Nvidia Geforce Gtx 1650 Update Driver
Jeremias Resendez
I have a problem with the drivers for the video card on my laptop.
At the end of 2020, I purchased a Lenovo IdeaPad Gaming 3 15ARH05 laptop.
Install the linux installation system ubuntu 20.04-kernel 5.8.0-44-generic.
This laptop has an Nvidia Geforce GTX 1650 graphics card. Unfortunately, no divers are installed on this video card. What I tried:
Please uninstall the runfile driver using the --uninstall option, afterwards use option 2) again to install drivers. Then run nvidia-bug-report.sh as root and attach the resulting nvidia-bug-report.log.gz file to your post.
I am running Ubuntu 22.04 LTS, and I was using the nvidia-driver-525 package at the time. Upon reboot however, my laptop would freeze before graphics mode started (I had a black screen with a grey cursor in the top left corner that stopped blinking after a few seconds, and then froze). I was able to enter tty mode and could use prime-select to fall back to my integrated GPU, so I can still access my system relatively normally.
I had a similar issue a few months ago when I tried installing some GPU libraries (I think it was tensorflow) and I might have accidentally broken something at the time. Back then I also fell back to my iGPU for a week or so but after reinstalling the nvidia drivers from scratch my system worked normally again.
Based on similar issues I could find via googling and my own past experience, I have tried purging all nvidia packages and installing nvidia-driver-515 (yes, that is an earlier version from what I was using before, I am aware and that was on purpose) from scratch, but that does not seem to work and the situation remains the same.
Running sudo prime-select nvidia means the blacklist disappears, but it also causes the issue to re-appear immediately (the screen turns black as if it is trying to restart my graphics driver, then the cursor blinks a few times and then freezes without graphics ever appearing. TTY is the only way to get access to my laptop at that point).
Hello thanks for your answer. I set the kernel parameter and the problem still continued so I decided to upgrade Ubuntu. I am now running Ubuntu20.04 and the drivers were upgraded to:
NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0
and still my computer freezes. Attached you can find the new log file
nvidia-bug-report.log.gz (388.6 KB)
Hello after much tests, I ended up doing a clean install on my system of ubuntu20.04, installing Nvidia driver 515, CUDA version: 11.7, and cuDNN: 8.5.0. I had to make this changes to the YOLO files in order for it to compile: Object Detection on a Webcam with Yolo - #7 by AastaLLL
After all of these changes my system works fine, no more freezes when watching videos, or random heating and/or sudden fan activations. But still when running the YOLO network my system crashes after abour 58sec ( it is an improvement because it used to crashed at 20sec with the previous drivers), and the screen goes into freeze mode and again the only way of restarting the computer is to hard reboot pressing the power button, which I just did. Attached you can find the bug report I just ran after rebooting the computer.
nvidia-bug-report.log.gz (329.5 KB)
Furthermore, when I try to download and use any of the drivers for the nvidia graphics card my computer will no longer boot successfully. It just stays on the black screen with the dell and ubuntu logos and will not progress past it. It requires a hard shut down then to select the driver indicated in the image in recovery mode. All the nvidia drivers in the image cause the boot issue.
Hello, I have just downloaded Adobe Creative Cloud a few day ago. My problem is, that with the Illustrator and Premiere Pro it informes me, that my application NVIDIA GeForce GTX 1650 is unsupported video driver. My computer is totaly new and in a good condition. I bought it with graphic card, which should be working well, as I would expect. Could I please get some advice about what can I do about it? Some updates? or installation?
You said you are using proton. Does that mean you are using steam? or something else? If using steam where was it installed from?
Please post the output of inxi -Fzxx so we can see a little bit about your system. (you may need to install inxi)
The 470 driver does not allow you to use wayland and leaves you using xorg only. That may or may not be an issue for you, but you should know that up front. The newer 495 driver on fedora does allow the use of wayland on nvidia.
A very large advantage to installing the driver from rpmfusion is that with every kernel or driver update the new kernel modules are built automatically, while installing from nvidia requires you to manually build the modules every time there is an update.
If you are using steam as your first post seems to indicate, (but you did not specify), then you should remove steam you already have installed and install it from the rpmfusion repo with sudo dnf install steam. The package installed from there is tested and configured to work on fedora. For me steam works best using xorg and not wayland.
Can someone guide me the proper installation of cuda, tensorflow and pytorch from beginning with proper compatible versions for my local machine. And which python-version, so that its packages should be compatible with cuda, torch and tensorflow.
Your GTX 1650, with a compute capability of 7.5, is supported in all currently released PyTorch binaries and you can install the stable or nightly release from here.
You would only need to install an NVIDIA driver (which seems to be the case already) as the binaries ship with their own CUDA dependencies.
E torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 308.00 MiB (GPU 0; 4.00 GiB total capacity; 5.51 GiB already allocated; 0 bytes free; 5.79 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
you first create an environment in conda with the required python version mostly 3.8.* and then pip3 install instead of conda install inside the environment and then you can use the environment as your python interpreter will use the torch GPU as your kernel in running the program
Can you please guide me, how to allocate and reserve memory. It will be very helpful to me.
Yesterday after the conversation with you, I created a tensor. Its showing allocated but reserved is still 0.
If you have an older card, NVIDIA no longer actively supports drivers for your card. This means that these drivers do not officially support the current Xorg version. It thus might be easier to use the nouveau driver, which supports the old cards with the current Xorg.
Since NVIDIA does not support automatic KMS late loading, enabling DRM (Direct Rendering Manager) kernel mode setting is required to make Wayland compositors function properly, or to allow for Xorg#Rootless Xorg.
Additionally, with the driver version 545 and above, you can also set the experimental nvidia_drm.fbdev=1 parameter, which is required to tell the NVIDIA driver to provide its own framebuffer device instead of relying on efifb or vesafb, which do not work under simpledrm.
For basic functionality, just adding the kernel parameter should suffice. If you want to ensure it is loaded at the earliest possible occasion, or are noticing startup issues (such as the nvidia kernel module being loaded after the display manager) you can add nvidia, nvidia_modeset, nvidia_uvm and nvidia_drm to the initramfs.
If you are using an old driver (e.g. nvidia-340xx-dkmsAUR), you need to create device nodes. Invoking the nvidia-modprobe utility automatically creates them. You can create /etc/udev/rules.d/70-nvidia.rules to run it automatically:
The proprietary NVIDIA graphics card driver does not need any Xorg server configuration file. You can start X to see if the Xorg server will function correctly without a configuration file. However, it may be required to create a configuration file (prefer /etc/X11/xorg.conf.d/20-nvidia.conf over /etc/X11/xorg.conf) in order to adjust various settings. This configuration can be generated by the NVIDIA Xorg configuration tool, or it can be created manually. If created manually, it can be a minimal configuration (in the sense that it will only pass the basic options to the Xorg server), or it can include a number of settings that can bypass Xorg's auto-discovered or pre-configured options.
Several tweaks (which cannot be enabled automatically or with nvidia-settings) can be performed by editing your configuration file. The Xorg server will need to be restarted before any changes are applied.
The "ConnectedMonitor" option under section Device allows overriding monitor detection when X server starts, which may save a significant amount of time at start up. The available options are: "CRT" for analog connections, "DFP" for digital monitors and "TV" for televisions.
Taken from the NVIDIA driver's README Appendix B: This option controls the configuration of SLI rendering in supported configurations. A "supported configuration" is a computer equipped with an SLI-Certified Motherboard and 2 or 3 SLI-Certified GeForce GPUs.
You want only one big screen instead of two. Set the TwinView argument to 1. This option should be used if you desire compositing. TwinView only works on a per-card basis, when all participating monitors are connected to the same card.
If you have multiple cards that are SLI capable, it is possible to run more than one monitor attached to separate cards (for example: two cards in SLI with one monitor attached to each). The "MetaModes" option in conjunction with SLI Mosaic mode enables this. Below is a configuration which works for the aforementioned example and runs GNOME flawlessly.
If you are using TwinView and vertical sync (the "Sync to VBlank" option in nvidia-settings), you will notice that only one screen is being properly synced, unless you have two identical monitors. Although nvidia-settings does offer an option to change which screen is being synced (the "Sync to this display device" option), this does not always work. A solution is to add the following environment variables at startup, for example append in /etc/profile:
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