GPU3 back in business

Fri Oct 21 15:54:08 EDT 2016

Sounds good. Let us have tensorflow system wide on all GPU nodes. We
can worry about Matlab later.

Best,
B
======================
Barnabas Poczos, PhD
Assistant Professor
Machine Learning Department
Carnegie Mellon University

On Fri, Oct 21, 2016 at 3:50 PM, Predrag Punosevac <predragp at cs.cmu.edu> wrote:
> Barnabas Poczos <bapoczos at cs.cmu.edu> wrote:
>
>> Hi Predrag,
>>
>> If there is no other solution, then I think it is OK not to have
>> Matlab on GPU2 and GPU3.
>> Tensorflow has higher priority on these nodes.
>
> We could possibly have multiple CUDA libraries for different versions
> but that is going to bite us for the rear end quickly. People who want
> to use MATLAB with GPUs will have to live with GPU1 probably until
> Spring release of MATLAB.
>
> Predrag
>
>>
>> Best,
>> Barnabas
>>
>>
>>
>>
>> ======================
>> Barnabas Poczos, PhD
>> Assistant Professor
>> Machine Learning Department
>> Carnegie Mellon University
>>
>>
>> On Fri, Oct 21, 2016 at 3:37 PM, Predrag Punosevac <predragp at cs.cmu.edu> wrote:
>> > Dougal Sutherland <dougal at gmail.com> wrote:
>> >
>> >
>> > Sorry that I am late for the party. This is my interpretation of what we
>> > should do.
>> >
>> > 1. I will go back to CUDA 8.0 which will brake MATLAB. We have to live
>> > with it. Barnabas please OK this. I will work with MathWorks for this to
>> > be fixed for 2017a release.
>> >
>> > 2. Then I could install TensorFlow compiled by Dougal system wide.
>> > Please Dugal after I upgrade back to 8.0 recompile it again using CUDA
>> > 8.0. I could give you the root password so that you can compile and
>> > install directly.
>> >
>> > 3. If everyone is OK with above I will pull the trigger on GPU3 at
>> > 4:30PM and upgrade to 8.0
>> >
>> > 4. MATLAB will be broken on GPU2 as well after I put Titan cards during
>> > the October 25 power outrage.
>> >
>> > Predrag
>> >
>> >
>> >
>> >
>> >
>> >
>> >> Heh. :)
>> >>
>> >> An explanation:
>> >>
>> >>    - Different nvidia gpu architectures are called "compute capabilities".
>> >>    This is a number that describes the behavior of the card: the maximum size
>> >>    of various things, which API functions it supports, etc. There's a
>> >>    reference here
>> >>    <https://en.wikipedia.org/wiki/CUDA#Version_features_and_specifications>,
>> >>    but it shouldn't really matter.
>> >>    - When CUDA compiles code, it targets a certain architecture, since it
>> >>    needs to know what features to use and whatnot. I *think* that if you
>> >>    compile for compute capability x, it will work on a card with compute
>> >>    capability y approximately iff x <= y.
>> >>    - Pascal Titan Xs, like gpu3 has, have compute capability 6.1.
>> >>    - CUDA 7.5 doesn't know about compute capability 6.1, so if you ask to
>> >>    compile for 6.1 it crashes.
>> >>    - Theano by default tries to compile for the capability of the card, but
>> >>    can be configured to compile for a different capability.
>> >>    - Tensorflow asks for a list of capabilities to compile for when you
>> >>    build it in the first place.
>> >>
>> >>
>> >> On Fri, Oct 21, 2016 at 8:17 PM Dougal Sutherland <dougal at gmail.com> wrote:
>> >>
>> >> > They do work with 7.5 if you specify an older compute architecture; it's
>> >> > just that their actual compute capability of 6.1 isn't supported by cuda
>> >> > 7.5. Thank is thrown off by this, for example, but it can be fixed by
>> >> > telling it to pass compute capability 5.2 (for example) to nvcc. I don't
>> >> > think that this was my problem with building tensorflow on 7.5; I'm not
>> >> > sure what that was.
>> >> >
>> >> > On Fri, Oct 21, 2016, 8:11 PM Kirthevasan Kandasamy <kandasamy at cmu.edu>
>> >> > wrote:
>> >> >
>> >> > Thanks Dougal. I'll take a look atthis and get back to you.
>> >> > So are you suggesting that this is an issue with TitanX's not being
>> >> > compatible with 7.5?
>> >> >
>> >> > On Fri, Oct 21, 2016 at 3:08 PM, Dougal Sutherland <dougal at gmail.com>
>> >> > wrote:
>> >> >
>> >> > I installed it in my scratch directory (not sure if there's a global
>> >> > install?). The main thing was to put its cache on scratch; it got really
>> >> > upset when the cache directory was on NFS. (Instructions at the bottom of
>> >> > my previous email.)
>> >> >
>> >> > On Fri, Oct 21, 2016, 8:04 PM Barnabas Poczos <bapoczos at cs.cmu.edu> wrote:
>> >> >
>> >> > That's great! Thanks Dougal.
>> >> >
>> >> > As I remember bazel was not installed correctly previously on GPU3. Do
>> >> > you know what went wrong with it before and why it is good now?
>> >> >
>> >> > Thanks,
>> >> > Barnabas
>> >> > ======================
>> >> > Barnabas Poczos, PhD
>> >> > Assistant Professor
>> >> > Machine Learning Department
>> >> > Carnegie Mellon University
>> >> >
>> >> >
>> >> > On Fri, Oct 21, 2016 at 2:03 PM, Dougal Sutherland <dougal at gmail.com>
>> >> > wrote:
>> >> > > I was just able to build tensorflow 0.11.0rc0 on gpu3! I used the cuda
>> >> > 8.0
>> >> > > install, and it built fine. So additionally installing 7.5 was probably
>> >> > not
>> >> > > necessary; in fact, cuda 7.5 doesn't know about the 6.1 compute
>> >> > architecture
>> >> > > that the Titan Xs use, so Theano at least needs to be manually told to
>> >> > use
>> >> > > an older architecture.
>> >> > >
>> >> > > A pip package is in ~dsutherl/tensorflow-0.11.0rc0-py2-none-any.whl. I
>> >> > think
>> >> > > it should work fine with the cudnn in my scratch directory.
>> >> > >
>> >> > > You should probably install it to scratch, either running this first to
>> >> > put
>> >> > > libraries your scratch directory or using a virtualenv or something:
>> >> > > export PYTHONUSERBASE=/home/scratch/$USER/.local
>> >> > >
>> >> > > You'll need this to use the library and probably to install it:
>> >> > > export
>> >> > >
>> >> > LD_LIBRARY_PATH=/home/scratch/dsutherl/cudnn-8.0-5.1/cuda/lib64:"$LD_LIBRARY_PATH"
>> >> > >
>> >> > > To install:
>> >> > > pip install --user ~dsutherl/tensorflow-0.11.0rc0-py2-none-any.whl
>> >> > > (remove --user if you're using a virtualenv)
>> >> > >
>> >> > > (A request: I'm submitting to ICLR in two weeks, and for some of the
>> >> > models
>> >> > > I'm running gpu3's cards are 4x the speed of gpu1 or 2's. So please don't
>> >> > > run a ton of stuff on gpu3 unless you're working on a deadline too.
>> >> > >
>> >> > >
>> >> > >
>> >> > > Steps to install it, for the future:
>> >> > >
>> >> > > Install bazel in your home directory:
>> >> > >
>> >> > > wget
>> >> > >
>> >> > https://github.com/bazelbuild/bazel/releases/download/0.3.2/bazel-0.3.2-installer-linux-x86_64.sh
>> >> > > bash bazel-0.3.2-installer-linux-x86_64.sh --prefix=/home/scratch/$USER
>> >> > > --base=/home/scratch/$USER/.bazel
>> >> > >
>> >> > > Configure bazel to build in scratch. There's probably a better way to do
>> >> > > this, but this works:
>> >> > >
>> >> > > mkdir /home/scratch/$USER/.cache
>> >> > > ln -s /home/scratch/$USER/.cache/bazel ~/.cache/bazel
>> >> > >
>> >> > > Build tensorflow. Note that builds from git checkouts don't work, because
>> >> > > they assume a newer version of git than is on gpu3:
>> >> > >
>> >> > > cd /home/scratch/$USER
>> >> > > wget
>> >> > > tar xf
>> >> > > cd tensorflow-0.11.0rc0
>> >> > > ./configure
>> >> > >
>> >> > > This is an interactive script that doesn't seem to let you pass
>> >> > arguments or
>> >> > > anything. It's obnoxious.
>> >> > > Use the default python
>> >> > > don't use cloud platform or hadoop file system
>> >> > > use the default site-packages path if it asks
>> >> > > build with GPU support
>> >> > > default gcc
>> >> > > default Cuda SDK version
>> >> > > specify /usr/local/cuda-8.0
>> >> > > default cudnn version
>> >> > > specify $CUDNN_DIR from use-cudnn.sh, e.g.
>> >> > > /home/scratch/dsutherl/cudnn-8.0-5.1/cuda
>> >> > > Pascal Titan Xs have compute capability 6.1
>> >> > >
>> >> > > bazel build -c opt --config=cuda
>> >> > > //tensorflow/tools/pip_package:build_pip_package
>> >> > > bazel-bin/tensorflow/tools/pip_package/build_pip_package ./
>> >> > > A .whl file, e.g. tensorflow-0.11.0rc0-py2-none-any.whl, is put in the
>> >> > > directory you specified above.
>> >> > >
>> >> > >
>> >> > > - Dougal
>> >> > >
>> >> > >
>> >> > > On Fri, Oct 21, 2016 at 6:14 PM Kirthevasan Kandasamy <kandasamy at cmu.edu
>> >> > >
>> >> > > wrote:
>> >> > >>
>> >> > >> Predrag,
>> >> > >>
>> >> > >> Any updates on gpu3?
>> >> > >> I have tried both tensorflow and chainer and in both cases the problem
>> >> > >> seems to be with cuda
>> >> > >>
>> >> > >> On Wed, Oct 19, 2016 at 4:10 PM, Predrag Punosevac <predragp at cs.cmu.edu
>> >> > >
>> >> > >> wrote:
>> >> > >>>
>> >> > >>> Dougal Sutherland <dougal at gmail.com> wrote:
>> >> > >>>
>> >> > >>> > I tried for a while. I failed.
>> >> > >>> >
>> >> > >>>
>> >> > >>> Damn this doesn't look good. I guess back to the drawing board. Thanks
>> >> > >>> for the quick feed back.
>> >> > >>>
>> >> > >>> Predrag
>> >> > >>>
>> >> > >>> > Version 0.10.0 fails immediately on build: "The specified
>> >> > >>> > --crosstool_top
>> >> > >>> > '@local_config_cuda//crosstool:crosstool' is not a valid
>> >> > >>> > cc_toolchain_suite
>> >> > >>> > rule." Apparently this is because 0.10 required an older version of
>> >> > >>> > bazel (
>> >> > >>> > https://github.com/tensorflow/tensorflow/issues/4368), and I don't
>> >> > have
>> >> > >>> > the
>> >> > >>> > energy to install an old version of bazel.
>> >> > >>> >
>> >> > >>> > Version 0.11.0rc0 gets almost done and then complains about no such
>> >> > >>> > file or
>> >> > >>> > directory for libcudart.so.7.5 (which is there, where I told
>> >> > tensorflow
>> >> > >>> > it
>> >> > >>> > was...).
>> >> > >>> >
>> >> > >>> > Non-release versions from git fail immediately because they call git
>> >> > -C
>> >> > >>> > to
>> >> > >>> > get version info, which is only in git 1.9 (we have 1.8).
>> >> > >>> >
>> >> > >>> >
>> >> > >>> > Some other notes:
>> >> > >>> > - I made a symlink from ~/.cache/bazel to
>> >> > >>> > /home/scratch/$USER/.cache/bazel,
>> >> > >>> > because bazel is the worst. (It complains about doing things on NFS,
>> >> > >>> > and
>> >> > >>> > hung for me [clock-related?], and I can't find a global config file
>> >> > or
>> >> > >>> > anything to change that in; it seems like there might be one, but
>> >> > their
>> >> > >>> > documentation is terrible.)
>> >> > >>> >
>> >> > >>> > - I wasn't able to use the actual Titan X compute capability of 6.1,
>> >> > >>> > because that requires cuda 8; I used 5.2 instead. Probably not a huge
>> >> > >>> > deal,
>> >> > >>> > but I don't know.
>> >> > >>> >
>> >> > >>> > - I tried explicitly including /usr/local/cuda/lib64 in
>> >> > LD_LIBRARY_PATH
>> >> > >>> > and
>> >> > >>> > set CUDA_HOME to /usr/local/cuda before building, hoping that would
>> >> > >>> > help
>> >> > >>> > with the 0.11.0rc0 problem, but it didn't.
>> >> > >>
>> >> > >>
>> >> > >
>> >> >
>> >> >
>> >> >