High-Performance Computing. Training. High-Speed Networking.
Ceres maintenance completed
Ceres' new storage system is now fully deployed and available for use! Read more about these updates here.
What is SCINet?
The SCINet initiative is an effort by the USDA Agricultural Research Service (ARS) to grow USDA’s research capacity by providing scientists with access to high-performance computing clusters, high-speed networking for data transfer, and training in scientific computing.
Upcoming Trainings and Events
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2024 Annual GRWG Workshop
Provides hands-on tutorials on workflows to access the SCINet HPC systems and conduct geospatial research at scale and fosters geospatial research efforts.
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Introduction to the Command line and Slurm
This hands-on workshop provides an introduction to the Linux command line and managing computing tasks on a supercomputer.
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Omics Webinar · Harnessing Transposons for Precise and Efficient Genome Editing in Plants
To recieve an invitation to upcoming webinars, fill out the Translational Omics Working Group registration survey.
Featured Stories
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SCINet as a Resource for Safeguarding and Advancing ARS's Biological Collections
Across the USDA’s Agricultural Research Service (ARS) there are nealy 100 biological collections containing millions of preserved and viable specimens including animal tissues, seeds, fungal cultures, plant accessions, pinned insects, and viral isolates. These specimens and the data about them document and support ARS research efforts and are an integral part of delivering on the Agency’s mission.
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Monte Carlo simulations on Atlas for soil content determinations
The Monte Carlo Method, or multiple probability simulation, is a mathematical technique used to estimate possible outcomes of uncertain events. The Monte Carlo Method was applied for nuclear problems by John von Neumann and Stanislaw Ulam during work on the Manhattan Project.
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SCINet Resources for Photogrammetry
Scientists at the NWRC use UAS to research long-term vegetation dynamics in sagebrush-dominated rangelands. Multispectral, hyperspectral, and natural color imagery are collected to study the effects of fire, grazing, and invasive weed encroachment.
Find out how SCINet can enable your Research
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Working Groups
Information about how our collaborators currently use SCINet
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Fellowship Opportunities
SCINet-funded research fellowship opportunities for PhD and MS level graduates
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How to Use SCINet
Quick Start guide to getting up and running with SCINet
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Running Analyses
Guides for running different analyses
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Frequently Asked Questions
Answers to common questions asked about SCINet
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Contact Us
Find who you need to contact for specific issues or requests