News Intel has answers to CUDA

[Tim S]

http://www.bit-tech.net/news/2008/04...wers_to_cuda/1

IDF SPRING 08: Intel's researchers talked about a new parallel programming model called Ct - it's designed to make threading exceptionally easy.

[Mentai]

If this is as amazing as they say it is, and they release a discrete GPU leaps and bounds ahead of the competition (which I see as possible considering the lackluster 9800GTX), then I'm very excited. Always good to have more competition and have nvidia play catch up again.

Hopefully the driver support will be up to scratch as well.

[Nikumba]

I cant remeber where I read it, but will have a look, but there was an article on how Intel were looking at the discrete GPU market, and could probally just stick a C2D on a card, with some GDDR and relase it.

If that was the case, would be cheaper than ATI/nVidia I am sure and better performing

[Xtrafresh]

finally something interesting. I'd really like a third company to take a stab at making GPUs. Not that we dont have enough good GPUs in the grey zone, but it's always nice to see more

[Laitainion]

Originally Posted by Nikumba

I cant remeber where I read it, but will have a look, but there was an article on how Intel were looking at the discrete GPU market, and could probally just stick a C2D on a card, with some GDDR and relase it.

If that was the case, would be cheaper than ATI/nVidia I am sure and better performing

Hate to burst your bubble, but a C2D (no matter how you clock it) could *ever* be a faster graphics processor than anything in current generation nVidia or ATi have out. It simply isn't designed to to be a massively parallel, floating point monster of doom. It would also need a seperate memory controller for the GDDR3, which would have to talk to the C2D over an FSB crippling the bandwidth and memory performance.

[chicorasia]

In the meantime, nVidia has quietly released CUDA for OSX.

[Anakha]

Y'Know, I'm amazed no-one's made this interesting (And more than a little ironic) leap yet.

CUDA enables developers to calculate massively parallel tasks.
Ray-Tracing is a massively parallel task.

Ergo, CUDA is perfect for raytracing.

I mean, seriously. Ray-Tracing, at it's heart, is a very simple equation that needs to be done many, many times (2 or 3 times per pixel). With 128 cores working on it at a high rate of speed (Say, a single GeForce 8800 GT), it would still be miles faster (And cheaper) than using C2D's (Or, as was demonstrated by the OpenRT guys, a massive network of 16 C2Ds).