Search Results for "gpu hardware"

Starling is an open-source 2D framework for ActionScript developers that leverages GPU acceleration via Adobe's Stage3D API to create smooth, high-performance games and applications across desktop and mobile platforms. It mimics the traditional Flash display list while dramatically improving performance, making it a popular choice for Flash developers transitioning into more efficient, hardware-accelerated environments.

Skiko is an open-source graphics library from JetBrains that provides lightweight, cross-platform bindings for the Skia graphics engine tailored specifically for Kotlin Multiplatform and Compose applications. It serves as the low-level rendering backbone for Kotlin UI frameworks like Compose for Desktop and Compose for Web, enabling smooth, GPU-accelerated 2D graphics across Windows, macOS, Linux, and other supported targets without writing native code. Skiko abstracts away platform-specific rendering details while exposing Skia’s powerful features such as high-quality text shaping, image filters, path operations, and hardware accelerated canvases, making it ideal for building rich UI components, animations, games, or custom drawing surfaces. ...

QtAV is a cross-platform and high performance multimedia playback framework based on Qt and FFmpeg. Features: timeline preview, gpu decoding etc

...Paint with fully procedural materials. Build fill layers with material nodes. Use brush nodes to create patterns and procedural brushes. ArmorPaint is designed from scratch to run completely on the GPU. This results in a smooth 4K painting experience on medium-power integrated hardware. Up to 16K texture painting is seamless using a high-end graphics card. Ray-traced baking, painting effects and viewport rendering feature running on Direct3D12 and Vulkan are in progress. ArmorPaint is powered by an in-house 3D rendering engine to achieve the best painting experience.

This repository provided a pre-release of TensorFlow and TensorFlow Addons tailored for macOS 11+ with native hardware acceleration via Apple’s ML Compute, supporting both Apple Silicon (M1) and Intel Macs. It shipped ready-made Python 3.8 wheels and install scripts so developers could quickly get an accelerated stack running without building from source. As TensorFlow added a Metal PluggableDevice path, the project directed users toward using Apple’s tensorflow-metal to get GPU acceleration on Mac directly through Metal. ...