Zerobrane Studio Version: 1.90
OS: Ubuntu 20.04.2 LTS x86_64
CPU: Intel i5-4590 (4) # 3.700GHz
GPU: NVIDIA GeForce GTX 1050 Ti
Memory: 2565MiB / 7852MiB
Video: https://app.box.com/s/dui1kxuat8saodg8hr9ws9qz91ewgop8
As title suggests. I never had this issue while working on windows. Sometimes right-clicking works, albeit very rarely. It seems the project tree is not able to properly capture my cursor.
Yes, it's a known issue that has been fixed in the master branch (see the discussion in ticket #1062), so you may want to use that or apply the fix from the ticket.
Related
I'm using an Asus Chromebook with a CPU(I think).
This is what the Error says:
Warning: Could not find a matching GPU name. Things may not behave as expected.
Detected OpenGL configuration:
Vendor: Red Hat
Renderer: virgl
/run/user/1000/gvfs/ non-existent directory
found bundled python: /home/sekhong5417/blender/2.90/python
This works on my Friend's Chromebook who has a GPU.
Also I am kinda young so I can't replace anything or buy a new device.
There are images at the bottom
If anyone still runs into this issue, there is an incompatibility with Blender and Intel ChromeOS GPU drivers.
See https://developer.blender.org/T77651#1172666 for more details and an updated working build of v2.93.
Hopefully, the fix gets included in the next release.
I use Acer Chromebook spin 13 and I just met the same issue with you. I think it is maybe the Debian within Chromebook don't have the driver that matches the Intel GPU. My Chromebook uses Intel HD graphics 620. I tried many ways to install the driver but they all failed. Linux works easier with Nvidia GPU though. So my idea is you can try to find intel a drive which matches your Graphic card and try again.
I was trying to run tensorflow-gpu on an ASUS laptop with a GTX 870M card on Ubuntu 16.40, but got an error message
018-10-07 16:54:50.537324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1482] Ignoring visible gpu device (device: 0, name: GeForce GTX 870M, pci bus id: 0000:01:00.0, compute capability: 3.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
However, GTX 870M's computing capability is listed as 5.0 (Maxwell). My questions are (1) what is GTX 870M's computing capability, and (2) Can I run tensorflow-gpu (latest or nightly) with GTX 870M? Thanks, CC.
I have a Razer Blade 14 2014 with the same GPU on Windows and run on the same problems. Unfortunately the CUDA compute capability is listed as 3.0 for this GPU.
In the context on Linux you have an advantage, for computing capability of 3.0 you can build the code from source using the official instructions, they recommend docker when doing this: https://www.tensorflow.org/install/source
A post I found a post where the problem is solved can help as well.
Please let me know if you could make it work, I will try to install it using latest stable Ubuntu Mate 18.04.2 LTS.
TensorFlow fails to use nvidia card though nvidia driver, cuda toolkit, cudnn installed and configured.
One thing that I suspect is the reason is the nvidia card on my laptop is connected to pci as 3d controller instead of VGA:
00:02.0 VGA compatible controller: Intel Corporation Sky Lake Integrated Graphics (rev 07)
Subsystem: ASUSTeK Computer Inc. Skylake Integrated Graphics
Kernel driver in use: i915_bpo
01:00.0 3D controller: NVIDIA Corporation GK208M [GeForce 920M] (rev a1)
Subsystem: ASUSTeK Computer Inc. GK208M [GeForce 920M]
Kernel modules: nvidiafb, nouveau, nvidia_304
Even the Nvidia xserver settings don't see the GPU:
Is this true that tensorflow can only use the graphic card as VGA?
After three month, I finally figured out even first what the issue is and resolved it. It turned out to be a nvidia issue with Secure Boot.
Feel obliged to thank jorgemf and Yao Zhang for your help at a time I couldn't even good articulate the problem.
Meanwhile I hope my case can help other people having a same problem.
All started with my attempt to install nvidia driver again today. The installation seemed successful but in the end, it says,
Unable to load the “nvidia-drm” kernel module.
So I thought maybe I could manually load the kernel with
modprobe mvidia-drm
but got an error says something like "required key not applicable". Wonder what that meant so googled a bit. It turned out to be application not registered! So that module has been stopped by Secure Boot!
Went back to boot settings and disabled secure boot. Installed nvidia driver again, successful! Now in Nvidia settings it looks like this:
See now the gpu device shows there.
Head further to install cuda and cudnn. Found this github gist super useful: https://gist.github.com/wangruohui/df039f0dc434d6486f5d4d098aa52d07
Last step, just followed the installation on Tensorflow home page. Tested it did run on GPU!
The take-home message is if you fail to install Nvidia driver on linux system, you probably need to disable Secure Boot. Personal opinion, Windows turned this good idea into a nightmare for linux users!
I'm new to Adobe Premiere and GPU acceleration. I started to follow simple tutorial on editing video with Premiere Pro CC that I had "Stopped Working" error after seconds when I hovered on my video or dragged it. Found that problem is because of OpenCL. So I put my settings to "Software Only" to have just CPU rendering.
My hardware and software:
HP ProBook 450 G1
Microsoft Windows 8.1 X64
AMD Radeon 8600/8700M
14.12 AMD Catalyst Omega Software
Intel HD 4600
AMD APP SDK 2.9
Microsoft Visual Studio Ultimate 2013
(For web developing. I'm not a CPP programmer.)
Adobe Premiere Pro CC
I used GPU-Z to have details about my AMD GPU and I saw that OpenCL is disabled and other one (Intel) is enabled.
Image
So I used /program files/adobe/adobe premiere pro cc/gpusniffer.exe and this is the output:
Found 2 devices supporting GPU computation.
OpenCL Device 0 -
Name: Intel(R) HD Graphics 4600
Vendor: Intel
Capability: 1.2
Driver: 1.2
Total Video Memory: 1348MB
* Not enabled by default because it did not match the named list of cards.
OpenCL Device 1 -
Name: Oland
Vendor: AMD
Capability: 2
Driver: 1.2
Total Video Memory: 2048MB
I read all the docs of APP SDK but I didn't find anything except this one:
Output of /windows/system32/clinfo.exe
Compiler available: Yes
Execution capabilities:
Execute OpenCL kernels: Yes
Execute native function: No
Queue properties:
Out-of-Order: No
Profiling : Yes
Platform ID: 00007FFBA45D6B60
Name: Oland
Vendor: Advanced Micro Devices, Inc.
Device OpenCL C version: OpenCL C 1.2
Driver version: 1642.5 (VM)
Profile: FULL_PROFILE
Version: OpenCL 1.2 AMD-APP (1642.5)
What should I do in order to enable OpenCL in GPU-Z for my AMD Radeon GPU?
Thanks.
After two weeks Googling for my problem I found my answer in playing with regedit.
To have fun with OpenCL on Windows 8.1 and AMD Radeon we must do these:
Only use AMD Catalyst Control Center downloaded from AMD official website. (For me, installer downloaded from HP Support Center didn't work. I think because it didn't contains some packages.)
Download and install AMD APP SDK from AMD Developers official website.
Go to C:\Program Files (x86)\AMD APP SDK\2.9\bin. (It will be different based on your version.)
Copy and replace files from x86 folder (OpenCL.dll and amdocl.dll) to C:\Windows\SysWOW64.
Copy and replace files from x86_64 folder (OpenCL.dll and amdocl64.dll) to C:\Windows\System32.
Note: OpenCL.dll files are different with each other. Pay attention.
Open Start and type regedit in search or RUN.
Go to Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Khronos\OpenCL\Vendors\.
Add amdocl64.dll as DWORD (32-bit) Value. (Do not edit it after creation!)
Navigate to Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Khronos\OpenCL\Vendors\.
Add amdocl.dll as DWORD (32-bit) Value.
Restart windows (Because of Catalyst) and start Catalyst.
In Premiere go to File -> Project Settings -> General -> Video Rendering and Playback and set Renderer to Mercury Playback Engine GPU Acceleration (OpenCL).
Note: In Registry Editor, 0 means true (enabled) and 1 means false (disabled) for OpenCL.
Note: regedit must run as administrator.
Done! Adobe Premiere Pro CC works fast and fine. Note: GPU-Z will not show OpenCL enabled. I think because its old version.
Image
I have setup a kubernetes node with a nvidia tesla k80 and followed this tutorial to try to run a pytorch docker image with nvidia drivers and cuda drivers working.
I have managed to install the nvidia daemonsets and i can now see the following pods:
nvidia-driver-installer-gmvgt
nvidia-gpu-device-plugin-lmj84
The problem is that even while using the recommendend image nvidia/cuda:10.0-runtime-ubuntu18.04 i still can't find the nvidia drivers inside my pod:
root#pod-name-5f6f776c77-87qgq:/app# ls /usr/local/
bin cuda cuda-10.0 etc games include lib man sbin share src
But the tutorial mention:
CUDA libraries and debug utilities are made available inside the container at /usr/local/nvidia/lib64 and /usr/local/nvidia/bin, respectively.
I have also tried to test if cuda was working through torch.cuda.is_available() but i get False as a return value.
Many help in advance for your help
Ok so i finally made nvidia drivers work.
It is mandatory to set a ressource limit to access the nvidia driver, which is weird considering either way my pod was on the right node with the nvidia drivers installed..
This made the nvidia folder accessible, but im'still unable to make the cuda install work with pytorch 1.3.0 .. [ issue here ]