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 RepositoriesCUDA Driver API Integrations

Low-level interfaces for coordinating GPU processing and memory allocation via the CUDA driver.

Distinct from CUDA Profiling Tool APIs: None of the candidates cover the specific host-side CUDA Driver API; they focus on profiling, web APIs, or IoT hardware.

Explore 2 awesome GitHub repositories matching operating systems & systems programming · CUDA Driver API Integrations. Refine with filters or upvote what's useful.

Awesome CUDA Driver API Integrations GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • gorgonia/gorgoniaالصورة الرمزية لـ gorgonia

    gorgonia/gorgonia

    5,919عرض على GitHub↗

    Gorgonia is a Go library that provides an automatic differentiation engine and a computation graph framework for building and training neural networks. It functions as a CUDA-accelerated tensor library and a SIMD-optimized math library, enabling machine learning workflows entirely within the Go ecosystem. The library distinguishes itself through a dual-backend architecture that dispatches neural network operations to either a GPU or CPU depending on CUDA availability at runtime. It constructs differentiable directed acyclic graphs of tensor operations, supports reverse-mode automatic gradient

    Manages GPU memory and kernel execution directly through the low-level CUDA Driver API from Go code.

    Go
    عرض على GitHub↗5,919
  • nvidia/cuda-pythonالصورة الرمزية لـ NVIDIA

    NVIDIA/cuda-python

    3,170عرض على GitHub↗

    cuda-python provides low-level Python bindings for the CUDA Driver and Runtime APIs. It serves as a programmatic wrapper for controlling device memory, managing hardware toolchains, and orchestrating execution graphs on NVIDIA GPUs, allowing for the compilation and launching of parallel kernels directly from Python. The project enables the development of SIMT kernels and the execution of mathematical algorithms on device memory. It integrates pre-compiled bytecode as custom operators and interfaces with accelerated device libraries to access low-level hardware functions without leaving the la

    Provides a programmatic interface to CUDA driver and compiler tools for coordinating hardware processing and memory.

    Cython
    عرض على GitHub↗3,170
  1. Home
  2. Operating Systems & Systems Programming
  3. CUDA Driver API Integrations