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SSCC Technical Specifications

This page contains technical information about the Social Science Computing Cluster (SSCC). For an overview of the system, please see SSCC Overview.

SSCC Basics

The SSCC is a cluster of computers (login nodes) running the Red Hat Linux operating system.

Programs with graphical interactive development environments are supported using X Windows. Well-known examples of applications with graphical IDEs are Stata, R and the MATLAB desktop. How to Connect to the SSCC explains how to get started.

Browser-based graphical interactive development environments (IDEs) are provided for R (RStudio Server) and SAS (SAS Studio).

The SSCC is designed with a single network file system (NFS) mounted on all nodes, so that your programs can run anywhere on the cluster in an identical manner. When you read a file, it is transparently transferred over the gigabit network from the NFS server to the node your program is running on. When you write a file, it is transferred over the network from your node to the NFS server. Those trips over the gigabit network are not instantaneous, and special care should be taken in the case of simultaneous access from multiple nodes or programs.

The login nodes are designed for interactive use and should not be used for long, intensive computational tasks. The login nodes have CPU time limits of 4 hours.  Users needing to run computationally intensive or long running jobs should use Quest instead.  Quest should also be used for submitting batch jobs.

SSCC Hardware Specifications


Processor Speed





Intel Xeon E5-2630

2.3 GHz

256 GB

12 cores



Intel Xeon E5-2650

2.0 GHz

256 GB

16 cores



Intel Xeon E5-2630

2.3 GHz

128 GB

12 cores

Login (restricted)

Guidelines on System Use

The SSCC is shared by many users. There are few formal constraints on users, but the following are best practices:

Users not complying with these guidelines may be contacted by system administrators and/or have their jobs cancelled.  Please contact for assistance, questions about exceeding best practice limits, help with running large jobs, or other concerns.

Last Updated: 1 September 2017

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