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Products that do what RightNow CUDA Editor does

AI code editor for GPU development

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    RightNow197

    AI code editor for GPU kernel development

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    The first GPU-native code editor with AI

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    Claude Code for CUDA, an open-source AI CLI for GPU devs

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  5. 5HR

    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.

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    AI models that run on an inference cloud optimized for speed

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    PearAI418

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  8. 8DO

    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

  9. 9

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    RunInfra156

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    Forge CLI107

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  12. 12

    On-GPU AI, built for the game

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  13. 13IB

    Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…

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    Run and train AI models locally on your desktop

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    Cursor210

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    This is a vector index I built that supports insertion and k-nearest neighbors (k-NN) querying, optimized for GPUs. It operates entirely in CUDA and can process queries on half a billion vectors in under 200 milliseconds. The codebase is structured as a standalone library with an HTTP API for remote access. It’s intended for high-performance search tasks—think similarity search, AI model retrieval, or reinforcement learning replay buffers. The codebase is located at https://github.com/rodlaf/BinaryGPUIndex.

    2025 · rlafuente.com

  18. 18

    AI code editor for PyTorch development on GPU workspaces

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  19. 19
    CUDA 13.1167

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    Grov123

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    Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels

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  23. 23

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    Finyuus81

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