ILGPU
CUDAfy.NET
| ILGPU | CUDAfy.NET | |
|---|---|---|
| 6 | 2 | |
| 1,059 | 40 | |
| - | - | |
| 9.0 | 5.4 | |
| 8 days ago | over 2 years ago | |
| C# | C# | |
| GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
ILGPU
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ILGPU VS ComputeSharp - a user suggested alternative
2 projects | 27 Oct 2023
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CUDA integration for C#
I've had a good experience with ILGPU: clean API, loads of samples, nice community. Apologies for a shameless plug, but I used it in one of my projects and happened to write a blog post about it: https://timiskhakov.github.io/posts/computing-the-convex-hull-on-gpu. Hope it helps!
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Is there a way to utilize the gpu in a C# program?
https://github.com/Sergio0694/ComputesSharp is always being recommended to me. But I also just found this one https://github.com/m4rs-mt/ILGPU which looks very interesting. There are a lot of libraries which allow you to execute on the gpu
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Is there a way to run metal shaders on CPU threads?
I would checkout the github for more details, or ask on the discord for more specifics, but all the kernels are compiled into IL by the C# compiler, then at runtime the ILGPU compiler converts them from IL into PTX, OpenCL, or back into IL (in a special way to maintain thread grouping and stuff). Then PTX / OpenCL /IL is compiled and run using the respective runtimes. Cuda for PTX, the OpenCL runtime for OpenCL, and .net for IL. We have talked about creating a CPU execution path that tries to match speeds with CPU code, but I do not think it is a big priority.
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What is ILGPU | Links | FAQ
Github repo
CUDAfy.NET
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CUDA integration for C#
I've used cudafy some years ago and it worked quite well. https://github.com/lepoco/CUDAfy.NET
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CUDA development with C#
But proof me wrong tho, not saying you should stop using it. I would personally advise you to learn C++ as this might be easier to understand if you come from a OO background. But if you still want to use C# you can look for unofficial wrappers around cuda. Here are a couple of them: - http://kunzmi.github.io/managedCuda/ - https://github.com/mlivernoche/CudaSharper - https://github.com/rapiddev/CUDAfy.NET
What are some alternatives?
ZenTimings
novideo_srgb - Calibrate monitors to sRGB or other color spaces on NVIDIA GPUs, based on EDID data or ICC profiles
NvAPIWrapper - NvAPIWrapper is a .Net wrapper for NVIDIA public API, capable of managing all aspects of a display setup using NVIDIA GPUs
waifu2x-converter-cpp - Improved fork of Waifu2X C++ using OpenCL and OpenCV
Hybridizer - Examples of C# code compiled to GPU by hybridizer
cuda-api-wrappers - Thin C++-flavored header-only wrappers for core CUDA APIs: Runtime, Driver, NVRTC, NVTX.
Amplifier.NET - Amplifier allows .NET developers to easily run complex applications with intensive mathematical computation on Intel CPU/GPU, NVIDIA, AMD without writing any additional C kernel code. Write your function in .NET and Amplifier will take care of running it on your favorite hardware.
theme-converter-for-vs - CLI tool that allows you to convert your VS Code color theme to a VS 2022 color theme.
arrayfire-rust - Rust wrapper for ArrayFire
ComputeSharp - A .NET library to run C# code in parallel on the GPU through DX12, D2D1, and dynamically generated HLSL compute and pixel shaders, with the goal of making GPU computing easy to use for all .NET developers! 🚀
srmd-ncnn-vulkan - SRMD super resolution implemented with ncnn library
CudaSharper - CUDA-accelerated functions that are callable in C#.