Showing 61-80 of 133 projects
NVIDIA GPU Operator manages GPUs in Kubernetes for developers building AI-powered applications.
A self-hosted, local-only NVR and AI computer vision software with features like object detection and face recognition.
A PyTorch domain library for building recommendation systems using GPU-accelerated deep learning.
3D Gaussian splatting studio for photorealistic NeRF rendering and computer vision.
NVIDIA's C++ Standard Library for high-performance GPU computing on your system.
NVIDIA's CUDA Core Compute Libraries for accelerated computing and GPU programming in C++
A high-performance compute language extension for Rust that enables GPU acceleration and CUDA support.
Sample CUDA programming codes for GPU-accelerated molecular dynamics simulations
OneDiff: An out-of-the-box acceleration library for diffusion models.
A Python library for learning and evaluating knowledge graph embeddings
A PyTorch-based implementation of the YOLO object detection model for the NVIDIA DeepStream SDK.
GPU-accelerated t-SNE library for data visualization and dimensionality reduction.
Run AI models like LLaMA locally on your machine with Node.js bindings for llama.cpp and enforce JSON schema on the output.
Real-time dense visual SLAM system for 3D reconstruction using C++, CUDA, and SLAM techniques.
A collection of C++, CUDA, and assembly programming techniques for high-performance computing and low-latency systems.
Deep learning library for Rust with shape-checked tensors and neural networks
A deep learning package for many-body potential energy representation and molecular dynamics
This is a Chinese translation of the CUDA programming guide, a library for GPU-accelerated computing.
A Python library that helps prevent CUDA out of memory errors in PyTorch models with just 1 line of code.
NVIDIA's cooperative primitives for CUDA C++ to simplify GPU programming.
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