cuda-samples
Remotery
cuda-samples | Remotery | |
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15 | 2 | |
5,348 | 2,730 | |
3.7% | - | |
5.0 | 7.9 | |
22 days ago | 3 months ago | |
C | C | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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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...
Remotery
- Remotery - Single c file, realtime cpu/gpu profiler with remote web viewer
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We Trace a KV Database with Less Than 5% Performance Impact
Remotery - https://github.com/Celtoys/Remotery
Visual Studio's built-in profiler is an ok sampling profiler. It doesn't give you a nice multi-thread view which is a huge advantage to a span based profiler.
MTuner is quite nice for debugging memory usage. Which is another gaping hole in the Rust ecosystem. https://github.com/milostosic/mtuner
Lots of tools generate data in a format viewable by the Chrome trace viewer. I think Chrome's tracer viewer is not great. Maybe someday someone will create a viewer for the format that's good. I get cranky when large traces don't render at 60fps. Web-based viewers are almost all very very slow and it makes me sad.
What are some alternatives?
VkFFT - Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library
easy_profiler - Lightweight profiler library for c++
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.
Celero - C++ Benchmark Authoring Library/Framework
geodesic_raytracing
libtap - Write tests in C
hashcat - World's fastest and most advanced password recovery utility
VLD - Visual Leak Detector for Visual C++ 2008-2015
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)
benchmark - A microbenchmark support library
RAJA - RAJA Performance Portability Layer (C++)
hayai - C++ benchmarking framework