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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

AMD Developer Cloud grants immediate access to high-performance AMD Instinct MI300X GPUs for developers and open-source contributors through a convenient cloud-based interface, featuring a ready-to-use environment that includes Docker containers and Jupyter notebooks, eliminating the need for any local setup. Developers can execute various workloads such as AI, machine learning, and high-performance computing on configurations tailored to their needs, whether opting for a smaller setup with 1 GPU providing 192 GB of memory and 20 vCPUs or a larger setup that includes 8 GPUs with a staggering 1536 GB of GPU memory and 160 vCPUs. The platform operates on a pay-as-you-go model linked to a payment method and offers initial complimentary hours, like 25 hours for qualifying developers, to facilitate hardware prototyping. Importantly, users maintain complete ownership of their projects, allowing them to upload code, data, and software freely without relinquishing any rights. Furthermore, this seamless access empowers developers to innovate rapidly and explore new possibilities in their respective fields.

Description

JupyterHub allows users to establish a multi-user environment that can spawn, manage, and proxy several instances of the individual Jupyter notebook server. Developed by Project Jupyter, JupyterHub is designed to cater to numerous users simultaneously. This platform can provide notebook servers for a variety of purposes, including educational environments for students, corporate data science teams, collaborative scientific research, or groups utilizing high-performance computing resources. It is important to note that JupyterHub does not officially support Windows operating systems. While it might be possible to run JupyterHub on Windows by utilizing compatible Spawners and Authenticators, the default configurations are not designed for this platform. Furthermore, any bugs reported on Windows will not be addressed, and the testing framework does not operate on Windows systems. Although minor patches to resolve basic Windows compatibility issues may be considered, they are rare. For users on Windows, it is advisable to run JupyterHub within a Docker container or a Linux virtual machine to ensure optimal performance and compatibility. This approach not only enhances functionality but also simplifies the installation process for Windows users.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Jupyter Notebook Yes 
Azure Marketplace No 
Cleanlab No 
Coiled No 
DataOps.live No 
Docker Yes 
JetBrains DataSpell No 
JupyterLab No 
NeevCloud No 
OpenHexa No 
Python Yes 
Quantinuum Nexus No 
Timbr.ai No 
Train in Data No 
Vast.ai No 
Wizata No 

Integrations

Jupyter Notebook Yes 
Azure Marketplace Yes 
Cleanlab Yes 
Coiled Yes 
DataOps.live Yes 
Docker No 
JetBrains DataSpell Yes 
JupyterLab Yes 
NeevCloud Yes 
OpenHexa Yes 
Python No 
Quantinuum Nexus Yes 
Timbr.ai Yes 
Train in Data Yes 
Vast.ai Yes 
Wizata Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

AMD

Founded

1969

Country

United States

Website

www.amd.com/en/developer/resources/cloud-access/amd-developer-cloud.html

Vendor Details

Company Name

JupyterHub

Founded

2014

Website

github.com/jupyterhub/jupyterhub

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