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This page contains commonly used words and phrases that are used in research computing, if you are unsure of any of the terms, please visit the Glossary page to learn more. |
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Training
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Overview
As research becomes more compute-intensive, ARCC has made high performance compute a core service. This core service is currently being performed by The Teton Compute Environment, allowing researchers to perform computation-intensive analysis on large datasets. Using Teton, researchers have control over their data, projects, and collaborators. Built-in tools help users get up and running in a short amount of time, and the ability to request custom tools allows users to fine-tune their research procedures.
Condo Model
The model for sustaining the Condo program is premised on faculty and principal investigators using equipment purchase funds from their grants or other available funds to purchase compute nodes (individual servers) which are then added to the Teton compute cluster. Condo computing resources are used simultaneously by multiple users. Teton is a condo model resource and as such, investors do have priority on invested resources. This is implemented through preemption and jobs not associated with the investment could be requested on the system when investor submits jobs. However, if the investor chooses not to implement preemption on their resources, ARCC can disable preemption while offering next-in-line access if that mode is preferred.
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Finally, individual jobs occur runtime limits based on a study that was performed in ~2014 such that our maximum walltime for a compute job is 7 days. ARCC is currently evaluating this to determine whether the orthogonal limits of CPU count and walltime are optimal operational modes. ARCC is considering concurrent usage limits based on a relational combination of CPU count, Memory, and walltime that would allow more flexibility for different areas of science. There will likely still be an upper limit on individual compute job walltime as ARCC will not allow infinite job walltime and due to possible hardware faults.
HPC Clusters
Teton
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Teton
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Loren
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