hardware technologies better suited to CAD-type work.
Javascript + Nintendo DSi = DSiCade
"GPUs have dedicated circuitry to do math, math, and more math - and to do it *fast*. In a single cycle, they can perform mathematical computations that take general-purpose CPUs an eternity, in comparison."
Sounds like there is a lot of untapped potential. I propose we move GPUs off the external cards, and give them their own dedicated spot on the motherboard. Though, since we will allowing it be used for more general applications, we could just call it a Math Processor. Then again, it's not really a full processor like a duel core, so, we'll just call it a Co-Processor. This new "Math Co- Processor" will revolutionize PCs like nothing we have ever seen before. Think of it, who would have thought 20 years ago we could have a whole chip just for floating point math!