✨ Zero-code distributed tracing and profiling, observability via eBPF 🚀
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Updated
Jun 12, 2024 - Go
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
✨ Zero-code distributed tracing and profiling, observability via eBPF 🚀
A high-throughput and memory-efficient inference and serving engine for LLMs
OpenCV installation script with CUDA and cuDNN support
Template library for floating point operations
Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.
A GPU-based correlator for MeerKAT Extension
Containers for machine learning
A high-performance inference system for large language models, designed for production environments.
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
A retargetable MLIR-based machine learning compiler and runtime toolkit.
Drop-in, local AI alternative to the OpenAI stack. Multi-engine (llama.cpp, TensorRT-LLM). Powers 👋 Jan
CUDA C++ Core Libraries
Pytorch domain library for recommendation systems
Created by Nvidia
Released June 23, 2007