CUDA toolkit now provided via anaconda?

[jchodera]

I just noticed that anaconda now appears to provide packages for different CUDA toolkit versions.

[jchodera]

The numba version of cudatoolkit appears to be more up-to-date.

[peastman]

Keep in mind that the toolkit isn't much use without the driver. You can't even compile, since libcuda.so comes with the driver, not the toolkit.

[jchodera]

I was under the impression we could use multiple toolkit versions if a recent driver (capable of supporting the most recent toolkit version) was installed. The big complaint we've had from users is that we might have compiled/released OpenMM conda packages against a CUDA version that is not available on their systems.

Presuming we used a docker build environment with a recent CUDA driver, would it be possible to build several versions of the OpenMM conda package using these toolkit versions (7.5, 8.0, 9.0) and make packages for all three (with appropriate toolkit package dependencies) available that would run on a range of drivers? Presumably, only kernels that support the CUDA toolkit we used to compile would work, but I'm not sure if there is more precise matching of CUDA toolkit x driver x compiled code that needs to happen for this to work.

[peastman]

I believe the requirement is that driver version >= toolkit version. So if someone had CUDA 9.0 (both driver and toolkit) installed, but we had compiled against CUDA 8.0, this would let it automatically install the older toolkit. But it wouldn't help the more common situation where they have an older CUDA version installed. For example, if they're running on a cluster that has CUDA 7.5, that wouldn't work because the 8.0 toolkit isn't compatible with the 7.5 driver.

That's separate from the question of providing several different OpenMM packages compiled against different CUDA versions. We could do that either way. But as far as I know, conda can't detect what driver they have installed, so the user would have to manually specify which version they wanted.

[emigmo]

how to install cuda toolkit in anaconda

[jchodera]

@emigmo : According to this page, you could install the CUDA 8.0 toolkit with

conda install -c anaconda cudatoolkit==8.0

[Sharuk06]

try this it will detect your pc specs and install the required toolkits i guess!

conda install -c anaconda cudatoolkit

https://anaconda.org/anaconda/cudatoolkit

[fastlater]

@Sharuk06 @jchodera I installed the cuda and cudnn packages in my environment I get ImportError: Could not find 'cudart64.80.dll' . If I used conda and not the nvidia website, how do I set the required paths or where to find this dll missing file.

[jchodera]

We don't officially support installing CUDA via conda, so this should be considered experimental. But I'd love to see if we could get this to work.

Can you do a "conda list" and paste all the packages you have installed here? And which platform are you on? Sounds like win?

[fastlater]

I am using win 7. I created this environment to run a tf code. I installed tf 1.4, cuda 8.0 and cudnn 6.0 using anaconda.
This list of installed packages is as below:

packages in environment at C:\ProgramData\Anaconda3\envs\tfenv:

Name Version Build Channel
bleach 1.5.0
bokeh 0.12.14 py35_0
ca-certificates 2017.08.26 h94faf87_0 anaconda
certifi 2018.1.18 py35_0 anaconda
click 6.7 py35h10df73f_0
cloudpickle 0.5.2 py35_1
cudatoolkit 8.0 3 anaconda
cudnn 6.0 0 anaconda
cycler 0.10.0 py35hcc71164_0
cython 0.27.3 py35h82876f0_0
dask 0.17.1 py35_0
dask-core 0.17.1 py35_0
decorator 4.2.1 py35_0
distributed 1.21.1 py35_0
enum34 1.1.6
freetype 2.8 vc14h17c9bdf_0 [vc14] anaconda
h5py 2.7.1 py35hb2c3add_0
hdf5 1.10.1 vc14hb361328_0 [vc14] anaconda
heapdict 1.0.0 py35_2
html5lib 0.9999999
icc_rt 2017.0.4 h97af966_0
icu 58.2 vc14hc45fdbb_0 [vc14] anaconda
imageio 2.2.0 py35hcd4b9a4_0
intel-openmp 2018.0.0 hd92c6cd_8
jinja2 2.10 py35hdf652bb_0
jpeg 9b vc14h4d7706e_1 [vc14] anaconda
libpng 1.6.32 vc14h5163883_3 [vc14] anaconda
libtiff 4.0.8 vc14h04e2a1e_10 [vc14] anaconda
locket 0.2.0 py35h0dfcdd0_1
Markdown 2.6.11
markupsafe 1.0 py35hc253e08_1
matplotlib 2.1.2 py35h016c42a_0
mkl 2018.0.1 h2108138_4
msgpack-python 0.5.5 py35he980bc4_0
networkx 2.1 py35_0
numpy 1.14.1
numpy 1.14.1 py35h4a99626_1
olefile 0.45.1 py35_0
openssl 1.0.2n h74b6da3_0 anaconda
packaging 16.8 py35h5fb721f_1
pandas 0.22.0 py35h6538335_0
partd 0.3.8 py35h894d1e4_0
pillow 4.2.1 py35hd7da350_0 anaconda
pip 9.0.1 py35h691316f_4
protobuf 3.5.1
psutil 5.4.3 py35hfa6e2cd_0
pycocotools 2.0
pyparsing 2.2.0 py35hcabcaab_1
pyqt 5.6.0 py35hd46907b_5
python 3.5.4 h1357f44_23
python-dateutil 2.6.1 py35h6b299a3_1
pytz 2018.3 py35_0
pywavelets 0.5.2 py35h7c47ace_0
pyyaml 3.12 py35h4bf9689_1
qt 5.6.2 vc14h6f8c307_12 [vc14] anaconda
scikit-image 0.13.1 py35hfa6e2cd_1
scipy 1.0.0 py35h75710e8_0
setuptools 38.5.1
setuptools 38.5.1 py35_0
sip 4.18.1 py35h01cbaa7_2
six 1.11.0 py35hc1da2df_1
six 1.11.0
sortedcontainers 1.5.9 py35_0
sqlite 3.20.1 vc14h7ce8c62_1 [vc14] anaconda
tblib 1.3.2 py35hd2cf7e1_0
tensorflow-gpu 1.4.0
tensorflow-tensorboard 0.4.0
tk 8.6.7 vc14hb68737d_1 [vc14] anaconda
toolz 0.9.0 py35_0
tornado 4.5.3 py35_0
vc 14 h0510ff6_3
vs2015_runtime 14.0.25123 3
Werkzeug 0.14.1
wheel 0.30.0 py35h38a90bc_1
wheel 0.30.0
wincertstore 0.2 py35hfebbdb8_0
yaml 0.1.7 vc14hb31d195_1 [vc14] anaconda
zict 0.1.3 py35hf5542e0_0
zlib 1.2.11 vc14h1cdd9ab_1 [vc14] anaconda

[fastlater]

The error is as shown below. I know that I need to set the paths but one of the reasons why I was trying to install cuda using anaconda was because in some way, I was getting error when I tried to install cuda 8.0 from the exe file downloaded from nvidia. Since cudnn64_6.dll is included with 'cudnn-8.0-windows7-x64-v6.0' , I guess this dll should be somewhere inside anaconda folder after I installed the package, right?

In case I keep the cuda and cudnn packages installed and install the cuda and cudnn using nvidia files in my computer, which one will be used for the environment when running the script?

(tfenv) C:\Program Files (x86)\Python 3.5.2\tensorflow\Master - Mask_RCNN>python
run.py
Traceback (most recent call last):
File "C:\ProgramData\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python
platform\self_check.py", line 75, in preload_check
ctypes.WinDLL(build_info.cudart_dll_name)
File "C:\ProgramData\Anaconda3\envs\tfenv\lib\ctypes_init_.py", line 351, i
n init
self._handle = _dlopen(self._name, mode)
OSError: [WinError 126] 找不到指定的模組。

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "run.py", line 10, in
import coco
File "C:\Program Files (x86)\Python 3.5.2\tensorflow\Master - Mask_RCNN\coco.p
y", line 49, in
import utils
File "C:\Program Files (x86)\Python 3.5.2\tensorflow\Master - Mask_RCNN\utils.
py", line 15, in
import tensorflow as tf
File "C:\ProgramData\Anaconda3\envs\tfenv\lib\site-packages\tensorflow_init
_.py", line 24, in
from tensorflow.python import *
File "C:\ProgramData\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python
init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\ProgramData\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python
pywrap_tensorflow.py", line 30, in
self_check.preload_check()
File "C:\ProgramData\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python
platform\self_check.py", line 82, in preload_check
% (build_info.cudart_dll_name, build_info.cuda_version_number))
ImportError: Could not find 'cudart64_80.dll'. TensorFlow requires that this DLL
be installed in a directory that is named in your %PATH% environment variable.
Download and install CUDA 8.0 from this URL: https://developer.nvidia.com/cuda-t
oolkit

[jchodera]

OK, a few things here:

• This is the issue tracker for the omnia channel which does not support either the cudatoolkit package (on the anaconda channel) or tensorflow. Are you asking for help about using OpenMM or some other package from omnia, or just tensorflow?
• The error message you are receiving from tensorflow suggests that the directory containing cudart64_80.dll has to be in your %PATH%:

ImportError: Could not find 'cudart64_80.dll'. TensorFlow requires that this DLL
be installed in a directory that is named in your %PATH% environment variable.

I think the anaconda channel cudatoolkit installs that DLL, but it may not be ending up added to your %PATH%, which tensorflow seems to require it. Maybe you can search for where conda installed it and try adding it to your path?

• This tensorflow issue may have some useful information for you: Tensorflow-GPU installation Error  tensorflow/tensorflow#13442
• I'd seek further support in the tensorflow issue tracker: https://github.com/tensorflow/tensorflow/issue

Good luck!

[aisri]

Extending the issues with conda installation of cudatoolkit. I dont really see the nvcc binary (or cuda-gdb, nvvp, etc) tools installed when using conda.
Hope they fix this.

[jchodera]

I don't think there's a supported mechanism for installing the CUDA toolkit via conda at this time. The best approach I've seen seems to be pytorch, which uses dummy packages to indicate which version of CUDA you've installed: https://anaconda.org/pytorch/repo

[nospotfer]

Summary of steps I've done to install tensorflow-gpu in Ubuntu 18.04 (should work in any Debian-based distro).

1.Install Nvidia driver on a machine with supported Nvidia card.
$ sudo apt update
$ sudo ubuntu-drivers autoinstall
$ sudo reboot
2. You might need to switch to Nvidia GPU from Intel GPU by using

$ sudo prime-select nvidia
$ sudo reboot
3. Install Anaconda with python 3.6.

https://repo.anaconda.com/archive/Anaconda3-5.2.0-Linux-x86_64.sh (Don’t use python 3.7.)

4. Install tensorflow-gpu

$ conda install tensorflow-gpu==1.11 cudatoolkit==9.0 cudnn==7.1.2 h5py

5. You’re done.

Source: https://medium.com/datadriveninvestor/install-tensorflow-gpu-to-use-nvidia-gpu-on-ubuntu-18-04-do-ai-71b0ce64ebc5