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Description

IONOS offers GPU Servers that deliver a high-performance computing framework aimed at managing tasks that demand significantly more power than standard CPU systems can provide. This infrastructure features top-tier NVIDIA GPUs, including the H100, H200, and L40s, in addition to specialized AI accelerators like Intel Gaudi, facilitating extensive parallel processing for demanding applications. By utilizing GPU-accelerated instances, the cloud infrastructure is enhanced with dedicated graphical processors, enabling virtual machines to execute intricate calculations and handle data-heavy tasks at a much faster rate compared to traditional servers. This solution is especially well-suited for fields such as artificial intelligence, deep learning, and data science, where training models on extensive datasets or executing rapid inference processes is necessary. Furthermore, it accommodates big data analytics, scientific simulations, and visualization tasks, including 3D rendering or modeling, that necessitate substantial computational capacity. As a result, organizations seeking to optimize their processing capabilities for complex workloads can greatly benefit from this advanced infrastructure.

Description

The RAPIDS software library suite, designed on CUDA-X AI, empowers users to run comprehensive data science and analytics workflows entirely on GPUs. It utilizes NVIDIA® CUDA® primitives for optimizing low-level computations while providing user-friendly Python interfaces that leverage GPU parallelism and high-speed memory access. Additionally, RAPIDS emphasizes essential data preparation processes tailored for analytics and data science, featuring a familiar DataFrame API that seamlessly integrates with various machine learning algorithms to enhance pipeline efficiency without incurring the usual serialization overhead. Moreover, it supports multi-node and multi-GPU setups, enabling significantly faster processing and training on considerably larger datasets. By incorporating RAPIDS, you can enhance your Python data science workflows with minimal code modifications and without the need to learn any new tools. This approach not only streamlines the model iteration process but also facilitates more frequent deployments, ultimately leading to improved machine learning model accuracy. As a result, RAPIDS significantly transforms the landscape of data science, making it more efficient and accessible.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Anaconda
Apache Spark
Capital One Spark Business Banking
Databricks
Domino Enterprise AI Platform
Gradient
HEAVY.AI
HPE Ezmeral Data Fabric
IBM Cloud
IONOS
Iguazio
Intel Gaudi Software
Kinetica
NVIDIA FLARE
NVIDIA virtual GPU
Nuclio
Plotly Dash

Integrations

Anaconda
Apache Spark
Capital One Spark Business Banking
Databricks
Domino Enterprise AI Platform
Gradient
HEAVY.AI
HPE Ezmeral Data Fabric
IBM Cloud
IONOS
Iguazio
Intel Gaudi Software
Kinetica
NVIDIA FLARE
NVIDIA virtual GPU
Nuclio
Plotly Dash

Pricing Details

$3,990 per month
Free Trial
Free Version

Pricing Details

No price information available.
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

IONOS

Founded

1988

Country

Germany

Website

cloud.ionos.com/servers/gpu-server

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/rapids

Product Features

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Alternatives

Alternatives

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