cuda-samples
WSL
cuda-samples | WSL | |
---|---|---|
15 | 406 | |
5,348 | 16,652 | |
3.7% | 0.6% | |
5.0 | 8.6 | |
22 days ago | 5 days ago | |
C | PowerShell | |
GNU General Public License v3.0 or later | MIT License |
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cuda-samples
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Is anyone successfully using an RTX 3000-series under WSL2?
installing, building, and running WSL CUDA examples from https://github.com/nvidia/cuda-samples
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Updated Install Instructions Dec 2022
After which nvcc should be accessible to new sessions, and you can build C++ cuda stuff like cuda-samples. Python packages like pytorch should also see CUDA and be able to use it.
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Virtual Memory Management APIs for NVIDIA GPUs on Windows
I haven't found any note that these APIs do not support Windows, and it also seems that the memMapIPCDrv CUDA sample supports Windows.
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ROS with CUDA on windows
I installed nvidia-cuda-toolkit and tried to build https://github.com/NVIDIA/cuda-samples but I'm getting stupid errors... it installed nvccat /usr/bin/nvcc and the samples expect /usr/local/cuda/bin/nvcc... symlinking it to that location and it dies with
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Script to install nvidia drivers , cuda/nvcc, gcc11 and setup on Fedora 36
Can build the cuda-samples, then you have a working nvcc.
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Can't get some CUDA Samples to work
I have installed cuda and cudnn, and was testing the installation with the cuda-samples, as the Arch Wiki suggested. But, I am not able to get samples like nbody, smokeparticles, Mandelbrot, etc. to run. Although devicequery works fine, and I get the expected output, so I think there is not a problem with my cuda installation.
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Cuda application question
Hi, I don't have much experience with Nvidia Jetsons. You can find some examples on GitHub (here https://github.com/NVIDIA/cuda-samples). You can find CUDA implementations of most functions on the internet though, you just have to look for the specific thing you are looking for. Cuda kernels are not platform specific, they should work on GPUs and embedded developer boards without problems as long as you respect the limits imposed by the "compute capability" of your device, you just have to compile your code using the right architecture flag. The biggest limit you have to deal with when developing for Jetson nano is the low amount of memory.
- My GPU-accelerated raytracing renderer
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Tutorial for ubuntu 20.04
—> git clone https://github.com/NVIDIA/cuda-samples.git —> cd cuda-samples/Samples/1_Utilities/deviceQuery/ —> make —> ./deviceQuery (Result=pass?good) —> cd ~/ —> wget https://repo.anaconda.com/archive/Anaconda3-2021.11-Linux-x86_64.sh
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cuda_kde_depth_packet_processor.cu:39:10: fatal error: helper_math.h: File or directory not found
is this the source code that u are talking about ? : https://github.com/NVIDIA/cuda-samples ? I dont see any CMakeLists.txt inside...
WSL
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GoboLinux
It absolutely 100% can be true.
As an example: Windows Services for Linux 2 used a special init daemon to interact with the host OS.
That meant no systemd. That meant that the `systemctl` program wasn't there.
This baffled legions, armies, of wannabe sysadmins.
https://stackoverflow.com/questions/55579342/why-systemd-is-...
https://superuser.com/questions/1785697/systemd-in-wsl-on-wi...
https://github.com/microsoft/WSL/issues/9477
https://askubuntu.com/questions/1132230/unable-to-run-any-sy...
People on the whole have no idea how this stuff works, and they just copy magic incantations from StackOverflow to get stuff to happen. If that doesn't work, then this OS is broken. The end.
For these guys, WSL was broken.
Result:
MS hired Lennart Poettering.
https://www.theregister.com/2022/07/07/lennart_poettering_re...
He "fixed" it. Systemd now works in WSL2. All those guides for noobs now work. Everyone is happy.
In a world where tools like Flatpak and Snap are proliferating and it's driving deep divisions between Linux distros, if you think the average person struggling with Linux is going to use `ldd` to work out where the dependencies for something live, I'm afraid you are a deep guru who lives on a different plane of existence.
We now have widely-used packaging systems which simply embed an apps entire dependency tree into a package to avoid people having to work out the difference between `apt` and `rpm`. Thousands of terabytes of disk are being burned to make this stuff go away.
Yes, this is too hard. Way too hard.
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Why Linux utilities tend to run poorly on Windows
Better source: https://github.com/Microsoft/WSL/issues/873#issuecomment-425...
- Weird graphical glitch/problem in Ubuntu WSLg (OpenGL)
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RamRamRamEveryoneSleepingOnDocker
One of the bugs where on the Docker side. As I have said, there have been several since release with a lot of impact period overlap. The latest and greatest is not resolved.
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Laravel dev in Windows - Laragon vs Docker?
It's the issue of abysmal I/O performance in communication between the mounted WSL2 virtual hard disk and Windows mounts inside the WSL2 distro.
- WSL freeze seems fixed in 2.0.12
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What's the right way to open files in the system's default program from Ubuntu 22.04 in WSL 2 please?
I found this github page and I was able to reproduce this from the answer
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Ask HN: Best Docker open source alternative?
* Docker engine and not Docker Desktop in a VM. WSL2 works well after some configuration: https://github.com/microsoft/WSL/issues/6655#issuecomment-11...
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Broadcom to Cut Almost 1,300 VMware Jobs in California After Takeover
Seems to more of a Defender issue than a WSL one, see https://github.com/microsoft/WSL/issues/8995
After adding exclusions for the fsnotifier-wsl process and and both variants of the WSL distro path my disk performance was improved.
Adding the idea64.exe process also helped since I was trying to run IntelliJ against projects inside WSL.
- Bricked WSL 2 after 2.0.9 / Windows 10
What are some alternatives?
VkFFT - Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library
wslg - Enabling the Windows Subsystem for Linux to include support for Wayland and X server related scenarios
catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
genie - A quick way into a systemd "bottle" for WSL
geodesic_raytracing
Scoop - A command-line installer for Windows.
hashcat - World's fastest and most advanced password recovery utility
Single-GPU-Passthrough
nvidia-auto-installer-for-fedora-linux - A CLI tool which lets you install proprietary NVIDIA drivers and much more easily on Fedora Linux (32 or above and Rawhide)
setup-msys2 - GitHub Action to setup MSYS2
RAJA - RAJA Performance Portability Layer (C++)
mkcert - A simple zero-config tool to make locally trusted development certificates with any names you'd like.