ocl
ILGPU
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ocl | ILGPU | |
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7 | 6 | |
694 | 1,053 | |
3.0% | - | |
5.9 | 9.0 | |
18 days ago | 5 days ago | |
Rust | C# | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
ocl
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An example for OpenCL 3.0?
Please note that OpenCL consists of two parts: host API and a separate language which is used to write kernels (code which is going to be offloaded to devices). OpenCL specification describes host APIs as C-style APIs and that is what implementors has to provide. However, there are number of various libraries which provides bindings for other languages: - C++ - Python - Go - Rust
- Any OpenCL + Rust Guides
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Non graphical computing on GPU
ocl
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Resources for Vulkan GPGPU searched
I don't know a lot about Rust, but this looks like a valid set of OpenCL bindings for Rust: https://github.com/cogciprocate/ocl
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What's the current state of GPU compute in rust?
If you prefer an open alternative to CUDA, there are complete, easy to use und well documented bindings for opencl: https://github.com/cogciprocate/ocl/
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Trying to install something using rust and really stuck, any help at all appreciated.
- https://github.com/cogciprocate/ocl/issues/202
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Making an algorithmic trading bot in Rust?
I use Rust with OpenCL (ocl). And I am still in college studying CS. It takes a while to setup OpenCL depending on what you want to do with it. But performance benefits are well worth it. On average I can backtest 4 years of data with 1 minute candles in about 8.745 ms for typical RSI indicator. This is done on i5-3320m CPU (not iGPU). Took me a year to build it. Was also learning rust with it. My project has many features so you probably can do it in half amount of time or even less. Currently the project has 21k in Rust and 2k lines in OpenCL.
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
What are some alternatives?
nvfancontrol - NVidia dynamic fan control for Linux and Windows
CUDAfy.NET - CUDAfy .NET allows easy development of high performance GPGPU applications completely from the .NET. It's developed in C#.
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
ZenTimings
GLSL - GLSL Shading Language Issue Tracker
NvAPIWrapper - NvAPIWrapper is a .Net wrapper for NVIDIA public API, capable of managing all aspects of a display setup using NVIDIA GPUs
vuh - Vulkan compute for people
Hybridizer - Examples of C# code compiled to GPU by hybridizer
autograph - Machine Learning Library for Rust
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.
RustaCUDA - Rusty wrapper for the CUDA Driver API
arrayfire-rust - Rust wrapper for ArrayFire