Dev tools · alternatives · 2026
24 alternatives to HipScript – Run CUDA in the browser with WebAssembly and WebGPU
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.
HipScript enables developers to run CUDA GPU code in web browsers by converting it through multiple compilation layers—CUDA to OpenCL to Vulkan to WebGPU. This allows GPU programming experiments using NVIDIA's CUDA… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Back in the old days, people used to do general-purpose GPU programming by using shaders like GLSL. This is what inspired NVIDIA (and other companies) to eventually create CUDA (and friends). This is an implementation of GPT-2 using WebGL and shaders. Enjoy!
2025 · github.com · its alternatives →
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2024 · shadeup.dev · its alternatives →
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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 →
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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 →
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Flox▲375Hey 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 →
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2013 · zhehaomao.com · its alternatives →
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RightNow CLI▲121I 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 →
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Creator here. I built ChartGPU because I kept hitting the same wall: charting libraries that claim to be "fast" but choke past 100K data points. The core insight: Canvas2D is fundamentally CPU-bound. Even WebGL chart libraries still do most computation on the CPU. So I moved everything to the GPU via WebGPU: - LTTB downsampling runs as a compute shader - Hit-testing for tooltips/hover is GPU-accelerated - Rendering uses instanced draws (one draw call per series) The result: 1M points at 60fps with smooth zoom/pan. Live demo:…
Jan 2026 · github.com · its alternatives →
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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 →
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Hi everyone, I'm kinda involved in some retrogaming and with some experiments I ran into the following question: "It would be possible to run transformer models bypassing the cpu/ram, connecting the gpu to the nvme?" This is the result of that question itself and some weekend vibecoding (it has the linked library repository in the readme as well), it seems to work, even on consumer gpus, it should work better on professional ones tho
Feb 2026 · github.com · its alternatives →
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turbo.js - perform massive parallel computations in your browser with GPGPU. - turbo/js
2016 · github.com · its alternatives →
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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…
2025 · github.com · its alternatives →
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A langgraph based workflow with a C++ CUDA suite to optimize CUDA kernels - bertaye/agentic-cuda-optimizer
26d ago · github.com · its alternatives →
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This started out as a personal effort to learn more about machine learning. It's currently a CLI app where you give it a JSON file specifying your network architecture and hyperparameters and point it to your training data, then invoke it again in 'eval' mode with some data it's not seen before and it will try to classify each sample. I don't see many other people using Vulkan for GPGPU, and there may be many good reasons for that, but I wanted to try something a bit different. I've made every attempt to make the code very clean and readable and I've written up the math in…
2024 · github.com · its alternatives →
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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 →
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A pipeline that translates Rust GPU code into formal Coq models, as a foundation for memory model proofs - neelsomani/vericuda
Oct 2025 · github.com · its alternatives →
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WebGPU Tech Demo▲141WebGPU tech demo running in modern browsers showcasing various rendering techniques like deferred rendering with 400+ dynamic lights, Hi-Z screen space reflections and cascaded shadow mapping.
2024 · gnikoloff.github.io · its alternatives →
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Svader is a library for rendering 2D shaders on Svelte websites, using either WebGL or WebGPU. It's streamlined for the specific use case of rendering 2D graphics using fragment shaders as an alternative to SVG or the JS canvas API, so it's not meant for doing 3D objects like three.js, for example. This started as something I needed for my own project, but I eventually decided to split it into a separate library. I've since found that this use case fits really well into the Svelte compiler-based approach and its fine-grained reactivity system. In general, I think using shaders like these has…
2024 · github.com · its alternatives →
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Most languages target CPUs, but what if we target GPUs?. Tagged with showdev, discuss, rust, machinelearning.
2019 · dev.to · its alternatives →
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Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation. - ymcrcat/rgpu
14d ago · github.com · its alternatives →
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GPU Raytracer from scratch in C++/CUDA. Contribute to jan-van-bergen/GPU-Raytracer development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 22GA
2016 · erkaman.github.io · its alternatives →
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An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
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I just think they're neat
2025 · github.com · its alternatives →
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