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ease
features
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support

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Description

NVIDIA GPU Cloud (NGC) serves as a cloud platform that harnesses GPU acceleration for deep learning and scientific computations. It offers a comprehensive catalog of fully integrated containers for deep learning frameworks designed to optimize performance on NVIDIA GPUs, whether in single or multi-GPU setups. Additionally, the NVIDIA train, adapt, and optimize (TAO) platform streamlines the process of developing enterprise AI applications by facilitating quick model adaptation and refinement. Through a user-friendly guided workflow, organizations can fine-tune pre-trained models with their unique datasets, enabling them to create precise AI models in mere hours instead of the traditional months, thereby reducing the necessity for extensive training periods and specialized AI knowledge. If you're eager to dive into the world of containers and models on NGC, you’ve found the ideal starting point. Furthermore, NGC's Private Registries empower users to securely manage and deploy their proprietary assets, enhancing their AI development journey.

Description

NVIDIA TensorRT is a comprehensive suite of APIs designed for efficient deep learning inference, which includes a runtime for inference and model optimization tools that ensure minimal latency and maximum throughput in production scenarios. Leveraging the CUDA parallel programming architecture, TensorRT enhances neural network models from all leading frameworks, adjusting them for reduced precision while maintaining high accuracy, and facilitating their deployment across a variety of platforms including hyperscale data centers, workstations, laptops, and edge devices. It utilizes advanced techniques like quantization, fusion of layers and tensors, and precise kernel tuning applicable to all NVIDIA GPU types, ranging from edge devices to powerful data centers. Additionally, the TensorRT ecosystem features TensorRT-LLM, an open-source library designed to accelerate and refine the inference capabilities of contemporary large language models on the NVIDIA AI platform, allowing developers to test and modify new LLMs efficiently through a user-friendly Python API. This innovative approach not only enhances performance but also encourages rapid experimentation and adaptation in the evolving landscape of AI applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

PyTorch
TensorFlow
Amazon Web Services (AWS)
Domino Enterprise AI Platform
Hugging Face
Kimi K2
Kimi K2.5
Kimi K2.6
MATLAB
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DRIVE
NVIDIA GPU-Optimized AMI
NVIDIA Jetson
NVIDIA NIM
Nutanix Enterprise AI
RankLLM
Rosepetal AI
Thunder Compute
Ultralytics

Integrations

PyTorch
TensorFlow
Amazon Web Services (AWS)
Domino Enterprise AI Platform
Hugging Face
Kimi K2
Kimi K2.5
Kimi K2.6
MATLAB
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DRIVE
NVIDIA GPU-Optimized AMI
NVIDIA Jetson
NVIDIA NIM
Nutanix Enterprise AI
RankLLM
Rosepetal AI
Thunder Compute
Ultralytics

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

ngc.nvidia.com

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/tensorrt

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

HPC

Product Features

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