Alternatives
Products that do what Vello's high-performance 2D GPU engine to .NET does
VelloSharp v0.5.0-alpha.1 is now available, delivering Vello’s high-performance 2D GPU engine to .NET atop the wgpu 3D backend. Integrates cleanly with Avalonia, WPF, and WinForms to modernize rendering pipelines without disruptive rewrites.
- 18F
Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…
2023 · github.com
- 2L3
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
- 3HP
Nov 2025 · github.com
- 4FL
I've been playing around with https://github.com/zphang/minimal-llama/ and https://github.com/tloen/alpaca-lora/blob/main/finetune.py, and wanted to create a simple UI where you can just paste text, tweak the parameters, and finetune the model quickly using a modern GPU. To prepare the data, simply separate your text with two blank lines. There's an inference tab, so you can test how the tuned model behaves. This is my first foray into the world of LLM finetuning, Python, Torch, Transformers, LoRA, PEFT, and Gradio. Enjoy!
2023 · github.com
- 5CW
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
- 6SM
It's been closed source for a long time while I worked on it on and off as a hobby research project, but yesterday the repo was made public for the first time under the MPL 2.0 license. A feature reel showing its capabilities can be found here: https://ktstephano.github.io/rendering/stratusgfx/feature_re... A technical breakdown of a single frame can be found here: https://ktstephano.github.io/rendering/stratusgfx/frame_anal... It's still in a very beta state (bugs and instability expected), but I felt like it was a good time to make it…
2023 · github.com
- 7VA
2021 · arccompute.com
- 8IV
This is a GPU "software" raytracer (i.e. using manual ray-scene intersections and not RTX) written using the WebGPU API that renders glTF scenes. It supports many materials, textures, material & normal mapping, and heavily relies on multiple importance sampling to speed up convergence.
2024 · github.com
- 9TL
Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…
2024 · github.com
- 10G2
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
- 11VA
Been making this rasterizer engine in C++ for the past few months, now also adding ray-tracing functionality to the system. Simply load a model or generate a mesh, add some lights, and render.
2025 · github.com
- 12TC
Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
2022 · tensordock.com
- 13HR
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
- 14WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat
- 15WR
I've built a package to use Raph Levien's Vello as a blazing fast 2D renderer for React on WebGPU. It uses WASM to hook into the Rust code
Jan 2026 · github.com
- 16PO
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
- 171A
We added a new feature to our open-source HTML5 game engine today that allows you to create Sprite GPU Layers. These pack together simple JS object definitions onto the GPU and renders them using a custom vertex shader. This skips all CPU computation and GPU upload operations, resulting in vastly increased performance. For objects that don't need to be updated by input, physics, or other interactive behaviors, we found it to be a great solution. In testing, we've easily managed to blast millions of sprites around on moderate desktop-grade GPUs. Indeed, we hit the fill rate limitation of the…
2025 · phaser.io
- 18AR
I’ve been experimenting with Rust lately and wanted a project that would help me explore some of its lower-level and performance-oriented features. Inspired by Sebastian Lague’s videos, I decided to implement my own ray tracer from scratch. The initial goal was just to render a simple 3D scene in the browser at a reasonable frame rate. It evolved into a small renderer that can: • Run locally or on the web using wgpu and WebAssembly • Perform mesh rendering with a Bounding Volume Hierarchy (BVH) for acceleration • Simulate both direct and indirect illumination for photorealistic results • Be…
Nov 2025 · github.com
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- 20IM
2023 · vram.asmirnov.xyz
- 21SA
2024 · shadeup.dev
- 22DV
I'm excited to announce the release of Datoviz 0.2.0, an open-source, high-performance GPU scientific visualization library built on Vulkan. It targets the interactive visualization of large 2D/3D datasets. This version includes tentative precompiled Python wheels for Linux, macOS (ARM and Intel), and Windows. Datoviz is a key part of the CZI-funded Vispy 2.0 project and will serve as its main GPU backend. Datoviz provides core GPU visualization capabilities while VisPy 2.0 will provide high-level plotting functionality (a bit similar to NumPy vs SciPy). What I'm looking for from the…
2024 · github.com
- 23SS
Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…
2023 · shadeform.ai
- 24FT
Aug 2026 · github.com
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