Sure, there are K80s out there still, but they are not cost-effective HW
anymore in any way. They're 8 years old now. Anyone still using one will
see a huge speedup just buying a low-end replacement based on Turing or
Ampere (minus the obvious crypto nonsense).
So for AMBER 20/21, sure, it's worth legacy support, but for a rewrite, I
want virtual memory support and that doesn't happen until Pascal in 2016.
Is anyone still using CUDA 8 though?
On Sun, Apr 4, 2021 at 6:19 PM David A Case <david.case.rutgers.edu> wrote:
> On Sun, Apr 04, 2021, Scott Le Grand wrote:
>
> >CUDA 7.5 is a 2015 toolkit and SM 5.x and below
> >are deprecated now. SM 6 is a huge jump over SM 5 enabling true virtual
> >memory and I suggest deprecating support for SM 5 across the board. SM 7
> >and beyond alas mostly complicated warp programming and introduced tensor
> >cores which currently seem useless for straight MD, but perfect for
> running
> >AI models inline with MD.
> >
> >CUDA 8 is a 2017 toolkit. That's way too soon to deprecate IMO ...
>
> We currently (appear to) support CUDA versions 7.5 through 11.2, and SM 3.5
> through 8.0. (All CUDA versions are not compatible with all SM's, but
> allowed combinations are set by NVIDIA, not by us.)
>
> The argument for SM3 is that there are still K80's out there, although I
> think this must be less and less true. There certainly are GTX 980's still
> in use, and supporting SM5 would make sense if it doesn't cost anything.
> But I'm fine with dropping support for SM5 if it helps us with code
> development or maintenance. (If a future user really needs to run on older
> cards, they can stick with Amber20.)
>
> The CUDA experts should make the decisions here, not me.
>
> ...dac
>
>
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Received on Sun Apr 04 2021 - 21:00:02 PDT
