cuda-samples
Samples for CUDA Developers which demonstrates features in CUDA Toolkit (by NVIDIA)
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| cuda-samples | geodesic_raytracing | |
|---|---|---|
| 15 | 18 | |
| 5,306 | 78 | |
| 6.9% | - | |
| 4.9 | 9.6 | |
| 19 days ago | about 2 months ago | |
| C | C++ | |
| GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cuda-samples
Posts with mentions or reviews of cuda-samples.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-01.
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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...
geodesic_raytracing
Posts with mentions or reviews of geodesic_raytracing.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-04.
- GPU accelerated raytracer that can render any analytic metric tensor
- Introducing posh: Type-Safe Graphics Programming in Rust
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Cyberpunk 2077: Technology Preview Of New Ray Tracing: Overdrive Mode Arrives April 11th
Someone has written a geodesic ray tracer in C++.
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A cool little blackhole simulation using raytracing and gravity simulation.
If you're ever interested in building GR sims, I've got a lot of experience here and maintain a similar tool for GR raytracing here
- Researchers suggest that wormholes may look almost identical to black holes
- Astray: A performance-portable geodesic ray tracing library.
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Clang for Windows
This is untrue, I've shipped single executable binaries before with mingw. If you check out the latest project I've released, the only binary dependencies are libOpenCL.dll and the steam dll
- New C++ features in GCC 12
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My GPU-accelerated raytracing renderer
I did build an implementation for a lot of this, so if you want this is probably a reasonable reference
- Best way to simulate total time dilation across a region of space.
What are some alternatives?
When comparing cuda-samples and geodesic_raytracing you can also consider the following projects:
VkFFT - Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library
FastAD - FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
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.
Drogon-torch-serve - Serve pytorch / torch models using Drogon
hashcat - World's fastest and most advanced password recovery utility
astray - A performance-portable geodesic ray tracing library.
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)
autodiff - automatic differentiation made easier for C++
RAJA - RAJA Performance Portability Layer (C++)
papers - ISO/IEC JTC1 SC22 WG21 paper scheduling and management
blender-cuda-subdivision-surface-gpu - A Blender 3.0.0 fork that will allow you to subdivide complex meshes using CUDA compatible GPUs. (WIP)
AECforWebAssembly - A port of ArithmeticExpressionCompiler from x86 to WebAssembly, so that the programs written in the language can run in a browser. The compiler has been rewritten from JavaScript into C++.
cuda-samples vs VkFFT
geodesic_raytracing vs FastAD
cuda-samples vs catboost
geodesic_raytracing vs Drogon-torch-serve
cuda-samples vs hashcat
geodesic_raytracing vs astray
cuda-samples vs nvidia-auto-installer-for-fedora-linux
geodesic_raytracing vs autodiff
cuda-samples vs RAJA
geodesic_raytracing vs papers
cuda-samples vs blender-cuda-subdivision-surface-gpu
geodesic_raytracing vs AECforWebAssembly