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What is NVIDIA NGC?

NVIDIA GPU Cloud (NGC) is a cloud-based platform that utilizes GPU acceleration to support deep learning and scientific computations effectively. It provides an extensive library of fully integrated containers tailored for deep learning frameworks, ensuring optimal performance on NVIDIA GPUs, whether utilized individually or in multi-GPU configurations. Moreover, the NVIDIA train, adapt, and optimize (TAO) platform simplifies the creation of enterprise AI applications by allowing for rapid model adaptation and enhancement. With its intuitive guided workflow, organizations can easily fine-tune pre-trained models using their specific datasets, enabling them to produce accurate AI models within hours instead of the conventional months, thereby minimizing the need for lengthy training sessions and advanced AI expertise. If you're ready to explore the realm of containers and models available on NGC, this is the perfect place to begin your journey. Additionally, NGC’s Private Registries provide users with the tools to securely manage and deploy their proprietary assets, significantly enriching the overall AI development experience. This makes NGC not only a powerful tool for AI development but also a secure environment for innovation.

What is IONOS Cloud GPU Servers?

IONOS provides GPU Servers that create a powerful computing environment tailored for handling tasks requiring much greater power than conventional CPU systems can offer. This setup includes high-quality NVIDIA GPUs, such as the H100, H200, and L40s, alongside dedicated AI accelerators like Intel Gaudi, which support extensive parallel processing for resource-intensive applications. With GPU-accelerated instances, the cloud infrastructure is further improved by integrating dedicated graphical processors, allowing virtual machines to perform complex calculations and manage data-heavy operations considerably more swiftly than standard servers. This solution is particularly advantageous in sectors like artificial intelligence, deep learning, and data science, where it is crucial to train models on large datasets or conduct fast inference processes. Additionally, it supports big data analytics, scientific simulations, and visualization tasks requiring significant computational strength, such as 3D rendering and modeling. Consequently, organizations aiming to enhance their processing power for intricate workloads can reap substantial benefits from this sophisticated infrastructure, making it an ideal choice for modern computational demands. Moreover, the flexibility of this service allows businesses to scale their resources according to project requirements, ensuring efficient performance across various applications.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Domino Enterprise AI Platform
IONOS
Intel Gaudi Software
NVIDIA GPU-Optimized AMI
NVIDIA virtual GPU
Nutanix Enterprise AI
PyTorch
TensorFlow

Integrations Supported

Amazon Web Services (AWS)
Domino Enterprise AI Platform
IONOS
Intel Gaudi Software
NVIDIA GPU-Optimized AMI
NVIDIA virtual GPU
Nutanix Enterprise AI
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

$3,990 per month
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

ngc.nvidia.com

Company Facts

Organization Name

IONOS

Date Founded

1988

Company Location

Germany

Company Website

cloud.ionos.com/servers/gpu-server

Categories and Features

Deep Learning

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

HPC

Categories and Features

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