You make it sound like you can enable full power DP math on non-Titan GeForce chips. Let's get something perfectly clear. How many shaders and performance did this card have to dedicate to get that 1:3 DP math?
Precisely? Zero. Of the 2688 shaders on the chip,1792 are FP32 capable, 896 are FP32/64. There are
no dedicated FP64 shaders on the chip.
You also gimp SP math when you enable full speed DP math. At least the 7970 just does compute well regardless if its DP or SP.
Yes...looks very gimped.
Single precision:
Double precision:
You know, ECC memory is pretty important when you're doing compute applications.
The case for ECC with GDDR5. ECC is generally a province of pro graphics/math co-processors where error detection is critical. Obviously, Titan is being not being aimed at those markets- that is what Quadro and Tesla are for.
You know, for people who actually invest in Tesla and use it's features would think that not having MPI would suck because now it's that much harder to get more than one of them to work together. If Titan is designed for compute, it's designed to do it on its own because anything to allow it to scale or be truly reliable for compute has been gimped....
What I’m trying to say is that for the last week I’ve been having to fend off our CS guys, who upon hearing I had a GK110 card wanted one of their own. If you’ve ever wanted proof of just how big a deal GK110 is – and by extension Titan – you really don’t have to look too much farther than that....Titan, its compute performance, and the possibilities it unlocks
is a very big deal for researchers and other professionals that need every last drop of compute performance that they can get, for as cheap as they can get it. This is why on the compute front Titan stands alone; in NVIDIA’s consumer product lineup there’s nothing like it, and even AMD’s Tahiti based cards (7970, etc), while potent, are very different from GK110/Kepler in a number of ways. Titan essentially writes its own ticket here....As compared to the server and high-end workstation market that Tesla carves out, NVIDIA will be targeting the compute side of Titan towards researchers, engineers, developers, and others who need access to (relatively) cheap FP64 performance, and don’t need the scalability or reliability that Tesla brings -
Anandtech
If you start overclocking the GPU your results can't be guaranteed.
Titan doesn't allow overclocking when full rate FP64 is enabled for that precise reason:
The penalty for enabling full speed FP64 mode is that NVIDIA has to reduce clockspeeds to keep everything within spec. For our sample card this manifests itself as GPU Boost being disabled, forcing our card to run at 837MHz (or lower) at all times-
Anandtech
FP64 calculation is obviously slower than FP32, and requires much more power to run. Just as well the laws of physics are in play- a 90% improvement over Tahiti using less power is probably not something AMD would like to see extended.
ECC at least eliminates the concern for corrupted memory to a point.and as far as professionals who use the Tesla cards, I think they might be intested in spending the extra money knowing that they can have their compute scale using MPI and that memory is reliable (ECC)
Obviously, there are enough people who just require EDC than full ECC (I'll take the word of the Anandtech guys over a random here I think)...after all, EDC was good enough for every AMD GPU (ECC was implemented only with Southern Islands FirePro)
Also once again, most data centers won't be wanted a Titan to crunch, they will be wanting something that's more reliable and has the features they need
I don't think anyone is suggesting Titan will be used in this manner.
With all of that said, GK110 is a GPU that does DP math well when you enable it. I wouldn't go so far to say that it was designed for compute
If FP64 isn't compute (GPGPU) then what is it ?
If you could please list some applications that require double precision that
aren't considered compute ?
I think you'll find that most commercial applications (i.e.
compute orientated Maya and AutoCAD for instance) use a combination of single and double precision.
So, what you are trying to convey is that enthusiast gamers wont buy the card because it is too expensive, and GPGPU users wont buy the card because it lacks features...so no one will buy the card! (There aren't a whole lot of options left). So your analysis differs -and you have me believe, superior, to Anandtechs staff and Nvidias strategic marketing planners. Well, hopefully you're right and the price craters a few weeks from now.