Hybridizer VS ILGPU

Compare Hybridizer vs ILGPU and see what are their differences.

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Hybridizer ILGPU
1 6
230 1,059
1.7% -
3.8 9.0
7 months ago 5 days ago
C# C#
MIT License GNU General Public License v3.0 or later
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.

Hybridizer

Posts with mentions or reviews of Hybridizer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-25.

ILGPU

Posts with mentions or reviews of ILGPU. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-27.
  • ILGPU VS ComputeSharp - a user suggested alternative
    2 projects | 27 Oct 2023
  • CUDA integration for C#
    5 projects | /r/csharp | 8 Sep 2022
    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!
  • Is there a way to utilize the gpu in a C# program?
    5 projects | /r/csharp | 25 Dec 2021
    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
  • Is there a way to run metal shaders on CPU threads?
    1 project | /r/GraphicsProgramming | 28 Jul 2021
    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.
  • What is ILGPU | Links | FAQ
    3 projects | /r/ILGPU | 12 May 2021
    Github repo

What are some alternatives?

When comparing Hybridizer and ILGPU you can also consider the following projects:

P - The P programming language.

CUDAfy.NET - CUDAfy .NET allows easy development of high performance GPGPU applications completely from the .NET. It's developed in C#.

Testura.Code - Testura.Code is a wrapper around the Roslyn API and used for generation, saving and compiling C# code. It provides methods and helpers to generate classes, methods, statements and expressions.

ZenTimings

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.

NvAPIWrapper - NvAPIWrapper is a .Net wrapper for NVIDIA public API, capable of managing all aspects of a display setup using NVIDIA GPUs

Mond - A scripting language for .NET Core

Iron python - Implementation of the Python programming language for .NET Framework; built on top of the Dynamic Language Runtime (DLR).

arrayfire-rust - Rust wrapper for ArrayFire

PeachPie - PeachPie - the PHP compiler and runtime for .NET and .NET Core

srmd-ncnn-vulkan - SRMD super resolution implemented with ncnn library