Quote from: bcp19 on September 07, 2013, 03:04:37 PM

Quote from: ReCat on September 06, 2013, 09:28:34 PM

Quote from: wyldfire on September 06, 2013, 07:51:43 PM

Quote from: ReCat on September 06, 2013, 07:44:25 PM

Quote from: refer_2_me on September 06, 2013, 06:04:26 PM

Any word on getting this to work on NVIDIA cards? From what I understand it's because the nvidia cards don't support opencl 1.2 (yet?). Any potential workarounds on windows or linux?

NVIDIA is poor at doing anything GPGPU.

Wha..?! No way! NVIDIA has a huge advantage over AMD in many aspects. Just look at how well their software works compared w/AMD's. You still need an X server running to do computation with AMD GPUs and that totally blows.

NVIDIA made a poor (IMO) strategic decision by abandoning OCL but you still have to give them the credit for creating it! I think they were afraid to abandon their early adopter CUDA customers and decided they didn't have the throughput to support both.

I think eventually they'll reverse their position on OCL. But to a lot of folks doing GPGPU they don't care about OCL and they're using CUDA and loving it. So it's not fair to say "NVIDIA is poor at doing anything GPGPU" IMO.

OpenCL Trademarks belong to Apple Corp. I dont think Nvidia made OpenCL.

They might be good at GPGPU, but only on the GPU's that specialize in it. ie. Their tesla series. The consumer GPU's they make aren't as good.. but they are also the vast majority.

Idk.

All I know is that the GPGPU software I've seen out there runs tons faster on ATI cards than it does on NVIDIA cards.

CUDA would work very well for this type of computing. Over on Mersenne.org, they have had CUDA based programs to run the Lucas-Lehmer tests for quite some time now while the OPENCL crowd have barely gotten one functioning and at nowhere near the speed of CUDA.

In trial factoring work, a GTX590 using CUDA puts out 681.6GHz Days of work per day compared to a 7990 using OPENCL putting out 748.7. On sha-256 the 590 is ~190 to the 7990's 1200+. Porting the OPENCL to CUDA will not be an easy task, but I'd bet the result would surprise you.

It's not very much of a surprise. I realize how different architectures can specialize in different types of tasks and have a significant advantages with them. I was just going by the little information I have seen about it, which I guess did not fully explain the situation.