when the general consumer uses it .. think "digital compressed audio on a computer system" ..wtf ? now it's mp3 and everyone uses it. 80387 mathematical coprocessor?
for scientists only. a computer? who needs a personal computer? to quote one of my professors "back in the days, a personal computer was about as useful for a normal person as a space station for an old woman"
But in a sense that's what I'm saying. Where was the math coprocessor used first? And then it made to the public, it's the natural trend. When talking about Teslas or Larrabee as coprocessors is the same, they will mostly be used in supercomputers and supercomputers that are not so much super on their own, but yes compared to current top500. Later they might get to office computers, although that's very unlikely. In any case, ok, it's a niche market in the sense that very few people actually use them, but it's a very profitably one and at least AMD wil agree since it's been almost surviving from it the last years and Intel must been agreeing too when they created Larrabee almost for that purpose.
What I mean when I say GPGPU aren't going to be a niche market, I'm trying to say that they are not going to be any more niche than 8p Xeons or Opterons.
"Deskside supercomputer" is an oxymoron. It's not a niche market when Tesla cards infiltrate more than one market (not just HPC). Seeing as that is what they are solely engineered to do, Tesla will never leave that market. A mistake on NVIDIA's behalf. They created a niche product for a niche market when a normal GeForce should be able to do both without a problem.
What other market do you see for Tesla? There's none, for the consumer, who doesn't care so much about reliability or ECC, THE SAME chip/card is going to be used in GeForces and also in Quadros and the GPGPU functionality is going to be there. The 3 are essentially the same thing, just like a Phenom and 2p and 8p Opterons are almost exactly the same except for the quality requirements, support and yes the inflated prices associated with HPC sector.
They made a differentiation between GeForce and Tesla because 1-2 GB of vram is nowhere near enough for the tasks that a Tesla is supposed to run and 3-6 GB is just not profitable for a consumer GPU. Also ECC is a requirement for computing companies, but it comes with a performance and frame buffer penalty that wouldn't be wise to have on a GPU, hence the two products. And of course the price difference is also important. Intel and AMD sell their Xeon and Opteron chips at 5x-10x times the price, why wouldn't Nvidia want to do the same with Tesla?
Also a "deskside supercomputer" is probably the most interesting thing of all this GPGPU cards. Having something like 4-20 TFlops in your "desktop" computer is a dream for many scientists. How many R&D scientists have to wait weeks if not months in order to get access to some supercomputer time?
Many if not
most. Having a $6000 computer with 4-20 Tflops would help them a lot and increase productivity in research areas by unimaginable amounts. Same can be said for design and animation markets, architecture... the list is long believe me.