Using SAS Studio on the Quest Analytics Nodes

Quest and Kellogg Linux Cluster Downtime, December 14 - 18.

Quest, including the Quest Analytics Nodes, the Genomics Compute Cluster (GCC), the Kellogg Linux Cluster (KLC), and Quest OnDemand, will be unavailable for scheduled maintenance starting at 8 A.M. on Saturday, December 14, and ending approximately at 5 P.M. on Wednesday, December 18. During the maintenance window, you will not be able to login to Quest, Quest Analytics Nodes, the GCC, KLC, or Quest OnDemand submit new jobs, run jobs, or access files stored on Quest in any way including Globus. For details on this maintenance, please see the Status of University IT Services page.

Quest RHEL8 Pilot Environment - November 18.

Starting November 18, all Quest users are invited to test and run their workflows in a RHEL8 pilot environment to prepare for Quest moving completely to RHEL8 in March 2025. We invite researchers to provide us with feedback during the pilot by contacting the Research Computing and Data Services team at quest-help@northwestern.edu. The pilot environment will consist of 24 H100 GPU nodes and seventy-two CPU nodes, and it will expand with additional nodes through March 2025. Details on how to access this pilot environment will be published in a KB article on November 18.

How to connect to, transfer files to, and use SAS Studio on the Quest Analytics Nodes.

Overview

The Quest Analytics Nodes allow users with active Quest allocations to use SAS Studio from a web browser. See Research Computing: Quest Analytics Nodes for an overview of the system.

Note: you cannot submit jobs to the Quest job scheduling system using the Quest Analytics Nodes.

Connecting

Users must already have a Quest account and an active Quest allocation.

Connections to the Quest Analytics Nodes are limited to the Northwestern network. If you are connecting from off-campus, you must use the Northwestern VPN.

Using any browser, connect to: https://sas.questanalytics.northwestern.edu

Sign in with your NetID and password.

Sessions time out after one hour of inactivity.

Transferring and Accessing Files

All of the Quest file systems are accessible from the Quest Analytics Nodes. You can transfer files using the methods to transfer files to Quest more generally.

You can also transfer files smaller than 500MB using the SAS Studio interface. See the upload icon in the Server Files and Folders window in the upper left of the session.



When you first connect to SAS Studio, you will be in your Quest home directory (/home/<netid>). To access your projects directory (/projects/<allocationID>), create a new folder shortcut. To do this, click on the icon in the upper left in the Server Files and Folder window that looks like a rectangle with an * on it.



From the Menu, choose Folder Shortcut. Then give the shortcut a name and enter the path to your projects folder. For example, if your allocation ID was p200000



When you click Save, the folder is now accessible from the Folder Shortcuts menu in Server Files and Folders:




You can access any of your files on Quest in your scripts by specifying the full path to the file.

To transfer files larger than 500MB to Quest, please use SFTP or another transfer method.

System Details

SAS is version 9.4 with maintenance release 4 applied (STAT module is version 14.2).

Users are limited to 4GB of RAM (memory) for SAS sessions on the Analytics Nodes. Researchers requiring more RAM for SAS processes should use interactive or batch jobs on Quest. Multicore and parallel processes should not be run on the Analytics nodes. Users needing to run computationally intensive jobs should schedule interactive or batch jobs on Quest instead of using the Analytics nodes.

Issues or Problems with the Analytics Nodes

To report issues or problems with the Analytics Nodes, please email quest-help@northwestern.edu with information on which service you were using (SAS Studio), the error you received or problem you encountered, and what you were doing prior to the problem occurring. Please note that you were using the Analytics Nodes.
 

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