awesome-repositories.com
المدونة
awesome-repositories.com

اكتشف أفضل مستودعات المصادر المفتوحة باستخدام بحث مدعوم بالذكاء الاصطناعي.

استكشفعمليات بحث منسقةبدائل مفتوحة المصدربرمجيات ذاتية الاستضافةالمدونةخريطة الموقع
المشروعحولكيفية ترتيب النتائجالصحافةخادم MCP
قانونيالخصوصيةالشروط
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

2 مستودعات

Awesome GitHub RepositoriesZero-Copy Buffer Interoperability

Mechanisms for sharing GPU memory buffers between different libraries without duplicating data to system memory.

Distinct from GPU Acceleration Libraries: Focuses on the high-performance sharing of memory buffers between libraries, rather than general GPU offloading or library integration.

Explore 2 awesome GitHub repositories matching devops & infrastructure · Zero-Copy Buffer Interoperability. Refine with filters or upvote what's useful.

Awesome Zero-Copy Buffer Interoperability GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • google-ai-edge/litertالصورة الرمزية لـ google-ai-edge

    google-ai-edge/LiteRT

    2,561عرض على GitHub↗

    LiteRT is a runtime and API for executing machine learning and generative AI models on mobile, desktop, and IoT hardware. It consists of an inference engine and a specialized environment for running quantized large language and diffusion models locally on edge hardware. The system includes an ahead-of-time model compiler that translates models into hardware-specific bytecode to reduce startup latency and memory overhead. It provides a unified interface for Neural Processing Units with automatic fallback routing to CPUs or GPUs when specific subgraph support is unavailable. An edge model conve

    Passes tensor data directly to accelerators without duplicating data to system memory to reduce latency and power.

    C++
    عرض على GitHub↗2,561
  • software-mansion/typegpuالصورة الرمزية لـ software-mansion

    software-mansion/TypeGPU

    2,564عرض على GitHub↗

    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

    Provides a mechanism for sharing typed GPU buffers between libraries without copying data to system memory.

    TypeScriptgpgpugpugpu-computing
    عرض على GitHub↗2,564
  1. Home
  2. DevOps & Infrastructure
  3. GPU Acceleration Libraries
  4. Zero-Copy Buffer Interoperability