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NVIDIA To Push Into Supercomputing
RedEaredSlider writes "NVIDIA outlined a plan to become 'the computing company,' moving well beyond its traditional focus on graphics and into high-profile areas such as supercomputing. NVIDIA is making heavy investments in several fields. Its Tegra product will be featured in several mobile devices, including a number of tablets that have either hit the market already or are planned for release this year. Its GeForce lineup is gaming-focused while Quadro is all about computer-aided design workstations. The Tesla product line is at the center of NVIDIA's supercomputing push."
begins to learn at a geometric rate. It becomes self-aware at 2:14 a.m. Eastern time, August 29th. In a panic, they try to pull the plug.
I just hope enough nuclear power plants come online before their first supercomputer customer turns on a new rig. The latest GPUs already use more power than the hungriest Intel or AMD x86 ever did.
I'm nowhere as qualified as everyone here, but Nvidia seems to be pushing more for the pararell supercomuting with rows of Tegra chips working in unision. They had talked about supercomputing when the Tegra 3 was announced.
version 2
"I use a Mac because I'm just better than you are."
Let us know why you think this is a bad idea.
I think it's a great idea. Intel keeps putting out chipsets with video on-board, and this has to hurt nVidia's core business. If they make inroads into other areas where Intel is now dominant, and can do it without going broke, then that puts them in a nicer position.
W..w..W - Willy Waterloo washes Warren Wiggins who is washing Waldo Woo.
Look, I apologize if I offended you in any way, ok? There's no need for such languages.
The company that was setup by disgruntled Silicon Graphics gfx division employees because the SGI gfx tech was suffering from toxic internal politics and the push into Big Iron and Storage... is now moving into 'Supercomputing'. Hope they bring back the Cube Logo :)
I doubt it would be truly useful, but I'd like to see a 2 million core processor. Arrange in, let's see, a 1920 x 1080 grid. The 8008 used 3500 transistors per core, so even before memory, it'd be a 7 billion transistor chip.
More practical might be a 128 x 128 core processor, using a modified 386 or 68020 for cores. That could be less than 5 billion transistors. Each processor is simple and well known enough that hand optimized assembly begins to make sense again.
Run the little bastard at just 1 GHz and your might be able to get 16 trillion calculations per second.
Something that specialized could make a handy co-processor for graphics, video, scientific crunching.
Won't happen, but I've got time to kill speculating.
The world is made by those who show up for the job.
Didn't their licenses expire on some bus or other preventing them from making chipsets for intel CPUs? The press release I saw said the recent $1.5b deal excluded certain chipsets. They probably aren't too interested in making AMD chipsets these days. Large racks of MIPS/ARM CPU & Fermi GPU systems makes sense to me. Top-end graphics cards will die off soon thanks to consoles & hollywood. Even multi-monitor gaming wont slow that by much. In a generation or two even low-end graphics cards will probably have the power to play 1080p games at full detail.
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I can NOT fucking believe there was not already a troll account called moderators long, long, LONG before UID 2M.
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
"Supercomputing" almost always means "massive Linux deployment and development." I will spare critics the wikipedia link on the subject, but the numbers reported there almost says "Supercomputing is the exclusive domain of Linux now."
Why am I offended that nVidia would use Linux to do their Supercomputing thing? Because their GPU side copulates Linux users in the posterior orifice. So they can take, take, take from the community and when the community wants something from them, they say "sorry, there's no money in it." We need a revision to the GPL -- that'd shut their Supercomputing project down really fast if there were some sort of verbage that says "if you shun Linux users and at the same time make extensive use of Linux for yourself, you can't use it." I know that would never happen and would probably be a very bad idea for reasons I don't want to consider right now. I just hate that nVidia and their damned Optimus technology serves no purpose but to lock Linux users out of using their own hardware.
3 of the Top 5 supercomputers are already using NVIDIA GPUs:
NVIDIA press release
Bill Dally outlined NVIDIA's plans for Exascale computing at Supercomputing in Nov 2010:
Bill Dally Keynote
+100
My favourite is when idiots who find tech support to be a challenging career option talk about the latest strategies of any big corporation like they are some important analyst, using sentences like: "My take on this is..." or "I don't see this happening..."
Always bet against the prevailing Slashdot opinion on any technology. Nine times out of ten, you'll come out ahead.
Low end cards already have that ability. I play games on my aging laptop that has a 8600M GT flawlessly at 1920x1200. "1080p" isn't that impressive of a resolution for PC games.
In a generation or two even low-end graphics cards will probably have the power to play 1080p games at full detail.
I suspect you are right, and that there will be a race for power efficiency like there is today on tablets/phones. "High end" will still exist, but the definition will change to power/performance rather than just raw performance.
And of course, powerful video cards will always be appreciated in the rendering world.
W..w..W - Willy Waterloo washes Warren Wiggins who is washing Waldo Woo.
They could be looking down the pipe and seeing that the market for their flag ship product is in trouble. The market will move to cheaper more generic solutions.
Perhaps they are seeking to flee to some kind of high tech, high margin product that suits their existing infrastructure. The problem with super computers is that they have to take market share from the existing players.
Their behavior looks something like a company fleeing up-market from a disruptive technology. http://en.wikipedia.org/wiki/Disruptive_technology Too bad. That usually ends in tears.
One thing I've been really keen to know is what the utilisation is like on those supercomputers. We know they can do LINPACK really fast and more efficiently than the CPUs do, that's what you get for having a high ALU density, a few threads per core and wide SIMD structures. The question is: out of the algorithms that people intended to run on those supercomputers, then what level of efficiency are they hitting.
Are they still a net gain over a standard opteron-based machine? They may be, but I don't know the answer. What I heard about Roadrunner with its Cell chips was not so good.
I've been working with their GPGPU push for a couple of years now. What I notice is they are very good at data parallelism with highly regular data access patterns and very few branches. While they are technically general purpose, they don't perform well on a large portion of high performance tasks that are critical even in scientific computing which are generally compute-bound. This creates some really annoying bottlenecks that simply cannot be resolved. They can give tremendous speedup to a very limited subset of HPC tasks, but others are left in the water, and since these things usually are all coupled into a single code your only choice is to move back and forth between GPU and CPU frequently which initiates a data throughput bottleneck (data transfer from RAM to GPU is very slow).
On real tasks it is not uncommon to only receive say 2X speedup, where the programmer time involved was increase exponentially. For a lot of my work I'd rather to just do traditional MPI with multiple CPUs.
The kid obviously has a bright future ahead of him. He's got moxy.
which is totally what she said
The current line up of AMD GPUs have far more stream processors than the NVIDIA models, and run at roughly the same clock speed. Why would anybody buy the NVIDIA ones?
In a generation or two even low-end graphics cards will probably have the power to play 1080p games at full detail.
They do already, so long as you're playing games from 2003. The reason why you can play many modern games on max settings on mid-range cards is that those games have been crippled for the console market and simply cannot benefit from the power of a high-end card.
"1080p" isn't that impressive of a resolution for PC games.
Exactly but because most newer games are made with 'console capable' engines designed to run on 1080p you'll see less and less games making
use of the extra power PCs have (especially as not everyone has higher spec pcs). The same is true for console games with most games being
designed for xbox360 capabilities and not as much effort into improving that for ps3 gameplay.
Its not entirely a bad thing as there is a very small chance some of that effort might be re-channelled into improving gameplay and not just louder/prettier
cutscenes and quick time events. Probably not but I can dream.
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They chose to not release the necessary specs to allow others to utilize their hardware the way Intel and to a lesser extent AMD did, and as the current smartphone trend has shown, locked in is the same as being locked out.
Time is what keeps everything from happening all at once.
I'm sorry if nvidia won't gut their business to satisfy your irrational request.
“Common sense is not so common.” — Voltaire
I show step-by-step how you can setup your own “Super computer cluster” using Ubuntu MPI Cluster from multiple machines with the goal of bruteforcing strong encrypted passwords with John the Ripper for academic purposes.
http://www.petur.eu/blog/?p=59
http://en.wikipedia.org/wiki/Amdahl's_law Really, can anyone educated enough to do scientific programming NOT know what to expect?
1024x768 wasn't wide enough to play the graphical version of Nethack without scrolling. 1280x1024 is almost but not quite enough, and 1440 or above works just fine.
Of course, 24x80 was enough for the real version.
Bill Stewart
New Fast-Compression-only CPR http://preview.tinyurl.com/dy575ks
... when GPGPU was in its infancy and I was lusting to play with that stuff; that's about 5 yrs ago, at most.
Alas, our semiconductor department was so content with its orthodoxy and cluster running Fortran WTF hairballs... :`( :>
Ah well, no point crying over that spilt milk... it just takes patience and pig headedness...
Mi domando chi à il mandante di tutte le cazzate che faccio - Altan
This sounds suspiciously like Silicon Graphics's shift from its beginning as a graphics workstation company to become a supercomputing company. It made the successful Origin line of big iron, used to own Cray, and still peddles their Altix products. Moore's Law has turned the crank a few times, but the "graphics to performance computing" change has a mighty familiar ring to it.
I bought an ATI card (HD 3800) and its Linux driver sucks, I can't use it for gaming or 3d arts. (If I try to run blender, it won't display some menu elements, and looks totally broken.) It only works decently on Windows. So the funny thing is, I can't use an opensource software (Blender) with a video card that's supposedly opensource friendly on an opensource operating system (Linux; I tried it with several distros).
The funny thing is that only nVidia and Intel have decent drivers for Linux. So it's not about a few more FPSes.
Double-precision linpack performance increase over a CPU-only system is ~288GFLOPS per Tesla M2050 card (up to 4 cards per system - adding more doesn't help without going to exotic motherboards. See news report of IBM study). Raw performance is 515GFLOPS/card (double precision), so you're looking at ~56% utilization. Others report 53% overall on a massively parallel setup ( See: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5470353 )
A rough rule of thumb for linpack double-precision is 25% of the theoretical single-precision performance. The gain is 4-8x over a standard processor depending on whether the metric is peak performance, performance/$ or performance/W. If you can live with 1.5GB non-ECC (GTX480), then it's about 8-32x gain depending on what you're comparing it to. Some applications will see a smaller gain, some larger. If it's matrix math under the hood, then linpack should be in the ballpark.
See gpgpu.org for papers and news on different applications.
"Is life so dear, or peace so sweet, as to be purchased at the price of chains and slavery?" - Patrick Henry
If we all buy AMD's product on the virtue of their openness, it won't be long before AMD holds the upper hand on features and stability. I think they're heading in a good direction already.
How much entrenched advantage does inferior need before you lock in? Your personal FIR filter on "what have you done for me lately" seems to have unit delay of hours rather than years.
In order to ensure the NVIDIA GTX graphics card you have purchased can't be used for economical general purpose supercomputing NVIDIA has disabled 75% of its double floating point execution units.
In the GeForce family, double-precision throughput has been reduced to 25% of the full design.
Can anyone come up with a worse example of deliberate sabotage of hardware for product differentiation purposes? AMD doesn't cripple their double floating point performance.
Yes, I've seen the stats for linpack. The stats for linpack on Roadrunner were good, too, and yet I was constantly hearing from national labs people how disappointing the utilisation was for any real-world apps. You're quite right, though, it depends a lot on how many of the apps are matrix driven.
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The biggest supercomputing company is always the next one to fail ... think about it ... CDC ... Cray ... SGI ... NVIDIA next?
I missed my chance to invest in NVIDIA in 2001 when a friend of mine from SGI said, "This company is going to beat all the others in 3-D graphics because they hired the right guys out of SGI" - and I ignored him. Now it appears that if those ex-SGI employees are heading back into the supercomputing business, then perhaps my friend was wrong after all ... they hired the wrong guys out of SGI !!!
Nvidia linux support is getting fixed by nouveau anyway. They reckon the GTX 5xx/4xx series is already upto the same level as the 2xx/9xxx/8xxx cards for drivers. As more resources get spent implementing opengl features in gallium and less on reverse engineering the cards, feature parity with the closed drivers will be achieved. I reckon in 1-2 years Nvidia card open source support will be at near parity with the closed source drivers.
It's obviously a bad idea because it makes you extremely stressed out, which in turn reduces your life expectancy.
Other than that GPGPU's are great for certain things, like supercomputers are good for certain things.
Why did you came here to post that anyway?
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