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Dev tools · alternatives · 2026

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24 alternatives to Clangd for CUDA Device Code

This is clangd extended to give feedback on host and device parts of cuda, including things like syntax errors within inline ptx. Actual cuda as it is written or the clang dialect as you prefer. I like the tarball release as that's a set of x86 binaries that run as your normal user. There's other good stuff in the package too - it's a complete cuda to amdgpu or nvptx compiler toolchain. Questions / feedback welcome here or to [email protected] or via https://discord.com/invite/KNpgGbTc38 etc

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    CUDA is NVIDIA's language for GPU programming, allowing you to mix write CPU and GPU code in C++ in one file. By chaining a few projects that compile CUDA to OpenCL, then Vulkan, then WebGPU, you can experiment with this GPGPU language on any hardware.

    2025 · hipscript.lights0123.com · its alternatives →

  2. 2

    A little help for programmers, who wants to run C/C++ code in the browser. (This is my second attempt to show it, first time I got banned bcoz of my personal page domain, I don't really understand it why is is suspicious.)

    2022 · github.com · its alternatives →

  3. 3

    I am excited to announce the launch of my e-book on Graphics/WebGPU programming! This project has consumed much of my spare time, during which I developed various tools to facilitate the publishing process, including a code playground and a static site generator that can reference sample codes. However, I'm feeling burnt out and ready to call it finished, even though it may not feel completely done. Avoiding another abandoned side project has been my primary motivation in reaching this point.

    2024 · shi-yan.github.io · its alternatives →

  4. 4

    A pipeline that translates Rust GPU code into formal Coq models, as a foundation for memory model proofs - neelsomani/vericuda

    2025 · github.com · its alternatives →

  5. 5
    Flox▲375

    Hey Everyone! Ron here, part of the NixOS Foundation and building Flox. Just coming out of this years NixCon and pretty excited to show hn below :) As of today, NVIDIA officially recognizes Canonical, SUSE, CIQ, and Nix—via Flox—as supported distributors for CUDA. Full blog - https://developer.nvidia.com/blog/developers-can-now-get-cud... This is a huge win for the Nix community. For years, CUDA on Nix was possible but painful—builds could take hours, and redistributing prebuilt binaries was blocked by NVIDIA's licensing requirements. NVIDIA's growing engagement with key…

    2024 · flox.dev · its alternatives →

  6. 6MP

    I have been working on this game somewhat sparsely for the past three years or so. However, it is still in a very early stage, and there is a lot of work to do. One of my friends encouraged me to post about it here, since he felt people might find interesting how I don’t use any libraries for it. The game can be played on a browser by virtue of WebAssembly. There are native ports using either MiniFB or SDL2, but you have to build those yourself. I decided to write the game in C because I feel like it is a simple language that a lot of people can understand well enough, and I didn’t think I…

    2023 · zamfofex.neocities.org · its alternatives →

  7. 7

    Hey HN! I just released go-nbd, a lightweight Go library for effortlessly creating NBD servers and clients. Its a neat tool for creating custom Linux block devices with arbitrary backends, such as a file, byte slice or what I'm planning to use it for, a tape drive. While there are a few partially abandoned projects like this out there already, this library tries to be as maintainable as possible by only implementing the most recent handshake revision and baseline functionality for both the client and the server, while still having enough support to be useful. I'd love to get your feedback :)

    2023 · github.com · its alternatives →

  8. 8

    A langgraph based workflow with a C++ CUDA suite to optimize CUDA kernels - bertaye/agentic-cuda-optimizer

    28d ago · github.com · its alternatives →

  9. 9

    Hi HN, We’re a small team of OS, virtualization, and ML engineers, and after three years of development, we’re thrilled to launch the beta of our CUDA abstraction layer! We decouple the Kernel Shader execution from applications that use CUDA into a Wooly Abstraction layer. In this abstraction layer, we compile these to a new binary, and Shaders are compiled into a Wooly Instruction Set. At runtime, Kernel Shader launch events initiate a transfer of Shader over the network from a CPU host to a GPU host, where they are recompiled. Their execution is managed by Wooly Server software to achieve…

    2025 · woolyai.com · its alternatives →

  10. 10

    cuTile Rust provides a safe, tile-based kernel programming DSL for the Rust programming language. It features a safe host-side API for passing tensors to asynchronously executed kernel functions. - NVlabs/cutile-rs

    Jun 2026 · github.com · its alternatives →

  11. 11LA

    Learn, write, practice CUDA programming on LeetGPU.com, an online CUDA playground for anyone to write and execute CUDA code without needing a GPU and for free

    2025 · its alternatives →

  12. 12

    Modified C++ Inspired by the paper "Some Were Meant for C" by Stephen Kell, I decided to show that it's possible to iterate C++ to be safer, more explicit, and less error-prone. Here's a possible starting point: I didn't invent a new language or compiler, but took the world's best compiler, clang, and modified it to begin iterating towards a new furture of C++. Naming things is hard, so I call this 'Modified C++'. Some of the following could be implemented as tooling in a linter or checker, but the idea is to update the compiler directly. I also wanted to learn more about clang. This…

    2022 · github.com · its alternatives →

  13. 13PO

    Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml

    2017 · its alternatives →

  14. 14

    I locked in for 18 hours and built Claude Code for CUDA. It is completely open source! It writes CUDA kernels, debugs memory issues, and optimizes for your specific GPU. It is a fully agentic AI with tool calling built specifically for the CUDA toolkit This is the CLI version of RightNow AI code editor, our GPU-native code editor with a built-in emulator, visual profiling, and remote GPU access. The CLI is open source, lightweight, and fast. It is designed for anyone who wants AI help with CUDA without setup I used Python because it is the most common language, so anyone can build on top of…

    2025 · github.com · its alternatives →

  15. 15

    Tabs, splits, and tmux work fine until you have several projects open with logs, tests, and long-running shells. I kept rebuilding context instead of resuming work. Horizon puts shells on an infinite canvas. You can arrange them into workspaces and reopen later with layout, scrollback, and history intact. Built in 3 days with Claude/Codex, dogfooding the workflow as I went. Feedback and contributions welcome.

    Mar 2026 · github.com · its alternatives →

  16. 16

    Demo of agent based model on GPU with CUDA and OpenGL (Windows/Linux) Agent instances on GPU memory Uses SSBO for instanced objects (with GLSL 450 shaders) CUDA OpenGL interops Renders with GLFW3 window manager Dynamic camera views in OpenGL (pan,zoom with mouse) Libraries installed using vcpkg (https://github.com/KienTTran/ABMGPU)

    2023 · github.com · its alternatives →

  17. 17

    This project contains no code from Linux, BSD, Minix, or any other OS. Everything up until this point is written entirely from scratch, including a pure microkernel (that only implements multiprocessor priority scheduling, memory management, and interprocess communication), a work-in-progress implementation of the standard C library, and a variety of servers that provide drivers and other essential OS functionality. At the time of writing this post, the servers provide drivers for the keyboard, NVMe SSDs (that works on real hardware), a Unix-like virtual file system (with a single root…

    2024 · github.com · its alternatives →

  18. 18

    GPU Raytracer from scratch in C++/CUDA. Contribute to jan-van-bergen/GPU-Raytracer development by creating an account on GitHub.

    2021 · github.com · its alternatives →

  19. 19

    So, after years of abandoning Rust after the hello world stage, I finally decided to do something substantial. It started with simple line rendering, but I liked how it was progressing so I figured I could make a reasonably complete PSX style renderer and a game with it. My only dependency is SDL2; I treat it as my "platform", so it handles windowing, input and audio. This means my Cargo.toml is as simple as: [dependencies.sdl2] version = "0.35" default-features = false features = ["mixer"] this pulls around 6-7 other dependencies. I am doing actual true color 3D rendering (with Z buffer,…

    2025 · totenarctanz.itch.io · its alternatives →

  20. 20

    CPU & GPU with Zero Hassle Built with NVIDIA Warp, the same code runs seamlessly on both CPU and GPU — no need to deal with CUDA setup, driver issues, or device-specific kernels. Just flip one config line. Learn Modern Graphics the Easy Way Explore core concepts in differentiable rendering and parallel graphics programming — no need for expensive GPUs or thousands of lines of boilerplate. Minimalist & Educational This isn’t another massive codebase. It’s a clean, hackable implementation built for clarity — perfect for study, prototyping, or teaching yourself how Gaussian Splatting works.

    2025 · github.com · its alternatives →

  21. 21LC

    Complete llama.cpp tutorial for 2026. Install, compile with CUDA/Metal, run GGUF models, tune all inference flags, use the API server, speculative decoding, and benchmark your hardware. https://vucense.com/dev-corner/llama-cpp-tutorial-run-gguf-m...

    Apr 2026 · its alternatives →

  22. 22

    After the incredible response to our launch of the first online CUDA playground, we have just shipped something we think all you GPU programming and ML enthusiasts will love. Introducing LeetGPU Challenges--the place to compete on writing the fastest CUDA kernels. We have problems like matrix multiplication, agent simulation, multi-head self-attention, with more dropping every couple of days! We have a lot of really cool things coming up, including support for PyTorch, TensorFlow, JAX, TinyGrad; Multi-GPU programs; H100, V100, A100 GPU options Give it a try and let us know what you think!

    2025 · leetgpu.com · its alternatives →

  23. 23

    I've been working on this for ~3 months now, with pretty slow progress to be honest. So far I've got an ATA PIO mode hard disk driver, a FAT32 file system, a real time clock driver, and of course the essentials (interrupts, keyboard, pixel graphics). Kernel panics also cause a blue screen of death xD. It uses a bitmap physical memory allocator, and I'm fixing some issues with paging at the moment as a work towards running userspace applications. I'd be interested to see your thoughts on it :D

    2024 · github.com · its alternatives →

  24. 24

    I participated in the Nvidia + Vercel 2 hour hackathon in SF tonight, and built something I've wanted, but hadn't tried building. I implemented an MCP Server and VS Code extension to allow Claude Desktop to place breakpoints, step through code, and execute expressions (assuming language support). So you can ask it a question that requires actually stepping through the code and now it can actually do that - check values for you, etc. It's _definitely_ not perfect. Have improvements? Please make a PR!

    2025 · github.com · its alternatives →

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