A library for visually programming on the GPU, built to enable rapid workflows and modular approaches to accelerated graphics, logic and computation.
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Updated
Nov 13, 2025 - C#
A library for visually programming on the GPU, built to enable rapid workflows and modular approaches to accelerated graphics, logic and computation.
GPUd automates monitoring, diagnostics, and issue identification for GPUs
📈 Predict market trends using a language model that reads stock charts as text, offering insights into price movements for better investment decisions.
🎮 Enhance Unity3D with this DX12 bindless plugin for efficient graphics and compute shader management, offering easy setup for developers.
🏎️ Simplify HTML and JavaScript integration with Rendu, a lightweight toolkit focused on standards and progressive rendering.
Doing non-Cartesian MR Imaging has never been so easy.
Metal programming in Julia
Tensors and Dynamic neural networks in Python with strong GPU acceleration
🌐 Enhance your Volant microVMs with this official Nginx plugin, providing robust web server functionality for your applications.
CUDA Core Compute Libraries
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.
Mersenne prime search using integer arithmetic and an IDBWT via an NTT executed on the GPU through OpenCL.
A GUI tool to overclock NVIDIA GPUs on Wayland and X11. Also supports fan curves,oc profiles, and adjusting power limits.
🧠 Optimize GPU workflows with `gpu-agent-opt`, a Python package for profiling, scientific computing, and efficient CUDA exploration.
🎯 Develop a deep learning model to accurately predict breast cancer using PyTorch, achieving approximately 97% accuracy for improved early detection.
🧠 Transform natural language into SQL queries seamlessly with Cognita, an intelligent app that simplifies database interactions for everyone.
⚙️ Automate machine learning tasks in-browser or with Node.js, utilizing efficient algorithms for regression and classification with minimal setup.
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