Getting started on Karst

Karst (karst.uits.iu.edu) is Indiana University's high-throughput computing cluster. Designed to deliver large amounts of processing capacity over long periods of time, Karst's system architecture provides IU researchers the advanced performance needed to accommodate high-end, data-intensive applications critical to scientific discovery and innovation. Karst also serves as a "condominium cluster" environment for IU researchers, research labs, departments, and schools.

Karst is equipped with 228 general access compute nodes and 28 condo nodes, plus 16 dedicated data nodes for separate handling of data-intensive operations. All nodes are IBM NeXtScale nx360 M4 servers, each equipped with two Intel Xeon E5-2650 v2 8-core processors. Each compute node has 32 GB of RAM and 250 GB of local disk storage. Each data node has 64 GB of RAM and 24 TB of local storage. All nodes run Red Hat Enterprise Linux (RHEL) 6 and are connected via 10-gigabit Ethernet to the IU Science DMZ.

Karst provides batch processing and node-level co-location services that make it well suited for running high-throughput and data-intensive parallel computing jobs. Karst uses TORQUE integrated with Moab Workload Manager to coordinate resource management and job scheduling. The Data Capacitor II and Data Capacitor Wide Area Network 2 (DC-WAN2) parallel file systems are mounted for temporary storage of research data. The Modules environment management package on Karst allows users to dynamically customize their shell environments.

Following are some useful documents to help you get started running compute jobs on Karst:

On this page:


System overview

Accounts, access, and user policies

Setting up your user environment

Running jobs

X forwarding and interactive jobs

Application-specific help

Getting help

Support for IU research computing systems, software, and services is provided by various UITS Research Technologies units. For help, see Research computing support at IU.

This is document bffh in the Knowledge Base.
Last modified on 2017-11-17 11:09:19.

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