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About LinkBacksRead more.It can render at twice the speed of a Titan X in new versions of Adobe Premiere and Blender.
Read more.It can render at twice the speed of a Titan X in new versions of Adobe Premiere and Blender.
TWICE as fast? wow. Also reasonable price for dual GPU professional @ $999.
Nice job AMD.
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Be Careful on the Internet! I ran and tackled a drive by mining attack today. It's not designed to do anything than provide fake texts (say!)
Really wish the power connectors were on the back of cards again much like this one
which titan x....
Is it 2x16 or 1x32 for the 32GB of memory
Price is still pretty good though but I'd really like to see some proper benchmarks on this in the likes of vray-rt but just finding a opencl versus cuda benchmark is hard enough as it is.
Unless things have changed recently you'll only see 'the same performance' as a titan x in viewports (at least in the software I use) because very few if any have crossfire/sli support so the only time the performance will really be seen is with gpu rendering etc where cuda has far better support from software such as vray-rt (cuda performs better than opencl) and in a lot of cases opencl isn't even supported.
I will say that this just shows that the radeon pro is just a normal radeon with some certified drivers (which to be fair is normal) and no massive price inflation.... which ultimately shows just how much price gouging is going on by nvidia for their quadro range.
It doesn't matter if its 2x16 or 1x32... its for professional use, not crossfire, you can use both gpus independantly for 99.999999% of professional use, so they dont need to share ram anyway, so you effectively have a full 32GB.
It's 2x16 though.
No, you have 2x16GB....Originally Posted by tantaku
And for professional use it can make a difference, at least in my work scenarios, more memory means more data can be stored in the gpu memory rather than needing to call from ram/scratch and in some cases it actually limits what you can do, 3d rendering is a perfect example of this. Due to the current constraints with most software/hardware when using multiple GPU's it currently works to the smallest memory available (so in this case 16GB) and then in essence 'mirrors' the data on each gpu.
Nvidia does have unified memory options in the cuda code but it's not being used by a lot of the software I use and have seen but to be honest it's more about combining motherboard and gpu ram, although the new quadro gp100 does seem to be heading in the direction of merging gpu memory into one pool but thats considerably more expensive.
A desktop version for around £400 with 16Gb would be interesting.
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