gpu24 and gpu25 added to the cluster

[Viraj Mehta]

Hmm, I don't see those available on the NVIDIA site. That being said, I
tested my code that runs using CUDA/CUDNN on other GPU machines and it
doesn't find these GPUs. So perhaps I missed something, I'll look around.

Viraj

On Fri, Dec 17, 2021 at 12:41 PM Predrag Punosevac <predragp at andrew.cmu.edu>
wrote:

> I just installed the RPM provided by you. However I am not sure that this
> is the correct RPM. In the past I used to install something like
>
>
>
> libcudnn8-8.1.1.33-1.cuda11.2.x86_64.rpm
> libcudnn8-devel-8.1.1.33-1.cuda11.2.x86_64.rpm
> libcudnn8-samples-8.1.1.33-1.cuda11.2.x86_64.rpm
>
> On Fri, Dec 17, 2021 at 11:13 AM Viraj Mehta <virajm at cs.cmu.edu> wrote:
>
>> Hi Predrag,
>>
>> This should be sitting in the scratch. Let me know if there are any
>> issues.
>>
>> Cheers,
>> Viraj
>>
>> On Fri, Dec 17, 2021 at 9:38 AM Predrag Punosevac <
>> predragp at andrew.cmu.edu> wrote:
>>
>>> Yes. Please get me 5 RPS for RHEL 8.1 and put them in your scratch on
>>> GPU24. Make sure they are for 64 bit AMD/Intel. They have them for ARM and
>>> Power architecture.
>>>
>>> On Fri, Dec 17, 2021, 10:31 AM Viraj Mehta <virajm at cs.cmu.edu> wrote:
>>>
>>>> Hey Predrag,
>>>>
>>>> I can get it for you. Out of the options listed in the attached image,
>>>> which one would make sense to install? I was thinking the RHEL x86  version
>>>> would be most appropriate.
>>>>
>>>> Best,
>>>> Viraj
>>>>
>>>>
>>>>
>>>> On Fri, Dec 17, 2021 at 9:10 AM Predrag Punosevac <
>>>> predragp at andrew.cmu.edu> wrote:
>>>>
>>>>> It is not installed right now. It is proprietary software and I have
>>>>> to locate my NVIDIA developer credentials to get RPS. If someone can
>>>>> download it quickly for me I will install it.
>>>>>
>>>>> On Fri, Dec 17, 2021, 9:11 AM Ifigeneia Apostolopoulou <
>>>>> iapostol at andrew.cmu.edu> wrote:
>>>>>
>>>>>> Hello Predrag,
>>>>>>
>>>>>> could you also please provide the cuDNN version? I couldn't find
>>>>>> cudnn.h in /usr/include, /usr/local/cuda-11/include,
>>>>>> /usr/local/cuda/include, /usr/local/cuda-11/include,
>>>>>> /usr/local/cuda-11.5/include
>>>>>>
>>>>>> thanks!
>>>>>>
>>>>>>
>>>>>> On Thu, Dec 16, 2021 at 1:27 PM Predrag Punosevac <
>>>>>> predragp at andrew.cmu.edu> wrote:
>>>>>>
>>>>>>> Just to add to this info. The installed version of CUDA is
>>>>>>>
>>>>>>> cuda-11.5.1-1.x86_64
>>>>>>>
>>>>>>> We already have a bunch of servers using cuda 11.1 but perhaps
>>>>>>> nothing newer than 11.3. Rolling back to EOL version CUDA 10 is the option
>>>>>>> of the last resort.
>>>>>>>
>>>>>>> I installed /opt/miniconda-py39
>>>>>>>
>>>>>>> which is Python 3.9.5. Most older servers run Python 3.8 branch or
>>>>>>> even 3.7 branch.
>>>>>>>
>>>>>>> I would like everyone to keep in mind that the OS packaging problem
>>>>>>> is NP hard so rolling things back to some "sweet spot" might be a
>>>>>>> prohibitively expensive approach.
>>>>>>>
>>>>>>> Predrag
>>>>>>>
>>>>>>> On Thu, Dec 16, 2021 at 12:40 PM Ifigeneia Apostolopoulou <
>>>>>>> iapostol at andrew.cmu.edu> wrote:
>>>>>>>
>>>>>>>> Hi all,
>>>>>>>>
>>>>>>>> Has anyone tried to test the new servers?
>>>>>>>>
>>>>>>>> I have not managed to run neither pytorch nor tensorflow processes.
>>>>>>>> I am getting the following errors:
>>>>>>>>
>>>>>>>> tensorflow: CUDA runtime implicit initialization on GPU:0 failed.
>>>>>>>> Status: device kernel image is invalid
>>>>>>>>
>>>>>>>> pytorch: RuntimeError: CUDA error: no kernel image is available for
>>>>>>>> execution on the device
>>>>>>>>
>>>>>>>> I am not sure whether this is a CUDA installation issue /
>>>>>>>> incompatibility (however, I am facing a problem with both pytorch and
>>>>>>>> tensorflow processes that can run on the rest of the servers).
>>>>>>>>
>>>>>>>> thanks!
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Wed, Dec 15, 2021 at 10:26 PM Predrag Punosevac <
>>>>>>>> predragp at andrew.cmu.edu> wrote:
>>>>>>>>
>>>>>>>>> Dear Autonians,
>>>>>>>>>
>>>>>>>>> I just finished provisioning two new GPU nodes. The purchase was
>>>>>>>>> approved by Dr. Schneider in July but the order was not placed until late
>>>>>>>>> August due to CMU internal issues just in time to be affected by supply
>>>>>>>>> chain disruption. The servers were finally shipped on 11/24/2021
>>>>>>>>> and received last Wednesday 12/8/2021. To add the final insult to
>>>>>>>>> the injury the nodes were not tagged until Monday afternoon. I had
>>>>>>>>> literally to hunt down people to do the work.
>>>>>>>>> I spent half a day yesterday getting power cables and other misc
>>>>>>>>> supplies. Thus they are only done today. However, I think they are
>>>>>>>>> definitely worth the trouble.
>>>>>>>>>
>>>>>>>>> Each server comes with 8 NVIDIA RTX A6000 connected by high-speed
>>>>>>>>> GPU interconnect NVIDIA links beside PCIe. Each server has 2 AMD EPYC 7502
>>>>>>>>> 32-Core Processors for a total of 128 threads per server. These CPUs are
>>>>>>>>> almost as fast as your desktop processors 3.5 GHz.
>>>>>>>>> Each server has 512GB of RAM and 2TB of scratch. These servers
>>>>>>>>> have 24 2'5" HDD bays so they could potentially be used as a storage space.
>>>>>>>>> I don't have 2'5" HDDs in the lab right now to populate the bays.
>>>>>>>>>
>>>>>>>>> There is one thing which is for now done suboptimally. Namely the
>>>>>>>>> servers were shipped with 1Gbs copper NIC and 10Gbs fiber optical NIC. I
>>>>>>>>> could not locate long enough optical cables in our lab yesterday but I will
>>>>>>>>> try to address this issue soon. I have exactly 2 optical connectors on the
>>>>>>>>> switch so it is down to cabling.
>>>>>>>>>
>>>>>>>>> Have fun and sorry for a long delay.
>>>>>>>>>
>>>>>>>>> Predrag
>>>>>>>>>
>>>>>>>>
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