#gpu

The RWTH extensible training framework for universal recurrent neural networks

Suite of python packages for multiparticle simulations of particle accelerators.

Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

Typed, reproducible high-content microscopy workflows across GUI, Python, CellProfiler, Napari/Fiji, GPU, and local MCP agents.

该仓库未发布描述。

Serverside, functional (ELM style) front-end and UI for Aardvark, an open-source platform for visual computing, real-time graphics and visualization.

GPU-accelerated transparent compression S3-compatible storage gateway. Drop-in replacement for AWS S3 endpoints; cuts your S3 bill 50-80% with no app changes (Rust, nvCOMP, zstd).

Shared GPU infrastructure for the gogpu ecosystem (DeviceProvider, EventSource, Registry)

.NET library for on-demand local AI model inference — zero bundled models, lazy loading, hardware-aware GPU/CPU selection, 10 task types including embeddings, generation, vision, and audio.

A JAX backend for Apple Metal Performance Shaders (MPS), enabling GPU-accelerated JAX computations on Apple Silicon.

CUDA driver API in pure Go, no cgo: loads libcuda at runtime, embeds PTX, JIT-compiles through the driver

Production-oriented browser CAD viewer for DWG, DXF, DWF, DWFx and XPS with LibreDWG WASM, WebGL/Canvas rendering, external SHX references and native DWF support.

Search code and feature records by meaning through the command line or Model Context Protocol (MCP). Inference runs on your GPU.

The fastest .NET tensor library. Beats MathNet (6x), NumSharp (3200x), matches TorchSharp CPU - pure managed C# with hand-tuned AVX2/FMA SIMD kernels. Optional CUDA/OpenCL GPU acceleration.

Make GPUs do branchy stuff fast.

WebGPU native for C#

该仓库未发布描述。

Aardvark.Rendering is a high-performance, dependency-aware rendering engine. It is part of the open-source Aardvark Platform for visual computing, real-time graphics, and visualization.

Kubernetes-native remote dev environments for AI/ML engineers. Code locally, run on cluster GPUs — live file sync, SSH/tmux into pods, multi-pod PyTorchJob support, and detached job control.

该仓库未发布描述。

Run, deploy and monitor CLI agents in secure cloud sandboxes.

JPEG XR decoder in Rust with optional Metal and CUDA backends

Simulate GPU clusters on Kubernetes. Test GPU-aware schedulers, autoscalers and platform tooling with zero GPU hardware.

a GPU powered yet browserless tool to view markdown files in the blink of an eye

ArrayFire: a general purpose GPU library.

A Rust implementation of the Khronos OpenCL 3.0 API.

Python-facing GUI framework backend — Rust-native rendering, layout, animation, and accessibility engine with Material Design 3 components (PyO3 bindings).

A tiny hardware-accelerated pixel frame buffer. 🦀

Pure Python bindings for the pure C++11/OpenCL Qrack quantum computer simulator library