This is from the BOINC log at startup:

3/11/2013 5:56:31 PM | | NVIDIA GPU 0: GeForce GTX TITAN (driver version 314.9, CUDA version 5.0, compute capability 3.5, 4096MB, 8384512MB available, 4989 GFLOPS peak)

3/11/2013 5:56:31 PM | | OpenCL: NVIDIA GPU 0: GeForce GTX TITAN (driver version 314.09, device version OpenCL 1.1 CUDA, 6144MB, 8384512MB available)

Strange. Only the OpenCL section is reporting the correct memory amount.

Operator

What's really strange is that the entire Kepler GeForce 600 range is actually OpenCL 1.2 capable, but the drivers only provide 1.1 functionality!

I think the Titan GPU is due a driver boost to better compete against the ATI cards in this area. Obviously the FP64 crippled 104 cards won't gain much if anything, but at least there is now a reason to support OpenCL 1.2.

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If you have a GeForce Titan, pending GPUGRID, the following projects are compatible,

Boinc

Collatz, Math
DistrRTgen, Math
WCG HCC GPU, Bio
Moo!, Math
Einstein, Astro
MilkyWay, Astro
Seti Beta, Astro

Folding @ Home, Bio

@+
*_*

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BTW: Moo! is not Math, is just brute-force cracking some meaningless encrypted message.

MrS

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Scanning for our furry friends since Jan 2002

Encryption is usually done with primes, and the calculation of prime numbers require a lot of mathematical calculations especially if one wants to calculate prime numbers very quickly.

L'encryptage est généralement effectué avec des nombres premiers, et le calcul de nombres premiers demandent beaucoup de calculs en mathématique surtout si on veut calculer des nombres premiers très rapidement.

@+
*_*

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All research uses maths, but using mathematics doesn't mean you're performing research!
Bottom line, it's a meaningless waste of electric and resources - a needless contribution to global warming.
It shouldn't be mentioned along side science, medicine or research.

Moo! is as batty as The Batty Bat

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The problem with the GeForce TITAN and GpuGrid a chance to be corrected?
I personally have tried almost all projects. But mostly I run projects that are devoted to biology and rotate with a GPU, GPUGRID, WCG HCC and Folding @ Home.
It's a shame not to be able to rotate GPUGRID.

Le problème de GpuGrid avec la GeForce TITAN à une chance d''être corrigé ?
Personnellement j'ai essayé pratiquement tous les projets. Mais je fais tourner principalement les projets qui sont consacrés à la Biologie et qui tournent avec un GPU, GPUGRID, WCG HCC et Folding@Home.
C'est dommage de ne plus pouvoir faire tourner GPUGRID.

@+
*_*

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Mmmm and they dare to say that ignorance does not breed stupidity.

All research uses maths, but using mathematics doesn't mean you're performing research!
Bottom line, it's a meaningless waste of electric and resources - a needless contribution to global warming.
It shouldn't be mentioned along side science, medicine or research.

Moo! is as batty as The Batty Bat

Encryption is usually done with primes, and the calculation of prime numbers require a lot of mathematical calculations especially if one wants to calculate prime numbers very quickly.

True, and that's what PrimeGrid does. Moo, on the other hand, simply uses a known and proven algorithm to find the key to a single message by chance.

@chris: you disagree with the quote from SK?

MrS

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Scanning for our furry friends since Jan 2002

Touching base, I think we're now past the deadlines mentioned.

Any update?

-- Craig

Any update?

Not forgotten, just preëmpted.

MJH

Any update?

Not forgotten, just preëmpted.

MJH

It wouldn't be the recent NOELIA WU's by any chance would it? ;-}

Since you folks got Titan(s) in your shop have you done any preliminary poking around to get an idea of what is making the current long WUs fail?

If so, is whatever the problem is completely fatal and requiring a complete rewrite of the program?

I've been toying with the idea of using the anonymous method to see if that would let me run long WUs.

I still don't know if the misreported memory total has anything to do with the failures but it doesn't seem to be affecting successful completion of tasks on Einstein. I have both Titans running 5 concurrent Einstein tasks each and it's running like a freight train.

Please let us Titan owners know as soon as you have something for us.

Thanks,

Operator

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I have both Titans running 5 concurrent Einstein tasks each and it's running like a freight train.

Interesting, it looks like the Titan is running about 35-40% slower than an HD 7970 with 5x WUs and around the same speed as an HD 7950, according to this chart at Einstein:

http://www.dskag.at/images/Research/EinsteinGPUperformancelist.pdf

Interesting, it looks like the Titan is running about 35-40% slower than an HD 7970 with 5x WUs and around the same speed as an HD 7950, according to this chart at Einstein:

http://www.dskag.at/images/Research/EinsteinGPUperformancelist.pdf

I don't even see a Titan on that list...

Interesting, it looks like the Titan is running about 35-40% slower than an HD 7970 with 5x WUs and around the same speed as an HD 7950, according to this chart at Einstein:

http://www.dskag.at/images/Research/EinsteinGPUperformancelist.pdf

I don't even see a Titan on that list...

It's not, but here's the 5x Titan results for you to peruse:

http://einstein.phys.uwm.edu/results.php?hostid=6889477&offset=0&show_names=1&state=3&appid=0

It's not, but here's the 5x Titan results for you to peruse:

http://einstein.phys.uwm.edu/results.php?hostid=6889477&offset=0&show_names=1&state=3&appid=0

Thanks. Hmm, interesting. I wonder where the bottleneck lies?

This is two EVGA Titan SC (air cooled) in a Dell T3500 WS with a Xeon W3565, 12GB, Win7Pro x64, and nothing else installed that isn't necessary to run BOINC/Apps.

Admittedly, BOINC still only sees 4096mb of the 6144mb of memory on the cards. I don't know if that has anything to do with it or not.

Operator

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Thanks. Hmm, interesting. I wonder where the bottleneck lies?

BRP4cuda32nv301 - they probably need to update their apps to better utilize the titan. Their apps were built for earlier GPUs, earlier cuda versions and compilers, so they are certainly not designed for Titans.

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They use CUDA 3, because their app fails with CUDA4-5. Apparently it should be a CUDA problem, that was acknowledged by nVidia, but wasn't fixed yet.

BRP4cuda32nv301 - they probably need to update their apps to better utilize the titan. Their apps were built for earlier GPUs, earlier cuda versions and compilers, so they are certainly not designed for Titans.

Thank you all for the recent information and observations regarding the GTX TITAN and CUDA crunching. I chose the TITAN SC for a single-gpu solution for a double-duty gaming and distributed computing box that would use less power than my previous pair of GTX 580 SCs. So far, it hasn't disappointed. If it crunches work units faster at some future date, so much the better ;)

I don't think the reported memory is the problem with Titan. The apps only use as much memory as necessary anyway, and 4 GB is still plenty (be it for 1 or 2 GPU-Grids or 5 Einsteins).

And regarding Titan and CUDA 3: each SMX is pretty much the same as for the other Keplers, just with some more features (more FP64 units etc.) and more registers. If these features are not being used, it should perform just as well as any other Kepler with this amount of shaders and clock speed.

MrS

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Scanning for our furry friends since Jan 2002