How do I update Nvidia display driver on ubuntu 18.04, if I already installed cuda toolkit 10.2 and its bundled display driver?

I installed CUDA toolkit 10.2 on ubuntu 18.04 LTS. I previously did not have any nvidia display drivers, so it came bundled with the 418 version display driver. This seemed to work fine.

I noticed on the NVIDIA site that the latest driver was 430. I want to update my display driver from 418 to 430. How can I do this?

[Downloading the driver directly] (https://www.nvidia.com/Download/index.aspx), and then running the installer, doesn’t work; it gives a complaint that Nvidia is already running with Xorg.

CUDA 10.0 breaking Kubuntu 18.04 LTS

Hoping you can help me with something. I really like Kubuntu but when I install CUDA (10.0) and CuDNN (7.6.2), it breaks my installation of Kubuntu. By that, I mean I get a terminal error and then it reboots to a tty1 login screen. I can get to the GUI by running startx but then I can’t use my keyboard or mouse (both wired USB). I reinstalled Kubuntu and tried again but got the same result. For info, I used the Kubuntu GUI to install the nVidia driver (435, iirc). Has anyone else come across this issue and know how to make it work? In the meantime, I’ve resorted to using Ubuntu 18.04 and CUDA works fine on it.

EDIT: I modified the instructions from this tutorial to install CUDA, CuDNN https://www.youtube.com/watch?v=vxjbL5iN1XY

Install Cuda 10.0 on Ubuntu 16.04 (for DGX-1)

I am trying to install CUDA-10.0 on Ubuntu 16.04 running on DGX-1 server. I followed the instructions for “runfile installation” in https://docs.nvidia.com/cuda/archive/10.0/cuda-installation-guide-linux/index.html#runfile.

I selected to install CUDA Drivers, CUDA Toolkit and CUDA Samples.

The previous versions of Nvidia driver and CUDA were removed using (as suggested in How can I install CUDA on Ubuntu 16.04?):

sudo apt-get purge nvidia-cuda* sudo apt-get purge nvidia-* 

After step 4.2.6 (i.e. Reboot the system to reload the graphical interface.), I checked the CUDA version as follows:

nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2018 NVIDIA Corporation Built on Sat_Aug_25_21:08:01_CDT_2018 Cuda compilation tools, release 10.0, V10.0.130 

However, when I run “nvidia-smi”, I get the following error:

nvidia-smi NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running. 

I went to step 4.4 (Device Node Verification.), and found that the device files “/dev/nvidia*” don’t exist. I tried to create them manually, however, running “modprobe” returns error:

sudo /sbin/modprobe nvidia modprobe: ERROR: could not insert 'nvidia': Exec format error 

Please help to solve the problem. Thanks!

========================================================================== Other details.

lspci | grep -i nvidia 06:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 07:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 0a:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 0b:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 85:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 86:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 89:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 8a:00.0 3D controller: NVIDIA Corporation GV100GL [Tesla V100 SXM2 32GB] (rev a1) 

uname -m && cat /etc/*release x86_64 DGX_NAME="DGX Server" DGX_PRETTY_NAME="NVIDIA DGX Server" DGX_SWBUILD_DATE="2018-03-20" DGX_SWBUILD_VERSION="3.1.6" DGX_COMMIT_ID="1b0f58ecbf989820ce745a9e4836e1de5eea6cfd" DGX_SERIAL_NUMBER=QTFCOU8280021 DISTRIB_ID=Ubuntu DISTRIB_RELEASE=16.04 DISTRIB_CODENAME=xenial DISTRIB_DESCRIPTION="Ubuntu 16.04.6 LTS" NAME="Ubuntu" VERSION="16.04.6 LTS (Xenial Xerus)" ID=ubuntu ID_LIKE=debian PRETTY_NAME="Ubuntu 16.04.6 LTS" VERSION_ID="16.04" HOME_URL="http://www.ubuntu.com/" SUPPORT_URL="http://help.ubuntu.com/" BUG_REPORT_URL="http://bugs.launchpad.net/ubuntu/" 

gcc --version gcc (GCC) 5.4.0 Copyright (C) 2015 Free Software Foundation, Inc. This is free software; see the source for copying conditions.  There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. 

uname -r 4.4.0-142-generic 

cat /proc/version Linux version 4.4.0-142-generic (buildd@lgw01-amd64-033) (gcc version 5.4.0 20160609 (Ubuntu 5.4.0-6ubuntu1~16.04.10) ) #168-Ubuntu SMP Wed Jan 16 21:00:45 UTC 2019 

dpkg -l | grep nvidia ii  dgx-peer-mem-loader                             1.1-10                                        amd64        Ensure nvidia is loaded before nv_peer_mem 

Cuda memory issues using large Pytorch model and Tensorflow model together

The Pytorch network is Tencent DSFD:https://github.com/TencentYoutuResearch/FaceDetection-DSFD

and the Tensorflow network is WideResNet: https://github.com/yu4u/age-gender-estimation

I’m using the former for face detection (very robust to all poses) and the latter for gender detection. They both get instantiated in the same driver script. I am on Ubuntu 18.04 with Pytorch GPU and Tensorflow GPU installed as Conda packages in a conda env. I read on a blog by Puget Systems that this is all I need to do with regards to Cuda and Cudnn installation and in fact it does seem that the GPU is used and thus results in Cuda Runtime memory errors.

My proposed solution is to detect faces first, save the bounding boxes and crops of faces as .npz files and then run the gender detection separately.

It was working fine with a much smaller gender detection model (Hassner and Levi’s) but the accuracy was too low.

Would installing Cuda and Cudnn on the Ubuntu 18.04 server itself make a difference? Ie. Do I have a better chance of running this script with both models? The GPU is a GTX 1080 with 8 GB memory.

CUDA 10.1 Update 2 is compatible to gcc 7.3.0, mine is 7.4.0, is this the cause the installation failed?

I downloaded the cuda installer from here.

I ran the installer on Ubuntu 18.04 LTS (Bionic Beaver) with gcc 7.4.0.

and I got this error.

[INFO]: Driver not installed. [INFO]: Checking compiler version... [INFO]: gcc location: /usr/bin/gcc  [INFO]: gcc version: gcc version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1)  [INFO]: Initializing menu [INFO]: Setup complete [INFO]: Components to install: [INFO]: Driver [INFO]: 418.87.00 [INFO]: Executing NVIDIA-Linux-x86_64-418.87.00.run --ui=none --no-questions --accept-license --disable-nouveau --no-cc-ver$   [INFO]: Finished with code: 256 [ERROR]: Install of driver component failed. [ERROR]: Install of 418.87.00 failed, quitting 

This table indicates the compatible gcc is 7.3.0, is this the reason causes installation failed? Do I need to reinstall or downgrade gcc?

Error : ATTENTION! No OpenCL or CUDA installation found in ubunut 16.04

I want to run hashcat on ubunut 16.0. But return with error about OpenCl installation.

ATTENTION! No OpenCL or CUDA installation found. 

The Graphic card used by system is:

lspci | grep VGA 03:00.0 VGA compatible controller: Advanced Micro Devices, Inc. [AMD/ATI] Oland GL [FirePro W2100]  glxinfo | grep Device Device: AMD OLAND (DRM 2.50.0 / 4.15.0-58-generic, LLVM 6.0.0) (0x6608)  CPU: product: Intel(R) Xeon(R) CPU E5-1660 v3 @ 3.00GHz 

I try to install few packages for drivers:

ocl-icd-libopencl1 

but when used, return error:

 DRM_IOCTL_I915_GEM_APERTURE failed: No such file or directory Assuming 131072kB available aperture size. May lead to reduced performance or incorrect rendering. get chip id failed: -1 [22] param: 4, val: 0 DRM_IOCTL_I915_GEM_APERTURE failed: No such file or directory Assuming 131072kB available aperture size. May lead to reduced performance or incorrect rendering. get chip id failed: -1 [22] param: 4, val: 0 beignet-opencl-icd: no supported GPU found, this is probably the wrong opencl-icd package for this hardware (If you have multiple ICDs installed and OpenCL works, you can ignore this message) clGetDeviceIDs(): CL_DEVICE_NOT_FOUND  clGetDeviceIDs(): CL_DEVICE_NOT_FOUND 

When i install RadeonOpenCompute (ROCm),Its not working too. Is there solution?

Can’t install anything but cuda 10.1 with driver version 430

I’ve been trying to roll back to cuda 10.0 with no success. I previously had Cuda 10.1 on my system, which had been installed using a runfile. I uninstalled it using the uninstall script. However, now whenever I try to install a different version of CUDA, I get Failed to initialize NVML: Driver/library version mismatch.

I have tried completely removing all versions of cuda and nvidia drivers using

sudo apt –purge remove nvidia-* sudo apt –purge remove cuda*

Then I reinstalled just the driver to see if I could get nvidia-smi to work. However, if I install 410 or 418, I get the same error message. nvidia-smi only works if I install 430.

All I can think is that there are some files that were put in place by the runfile that never got removed and that’s corrupting my installation. I have been using .deb files to install cuda 10.0 and the ubuntu repository for the drivers.

I’m running ubuntu 18.04 and I have two rtx 2080ti. I have been rebooting after installing drivers, removing drivers, and installing CUDA.

How do I accept the ELUA while installing CUDA with run file?

I have a very simple question: Is there anyone knowing how to accept the ‘END user agreement’ of the CUDA installation with run file? tried different keys, googled but find nothing related…

┌──────────────────────────────────────────────────────────────────────────────┐ │  End User License Agreement                                                  │ │  --------------------------                                                  │ │                                                                              │ │                                                                              │ │  Preface                                                                     │ │  -------                                                                     │ │                                                                              │ │  The Software License Agreement in Chapter 1 and the Supplement              │ │  in Chapter 2 contain license terms and conditions that govern               │ │  the use of NVIDIA software. By accepting this agreement, you                │ │  agree to comply with all the terms and conditions applicable                │ │  to the product(s) included herein.                                          │ │                                                                              │ │                                                                              │ │  NVIDIA Driver                                                               │ │                                                                              │ │                                                                              │ │  Description                                                                 │ │                                                                              │ │  This package contains the operating system driver and                       │ │──────────────────────────────────────────────────────────────────────────────│ │ Do you accept the above EULA? (accept/decline/quit):                         │