Moonglow

Easily run local notebooks on remote GPUs

PremiumNewProductProgrammingJupyter NotebooksGPU Acceleration

Moonglow is a service that allows users to run local Jupyter notebooks on remote GPUs without the hassle of managing SSH keys or installing packages. The service was founded by Leila and Trevor, with Leila having built high-performance infrastructure at Jane Street, and Trevor conducting machine learning research at Stanford's Hazy Research Lab.

Seamlessly switch from CPU to GPU runtime in seconds
No need to manage SSH keys
package installations
or other DevOps challenges
Offers multiple GPU options
including A40
A100
H100
etc.
Directly manage GPUs in the IDE

\Moonglow is designed for technical professionals and data scientists who require high-performance computing resources
especially those working in machine learning and deep learning fields. It simplifies the use of GPU resources
allowing users to focus more on model training and data analysis rather than on configuring and managing underlying hardware.\

Use Moonglow to train a ResNet model on the CIFAR-10 dataset
completing it in under 1 minute and 15 seconds from scratch.
Data scientists utilize Moonglow to seamlessly switch GPU resources in the IDE for large-scale data processing and model training.
Enterprise teams use the enterprise version of Moonglow to share GPU resources for collaborative completion of complex machine learning projects.

Visit the Moonglow official website and register an account
Select the appropriate GPU type and connect to Runpod
Start
stop
or restart GPU resources directly in the IDE

Visit

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