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ILGPU Alternatives
Similar projects and alternatives to ILGPU
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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Vrmac
Vrmac Graphics, a cross-platform graphics library for .NET. Supports 3D, 2D, and accelerated video playback. Works on Windows 10 and Raspberry Pi4.
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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! 🚀
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Stream
Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.
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CUDAfy.NET
Discontinued CUDAfy .NET allows easy development of high performance GPGPU applications completely from the .NET. It's developed in C#.
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NvAPIWrapper
NvAPIWrapper is a .Net wrapper for NVIDIA public API, capable of managing all aspects of a display setup using NVIDIA GPUs
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cuda-api-wrappers
Thin C++-flavored header-only wrappers for core CUDA APIs: Runtime, Driver, NVRTC, NVTX.
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managedCuda
ManagedCUDA aims an easy integration of NVidia's CUDA in .net applications written in C#, Visual Basic or any other .net language.
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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.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better ILGPU alternative or higher similarity.
ILGPU discussion
ILGPU reviews and mentions
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 2024-10-09.
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My negative views on Rust (2023)
> https://github.com/m4rs-mt/ILGPU/releases/tag/v1.5.1
> Sept 2023.
you guys just don't get it - there's a reason why CUDA is a dialect of C/C++ and not C# and it's not because the engineers at NVIDIA have just never heard of C#.
- .Net high performance computing
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Ilgpu: Write GPU programs with C# and F#
Given IL itself is an abstract stack-based bytecode, it can be compiled to the corresponding IR, which can then target corresponding back-end - this is what ILGPU does.
C# (and F# by extension) also allows to write system-ish code, with references to locals and same C primitives, which means that you're not sacrificing in performance by having the language be higher-level. After all, you're using ILGPUs APIs first and foremost.
It also lets you do things like PTX assembly (learned about it today, haven't seen that sample before): https://github.com/m4rs-mt/ILGPU/blob/master/Samples/InlineP...
- Bend: The first high-level language that runs natively on GPUs (via HVM2)
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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
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A note from our sponsor - Stream
getstream.io | 15 Jul 2025
Stats
Basic ILGPU repo stats
12
1,585
5.7
7 days ago
m4rs-mt/ILGPU is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of ILGPU is C#.
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