[paulmd]

Do you need FP64? If so, right now the OG GTX Titan is the default choice - it offers full double-precision performance with 6 GB of VRAM. There's nothing better south of $3000.

If not, the 980 Ti or Titan X offer excellent deep learning performance, albeit only at FP32. And their scheduling/preemption is not entirely there, they may not be as capable of Dynamic Parallelism as Kepler was. The 780 Ti is actually a more capable card in some respects.

The new consumer Pascal cards will almost certainly not support FP64, NVIDIA has considered that a Quadro/Tesla feature since the OG Titan. If DP performance is a critical feature for you and you need more performance than an OG Titan will deliver, you want the new Tesla P100 compute cards, and you'll have to convince NVIDIA you're worthwhile and pay a 10x premium for it if you want it within the next 6 months. But they probably will support compute better, although you should wait for confirmation before spending a bunch of money...

For VR stuff or deep learning, the consumer Pascal cards sound ideal. Get a 1070 or 1080, definitely. The (purportedly) improved preemption performance alone justifies the premium over Maxwell, and the FP16 capability will significantly accelerate deep learning (FP16 vs FP32 is not a significant difference in overall net output in deep learning).

[haristo]

Question following up on the remark "Do you need FP64? If so, right now the OG GTX Titan is the default choice"

I am purely after FP64 performance for scientific compute.

a) what does the "OG" stand for? b) what about the titan black model? seems to offer yet a bit more FP64 performance than the normal Titan?

[viperscape]

nothing better south of 3k$? does that include the new amd duo pro? or is that just useful for VR?

[paulmd]

The AMD Pro Duo seems aimed at the workstation/rendering market rather than the compute market.

NVIDIA is totally dominant in the compute market. They have an enormous amount of software running on CUDA that you would be locking yourself out of with AMD, and since NVIDIA has such a dominant share of the compute hardware you would also be tuning for what amounts to niche hardware.

AMD has recently been working on getting a CUDA compatibility layer working, hopefully this will improve in the future.