Streamlined IT support
Adapted for large firms as well as individual engineers
Drug discovery and other chemistry and physics applications
Powerful computing resources and MD tools in one interface
Tools tailored for academic labs, students, and university communities
The pipeline for quantitative social research
Available Now: Run Algorand Relay Nodes in Galileo
Learn more about missions, storage integration, and the rest of the Galileo tool kit
Get help specifically tailored to your project, software, and programming language
Technical documents, guides, SDK information
Discussion, learning center, and your first stop for support
Streamlined IT support
Adapted for large firms as well as individual engineers
Drug discovery and other chemistry and physics applications
Tools tailored for academic labs, students, and university communities
The pipeline for quantitative social research
Powerful computing resources and MD tools in one interface
Learn more about missions, storage integration, and the rest of the Galileo tool kit
Get help specifically tailored to your project, software, and programming language
Technical documents, guides, SDK information
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Discussion, learning center, and your first stop for support
CATEGORY
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Watch Hypernet Labs CTO Todd Chapman and data scientist Matthew Gasperetti run the same R script on a brand new 8-core i9 with 32 gb of ram and then on a Galileo-enhanced Raspberry Pi. Here are the runtime results (spoiler alert): 1 minute 16 seconds on the i9 30...
Check out Product Manager John Drexler explaining how easy it is to launch your first HEC-RAS project–or other simulation or data analysis work–using...
Julia has certain built-in advantages for distributed computing as well as remote deployment, and there is now a native app—Galileo—that will allow you to quickly and easily drag and drop your Julia code to run elsewhere.
Galileo can be used to run code on a more powerful machine, in the cloud, or simply on a friend or colleague’s computer so you can free up your own machine. This is by far the fastest way that we have found to deploy our Julia scripts to remote machines.