3 个仓库
Awesome GitHub RepositoriesZero-Copy GPU Buffer Interop
High-performance sharing of typed GPU buffers between libraries without copying data to system memory.
Distinct from Zero-Copy Image Buffers: Focuses on cross-library GPU buffer interoperability rather than image-specific shared memory or network sockets.
Explore 3 awesome GitHub repositories matching data & databases · Zero-Copy GPU Buffer Interop. Refine with filters or upvote what's useful.
Awesome Zero-Copy GPU Buffer Interop GitHub Repositories
用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
- maderix/ane
maderix/ANE
6,876在 GitHub 上查看ANE is an open-source framework for training neural networks directly on Apple's Neural Engine hardware, bypassing Apple's public Core ML toolchain through reverse-engineered private APIs. It provides low-level control over the ANE, enabling developers to compile custom compute graphs into binary kernels, partition transformer model layers into hardware-compatible subgraphs, and share GPU-allocated memory with the Neural Engine via zero-copy IOSurface buffers. The framework distinguishes itself by offering direct access to hardware performance counters and power telemetry for benchmarking thr
Shares GPU-allocated buffers directly with the Neural Engine via IOSurface to eliminate data copying.
Objective-C - wang-bin/qtav
wang-bin/QtAV
4,250在 GitHub 上查看QtAV 是一个跨平台媒体引擎和多媒体框架，结合了 FFmpeg 解码与 Qt 框架，用于音频和视频渲染。它作为一个硬件加速视频播放器、OpenGL 视频渲染器和多媒体流转码器。 该项目通过硬件抽象解码层脱颖而出，该层利用 VA-API 和 VideoToolbox 等 GPU 接口来解码高分辨率视频。它采用零拷贝内存传输路径将解码后的视频数据直接移动到图形 API，从而降低 CPU 开销并实现高性能 YUV 渲染。 该引擎涵盖了广泛的功能，包括多媒体播放控制、流同步和元数据提取。它提供通过自定义着色器和过滤器进行视频处理的工具，以及媒体转码和帧捕获。渲染支持扩展到高动态范围 (HDR) 内容、高保真字幕和专辑封面显示。 该框架直接与 Qt 事件循环和信号系统集成，将播放控制和视频输出表面绑定到用户界面。
Implements a zero-copy path to transfer decoded video data directly to GPU buffers, reducing CPU overhead.
C++ - software-mansion/typegpu
software-mansion/TypeGPU
2,564在 GitHub 上查看TypeGPU is a tool for type-safe WebGPU development that enables writing shaders in TypeScript. It translates high-level TypeScript function definitions and structures into WebGPU Shading Language source code to automate shader generation and validate logic using a type system. The project provides a mechanism for cross-library GPU interoperability by sharing typed buffers without copying data to system memory. It also integrates the Model Context Protocol to allow AI agents to inspect generated shader code and diagnose runtime errors. The system manages WebGPU resource mapping through typed
Shares typed GPU buffers between libraries without copying data to system memory for high performance.
TypeScriptgpgpugpugpu-computing
