[gmx-users] Short how-to for installing GROMACS with CUDA ...

[Szilárd Páll]

Hi,

On Thu, Dec 17, 2015 at 4:40 PM, Stéphane Téletchéa <
stephane.teletchea at univ-nantes.fr> wrote:

> Le 17/12/2015 12:16, Szilárd Páll a écrit :
>
> Dear Szilárd,
>
>> Stéphane,
>>
>> On Wed, Dec 16, 2015 at 6:21 PM, Téletchéa Stéphane <
>> stephane.teletchea at univ-nantes.fr> wrote:
>>
>> >Dear all,
>>> >
>>> >I have struggled recently in getting gromacs-aware of cuda capabilities.
>>> >After searching for a "while" (one afternoon), I removed the
>>> >ubuntu-provided
>>> >drivers and packages (which worked in the past) and installed everything
>>> >"from scratch".
>>>
>>  From your article:
>> "It seems that with very recent revisions of gromacs it is not possible
>> anymore to use the bundled NVIDIA packages from the official Ubuntu
>> repositories. "
>>
>> The "incompatibility" can only come from a driver-runtime mismatch or
>> broken installation, IMO. There is no incompatibility, at least not that I
>> know of.
>>
>
> Well, this is what I thought also, but nvidia-smi worked correctly, and
> cuda examples
> too, so it seems gromacs is more sensitive to the minor number (352.63 in
> ubuntu repositories,
> 352.39 in the cuda driver bundled with the cuda package).
>

I have never encountered cases where GROMACS would be "more sensitive" than
other codes, e.g. an SDK sample.
Secondly, normally there should not be any explicit dependence of GROMACS
binaries on NVIDIA driver components. Binaries get linked against
libcudart, the CUDA runtime part of the toolkit installation (I suggest you
verify that with ldd, IIRC some older cmake did link against libcuda.so
too). Hence, any dependence on the driver version _should_ only be indirect.


>
> If you wish I can try to reproduce with more debug information, but this
> is what led me to
> the article, because other cuda-aware codes seemed to not be affected.


That would be useful, both to satisfy my.our curiosity and beneficial for
the community to know where the pitfalls are.
I suggest you purge your NVIDIA driver and toolkit and start with fresh
copy. Note that if you do not purge your NVIDIA driver installed through
the binary blob before installing the packages, you will get some
components overwritten and potentially end up a big mess. Same can happen
with the toolkit.

--
Szilárd


>
>
>> If your installation works, e.g. if i) nvidia-smi works and lists your GPU
>> (meaning that the driver works) ii) you can compile and run CUDA SDK
>> examples (meaning that the CUDA runtime works and it's compatible with the
>> driver) , GROMACS should work too!
>>
>
> Well, no. We can dig on this if you wish, it seemed gromacs for more
> "sensitive"
> to other cuda codes, but I can provide details if you wish (and open a bug
> report).
>
>
>> I suggest you add these two steps to your article because they are quite
>> essential in diagnosing whether there is something wrong with the driver
>> or
>> the runtime (/runtime-driver combo).
>>
>
> Well, this seemed weird to me also, but the point is that previously I
> could use
> the binaries from the ubuntu repositories and get the proper cuda-aware
> gromacs
> and with the recent packages this is no more the case.
> I'm building gromacs with the same scripts as I'm using since 2007, just
> adjusting paths
> or option as they evolve, but this is the first time I have to dig that
> much. It may be a
> side effect (from the ubuntu packages), but from their repository the
> files were properly
> package I think. Again, I can go into details in a bug report if needed.
>
>
>>
>> >It seems this is both coming from NVIDIA requiring the
>>> >"GPU deployment kit" in addition to the cuda toolkit, and from GROMACS
>>> >only warning about the missing NVML (but not failing while asking for
>>> GPU
>>> >compilation).
>>> >
>>>
>> Note that NVML is*recommended*  but not mandatory and used to control the
>> application clocks on the GPU. Note that you can set the applicaiton
>> clocks
>> manually with nvidia-smi.
>> (For more details see this blog post by Jiri Kraus:
>>
>> http://devblogs.nvidia.com/parallelforall/increase-performance-gpu-boost-k80-autoboost/
>> )
>>
>
> Many thanks for the link, i only read the NVML description page, and got
> more or less
> to the conclusion that it *should* be helpful, this may also lead to more
> lock-up I think in real
> scenarios where dust enter the fan (on personal workstations like in my
> case for instance),
> but I'll see from experience.
>
> I'll add a note about this, thanks for the feedback
>
>
>> Cheers,
>> --
>> Szilárd
>>
>
> Best,
>
> Stéphane
>
>
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