Cannot run CUDA code that queries NVML - error regarding libnvidia-ml.so - cuda

Recently a colleague needed to use NVML to query device information, so I downloaded the Tesla development kit 3.304.5 and copied the file nvml.h to /usr/include. To test, I compiled the example code in tdk_3.304.5/nvml/example and it worked fine.
Over a weekend, something changed in the system (I cannot determine what was changed and I am not the only one with access to the machine) and now any code that uses nvml.h, such as the example code, fails with the following error:
Failed to initialize NVML:
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
WARNING:
You should always run with libnvidia-ml.so that is installed with your NVIDIA Display Driver. By default it's installed in /usr/lib and /usr/lib64. libnvidia-ml.so in TDK package is a stub library that is attached only for build purposes (e.g. machine that you build your application doesn't have to have Display Driver installed).
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
However, I can still run nvidia-smi and read information about my K20m's state, and as far as I am aware nvidia-smi is just a set of calls to nvml.h. The error message I receive is somewhat cryptic, but I believe it is telling me that the nvidia-ml.so file needs to match the Tesla driver that I have installed on my system. Just to ensure everything is correct, I re-downloaded CUDA 5.0 and installed the driver, CUDA runtime, and the test files. I am certain that the nvidia-ml.so file matches the driver (both are 304.54) so I am quite confused as to what could be going wrong. I can compile and run the test code with nvcc as well as run my own CUDA code, as long as it doesn't include nvml.h.
Has anyone encountered this error or have any thoughts on rectifying the issue?
$ ls -la /usr/lib/libnvidia-ml*
lrwxrwxrwx. 1 root root 17 Jul 19 10:08 /usr/lib/libnvidia-ml.so -> libnvidia-ml.so.1
lrwxrwxrwx. 1 root root 22 Jul 19 10:08 /usr/lib/libnvidia-ml.so.1 -> libnvidia-ml.so.304.54
-rwxr-xr-x. 1 root root 391872 Jul 19 10:08 /usr/lib/libnvidia-ml.so.304.54
$ ls -la /usr/lib64/libnvidia-ml*
lrwxrwxrwx. 1 root root 17 Jul 19 10:08 /usr/lib64/libnvidia-ml.so -> libnvidia-ml.so.1
lrwxrwxrwx. 1 root root 22 Jul 19 10:08 /usr/lib64/libnvidia-ml.so.1 -> libnvidia-ml.so.304.54
-rwxr-xr-x. 1 root root 394792 Jul 19 10:08 /usr/lib64/libnvidia-ml.so.304.54
$ cat /proc/driver/nvidia/version
NVRM version: NVIDIA UNIX x86_64 Kernel Module 304.54 Sat Sep 29 00:05:49 PDT 2012
GCC version: gcc version 4.4.7 20120313 (Red Hat 4.4.7-3) (GCC)
$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2012 NVIDIA Corporation
Built on Fri_Sep_21_17:28:58_PDT_2012
Cuda compilation tools, release 5.0, V0.2.1221
$ whereis nvml.h
nvml: /usr/include/nvml.h
$ ldd example
linux-vdso.so.1 => (0x00007fff2da66000)
libnvidia-ml.so.1 => /usr/lib64/libnvidia-ml.so.1 (0x00007f33ff6db000)
libc.so.6 => /lib64/libc.so.6 (0x000000300e400000)
libpthread.so.0 => /lib64/libpthread.so.0 (0x000000300ec00000)
libdl.so.2 => /lib64/libdl.so.2 (0x000000300e800000)
/lib64/ld-linux-x86-64.so.2 (0x000000300e000000)
EDIT: The solution was to remove all extra instances of libnvidia-ml.so. For some reason there were a LOT of them.
$ sudo find / -name 'libnvidia-ml*'
/usr/lib/libnvidia-ml.so.304.54
/usr/lib/libnvidia-ml.so
/usr/lib/libnvidia-ml.so.1
/usr/opt/lib/libnvidia-ml.so
/usr/opt/lib/libnvidia-ml.so.1
/usr/opt/lib64/libnvidia-ml.so
/usr/opt/lib64/libnvidia-ml.so.1
/usr/opt/nvml/lib/libnvidia-ml.so
/usr/opt/nvml/lib/libnvidia-ml.so.1
/usr/opt/nvml/lib64/libnvidia-ml.so
/usr/opt/nvml/lib64/libnvidia-ml.so.1
/usr/lib64/libnvidia-ml.so.304.54
/usr/lib64/libnvidia-ml.so
/usr/lib64/libnvidia-ml.so.1
/lib/libnvidia-ml.so.old
/lib/libnvidia-ml.so.1

You are getting this error because the application that is trying to use nvml is loading the stub library that is located in:
...tdk_install_path/lib64/libnvidia-ml.so
instead of the one in:
/usr/lib64/libnvidia-ml.so
I was able to reproduce your error when I added the stub library path to my LD_LIBRARY_PATH environment variable. So that is one possible source of error, if someone added the path of the stub library that comes with the tdk distribution to your LD_LIBRARY_PATH environment variable, but probably not the only way this could happen. If someone in an unusual fashion copied the stub library to some system path, that might also be an issue.
You'll need to try and figure out why your system is loading that stub library in place of the correct one in /usr/lib64. Alternatively, for discovery purposes, you could try deleting all instances of the stub library anywhere on your system (leave the correct libraries in /usr/lib and /usr/lib64 alone), and you should be able to observe correct behavior.

I solved the problem this way on a GTX 1070 using windows 10 : go to device manager, select the GPU that is having a problem, disable the GPU and enable back.

I was having this same or similar issue with EWBF Cuda Miner for zCash.
Here is a way to automatically implement Pro7ech's answer (which worked for me) for WIN10:
Install WDK for Windows 10 if you don't already have it: This will give you the ability to use devcon.exe which allows manipulation of devices via batch scripts:
https://learn.microsoft.com/en-us/windows-hardware/drivers/download-the-wdk
You might also need the Windows SDK if you don't have visual studio with Desktop development with C++ workload:
https://developer.microsoft.com/en-us/windows/downloads/windows-10-sdk
To make things easier, you might want to add the installation path to your PATH environment variable:
https://www.howtogeek.com/118594/how-to-edit-your-system-path-for-easy-command-line-access/
Devcon.exe was installed here for me:
C:\Program Files (x86)\Windows Kits\10\Tools\x64
So now run this or similar in a cmd.exe prompt to get the device id:
devcon findall * | find /i "nvidia"
Here is what mine looks like:
C:\Users\Soenhay>devcon findall * | find /i "nvidia"
HDAUDIO\FUNC_01&VEN_10DE&DEV_0083&SUBSYS_38426674&REV_1001\5&1C277AD4&0&0001: NVIDIA High Definition Audio
SWD\MMDEVAPI\{0.0.0.00000000}.{574980C3-9747-42EF-A78C-4C304E070B81}: SAMSUNG (NVIDIA High Definition Audio)
ROOT\UNNAMED_DEVICE\0000 : NVIDIA Virtual Audio Device (Wave Extensible) (WDM)
PCI\VEN_10DE&DEV_1B81&SUBSYS_66743842&REV_A1\4&1F1337ch33s3&0&0000: NVIDIA GeForce GTX 1070
From that I see that my graphics device id is:
PCI\VEN_10DE&DEV_1B81&SUBSYS_66743842&REV_A1\4&1F1337ch33s3&0&0000
So I create a batch file with the following to disable and re-enable the driver:
devcon disable "#PCI\VEN_10DE&DEV_1B81&SUBSYS_66743842&REV_A1\4&1F1337ch33s3&0&0000"
devcon enable "#PCI\VEN_10DE&DEV_1B81&SUBSYS_66743842&REV_A1\4&1F1337ch33s3&0&0000"
Now, when I get the NVML error when starting the miner I just run this batch file and it fixes it. You could also just add those 2 lines to the beginning of your start.bat file to do this every time but I found that the error does not always happen every time I restart the miner time now.
References:
superuser post
devcon commands
devcon examples
No matching devices found.
NOTE:
The command should have the # symbol at the beginning of the device id.
The batch script should be run as administrator.

I have faced the same error.
Found a solutions is to run command:
nvidia-uninstall

Related

Why won't DraftSight run on Fedora 26 with Intel graphics?

DraftSight 2017SP1 Linux (beta) worked on Fedora 24. It fails after upgrading to Fedora 26. Running it from the command line so you can see the low-level errors,
/opt/dassault-systemes/DraftSight/Linux/DraftSight
Qt: Session management error: None of the authentication protocols specified are supported
Could not parse stylesheet of object 0x238a050
Could not parse stylesheet of object 0x238a050
In the graphics environment you see the usual start screens, then error pop-ups which offer to report the error and then close the application when clicked. One says that error-reporting is not available.
Similarly with 2017SP3 and 2018SP0. Fedora updates are current as of today.
This system is an Intel core i3. lspci reports "Intel Corp Xeon E3-1200 v3/4th Gen core processor Integrated Graphics Controller (rev 06)"
2018SP0 does work once an Nvidia GT710 card and the nvidia driver module are installed. It does not work with the nouveau driver module and the same card.
Does anybody have any insight as to the cause? A regression in Fedora, or a latent bug in DraftSight, or anything else?
Knowing whether it works with Fedora 26 and AMD graphics might be very helpful.
Edit March 2018
Doesn't work but differently on a system with AMD R5 230. No "Could not parse" errors, not anything else on the terminal window, but Draftsight starts up with the display all wrong and then locks up. Clicking the "X" gets to "the program is not responding".
Also worth noting that this isn't a Wayland issue. Systems are running Cinnamon and lightdm, so it's good old X.
Also a work-around, if performance is unimportant. (And it probably isn't, with Gen 4 Intel Graphics). Run it as a "remote" application on localhost, on a system with Intel graphics.
$ ssh -X 127.0.0.1
password:
Last login: Wed Mar ...
-bash-4.4$ /opt/dassault-systemes/DraftSight/Linux/DraftSight
(success)
Further update Fedora 29, DraftSight 2018SP3
New wrinkles for Nvidia, Cinnamon as above
Needs invocation
LD_PRELOAD=/usr/lib64/libfreetype.so.6 /opt/dassault-systemes/DraftSight/Linux/DraftSight
otherwise fails with /lib64/libfontconfig.so.1 lookup error FT_DOne_MM_Var
Also kernel 4.20 plus NVidia 390.87 fails to build. There's a patched NVidia installer that does work at if_not_false_then_true site.
Also does not install a .desktop file into /usr/share/applications
I had similar problems when I updated Fedora 24 to 25. The parse stylesheet messages still show up but I can run draftsight from an Xorg session, (not Wayland), using the nouveau drivers but only under root privileges using sudo .
You might try the following script:
sudo DISPLAY=$DISPLAY vblank_mode=1 /opt/dassault-systemes/DraftSight/Linux/DraftSight
I can only get DraftSight to run as root under Fedora 27, 4.18.16-100.fc27.x86_64. I have installed a VM with Ubuntu, and it runs fine, without elevated privileges.

How to Install the CUDA Driver for TensorFlow (installing from source)

I'm trying to build TensorFlow from source and run it with GPU support. To install the toolkit I use the runfile, to install the driver I used the Additional Drivers Tool, since I did not get Ubuntu to boot into Text mode as specified in the CUDA documentation and stop lightdm and start lightdm does not work either, it gives me (also with sudo):
Name com.ubuntu.Upstart does not exist
So far I could build a release from the TensorFlow repository. However, when I'm trying to run the example as specified in the how-to
bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu
the GPU apparently cannot be found:
jonas#jonas-Aspire-V5-591G:~/Documents/repos/tensoflow_fork$ bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally
E tensorflow/stream_executor/cuda/cuda_driver.cc:491] failed call to cuInit: CUDA_ERROR_UNKNOWN
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:153] retrieving CUDA diagnostic information for host: jonas-Aspire-V5-591G
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:160] hostname: jonas-Aspire-V5-591G
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:185] libcuda reported version is: 352.63.0
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:356] driver version file contents: """NVRM version: NVIDIA UNIX x86_64 Kernel Module 352.63 Sat Nov 7 21:25:42 PST 2015 GCC version: gcc version
4.9.2 (Ubuntu 4.9.2-10ubuntu13) """
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] kernel reported version is: 352.63.0
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:293] kernel version seems to match DSO: 352.63.0
I tensorflow/core/common_runtime/gpu/gpu_init.cc:81] No GPU devices available on machine.
F tensorflow/cc/tutorials/example_trainer.cc:125] Check failed: ::tensorflow::Status::OK() == (session->Run({{"x", x}}, {"y:0", "y_normalized:0"}, {}, &outputs)) (OK vs. Invalid argument: Cannot assign a device to node 'y': Could not satisfy explicit device specification '/gpu:0' because no devices matching that specification are registered in this process; available devices: /job:localhost/replica:0/task:0/cpu:0
[[Node: y = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/gpu:0"](Const, x)]])
Aborted
I'm using a clean Ubuntu 15.04 installation on an Acer Notebook with the GTX950M.
Can anybody tell me how to properly install the driver?
Can you run deviceQuery (comes with cuda installation)? Can you see nvidia present in lspci/lsmod/nvidia-smi?
lsmod |grep nvidia
dmesg | grep -i nvidia
lspci | grep -i nvidia
nvidia-smi
You can reload nvidia module and look for error messages
modprobe -r nvidia
dmesg | tail
sudo dmesg | grep NVRM
Related issue https://github.com/tensorflow/tensorflow/issues/601

lwjgl + slick2d + jinput error on 64-bit linux

I am using Linux (Ubuntu 12.04) with 64-bit java 7 and Eclipse (Indigo).
On the game project we are using slick2d and along with it lwjgl. I was halted by the following errors.
(fixes explained in the answer)
java.lang.UnsatisfiedLinkError: no lwjgl in java.library.path
java.lang.UnsatisfiedLinkError: no jinput-linux64 in java.library.path
Failed to open device (/dev/input/event8): Failed to open device /dev/input/event8
Versions:
Slick2D
Mon, 01 Oct 2012 09:54:11 +0100
Sun May 11 20:17:03 BST 2008
build=264
LWJGL (could be 2.8.5 already, but now this):
2.8.4
To fix this, follow the instructions provided in the 'slick2d' documentation
http://www.slick2d.org/wiki/index.php/Main_Page
This seems to be a real bug with slick2D/lwjgl on the versions that we are currently using. To fix this you can't use 64-bit java (with linux at least). Download the 32-bit java from Oracle web site and configure this to be your IDEs runtime environment (you may need to search for more help how to do this in your particular IDE)
This is purely related to permissions on linux. Go to '/dev/input' and change the folder permission 'sudo chmod 644 *' so that the process can simply read what's in there.
There didn't seem to be info on how to fix this problem whole together. Hope this helps some one else.
Download slick and copy needed libs (jinput-linux64, lwjgl, .dll & .so files) to your java.library.path
to get the java.library.path you can do so: System.out.println(System.getProperty("java.library.path"));

CUDA Runtime API error 38: no CUDA-capable device is detected

The Situation
I have a 2 gpu server (Ubuntu 12.04) where I switched a Tesla C1060 with a GTX 670. Than I installed CUDA 5.0 over the 4.2. Afterwards I compiled all examples execpt for simpleMPI without error. But when I run ./devicequery I get following error message:
foo#bar-serv2:~/NVIDIA_CUDA-5.0_Samples/bin/linux/release$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
cudaGetDeviceCount returned 38
-> no CUDA-capable device is detected
What I have tried
To solve this I tried all of the thinks recommended by CUDA-capable device, but to no avail:
/dev/nvidia* is there and the permissions are 666 (crw-rw-rw-) and owner root:root
foo#bar-serv2:/dev$ ls -l nvidia*
crw-rw-rw- 1 root root 195, 0 Oct 24 18:51 nvidia0
crw-rw-rw- 1 root root 195, 1 Oct 24 18:51 nvidia1
crw-rw-rw- 1 root root 195, 255 Oct 24 18:50 nvidiactl
I tried executing the code with sudo
CUDA 5.0 installs driver and libraries at the same time
PS here is lspci | grep -i nvidia:
foo#bar-serv2:/dev$ lspci | grep -i nvidia
03:00.0 VGA compatible controller: NVIDIA Corporation GK104 [GeForce GTX 670] (rev a1)
03:00.1 Audio device: NVIDIA Corporation GK104 HDMI Audio Controller (rev a1)
04:00.0 VGA compatible controller: NVIDIA Corporation G94 [Quadro FX 1800] (rev a1)
[update]
foo#bar-serv2:~/NVIDIA_CUDA-5.0_Samples/bin/linux/release$ nvidia-smi -a
NVIDIA: API mismatch: the NVIDIA kernel module has version 295.59,
but this NVIDIA driver component has version 304.54. Please make
sure that the kernel module and all NVIDIA driver components
have the same version.
Failed to initialize NVML: Unknown Error
How could that be, if I use the CUDA 5.0 installer to install driver and libs at the same time. Could the old 4.2 version, that is still lying around mess things up?
I came across this issue, and running
nvidia-smi
informed me of an API mismatch. The problem was that my Linux distro had installed updates that required a system restart, so restarting resolved the issue.
See this stack overflow question Installing cuda 5 samples in Ubuntu 12.10.
Ubuntu 12 is not a supported Linux distro (yet). For reference see CUDA 5.0 Toolkit Release Notes And Errata
** Distributions Currently Supported
Distribution 32 64 Kernel GCC GLIBC
----------------- -- -- --------------------- ---------- -------------
Fedora 16 X X 3.1.0-7.fc16 4.6.2 2.14.90
ICC Compiler 12.1 X
OpenSUSE 12.1 X 3.1.0-1.2-desktop 4.6.2 2.14.1
Red Hat RHEL 6.x X 2.6.32-131.0.15.el6 4.4.5 2.12
Red Hat RHEL 5.5+ X 2.6.18-238.el5 4.1.2 2.5
SUSE SLES 11 SP2 X 3.0.13-0.27-pae 4.3.4 2.11.3
SUSE SLES 11.1 X X 2.6.32.12-0.7-pae 4.3.4 2.11.1
Ubuntu 11.10 X X 3.0.0-19-generic-pae 4.6.1 2.13
Ubuntu 10.04 X X 2.6.35-23-generic 4.4.5 2.12.1
If you want to do it run on Ubuntu 12 anyway then see answer of rpardo. It looks like this distro instead of installing 64 bit libraries to /usr/lib64 installs them to /usr/lib/x86_64-linux-gnu/
I'd suggest searching for all instances of libcuda.so and libnvidia-ml.so on the system. Since the driver doesn't support this distro it might have installed libraries to a path that is not pointed by LD_LIBRARY_PATH. Then move the libraries around and/or change the LD_LIBRARY_PATH to point to this location (it should be the first path on the left). Then retry nvidia-smi or deviceQuery
Good luck
I got error 38 for cudaGetDeviceCount on a windows machine with GTX980 GPU.
After I downloaded the latest driver for GTX 980 fro the NVIDIA site, installed it and restarted, everything is fine. Looks like the CUDA installer is not installing the latest driver.
Try running the sample using sudo (or, you might do a 'sudo su', set LD_LIBRARY_PATH to the path of cuda libraries and run the sample while being root). Apparently, since you've probably installed CUDA 5.0 using sudo, the samples doesn't run with normal user. However, if you run a sample with root, then you'll be able to run samples with the regular user too! I've not yet restarted the system to see if samples work with normal user even after reboot, or each time you should run at least one CUDA application with root.
The problem might completely disappear if you install CUDA TookKit without using sudo.
I had very similar problem on Debian and it turns out that loaded nvidia module had different version than libcuda1.
To check for installed nvidia module you should do:
$ sudo modinfo nvidia-current | grep version
version: 319.82
If it doesn't match version of libcuda1 this the root of your problems.

MXMLC Incremental compilation not working

Google shows a couple of hits for this issue, but never a solution that I can find. It's always just a few other people saying "it works for me", and the issue dries up. I've tested both with the "-incremental=true" flag to mxmlc and with the <incremental>true</incremental> tag in my flex config.xml with the same result:
Failed to match the compile target with /export/vampire/build/Editor.swf.cache. The cache file will not be reused.
I get this on each compile after the first that creates the cache, whether the source files were modified or not.
I've checked file permissions (not expecting anything - the cache file and the swf it's checking against were both created by MXMLC to begin with):
-rw-rw-r-- 1 nathan nathan 3181508 2009-07-15 17:50 Editor.swf
-rw-rw-r-- 1 nathan nathan 5756512 2009-07-15 17:50 Editor.swf.cache
$ flex_sdk/bin/mxmlc -version
Version 3.3.0 build 4852
$ uname -a
Linux sargasso 2.6.24-19-generic #1 SMP Fri Jul 11 23:41:49 UTC 2008 i686 GNU/Linux
Ubuntu 8.04
It looks like the "Failed to match compile target" error is being caused by an updated timestamp on the flex config file. Even if the config file is unmodified, mxmlc will throw out the old compile cache and recompile everything as long as the timestamp is newer than that on the cache file. This misleading error message is all the info you get.