Teaching Cluster

Description

  • The teaching cluster is meant as a resource for students and instructors for computational computing. The teaching cluster is a full HPC cluster and students are allowed to run jobs on the head node. Students must contact instructors for course related questions and support.

Example Use Cases

  • As a student, I want to learn how to login and run a simple program on an HPC cluster with minimal setup time and effort.
  • As an instructor, I want a resource to teach my students about the different functions of high performance computing without needing to spend a lot of time to set up accounts and get the students logged in.

Service Policies

For Instructors:

  • The teaching cluster provided to all UM students, students must be official UM students with an PawPrint or UM SSO ID.
  • The environment is “research grade”. No backups or high availability. Students/TA’s are responsible for backing up any data throughout the semester.
  • Only infrastructure support is provided, there is no student/end-user support. All support requests should come through the instructor or TA’s via rcss-support@missouri.edu. Support is best effort and provided during regular business hours.
  • Software is limited to CentOS 7 packages installed via yum that require minimal configuration and a subset of Lewis scientific packages.
  • We do not support a development environment/IDE. Users need to use either sftp or emacs/vi/nano or other console based text editors. For windows users we have a site license for MobaXterm https://missouri.app.box.com/v/rcss-mobaxterm-new.
  • We take security seriously. We upgrade the entire environment (including rebooting) on a regular basis and without notice. SELinux is enforced.
  • Students must be made aware of the “Teaching Cluster Policy” and the limitations of the environment.

For Students:

  • Use of this system is governed by the rules and regulations of the University of Missouri and the University of Missouri System.
  • Users must be familiar with and abide by the UM System acceptable use policy (CRR 110.005) and the UM System Data Classification System (DCL)[1]. Collected Rules and Regulations – Chapter 110, Data Classification System[2].
  • Only DCL 1 data is permitted on the cluster Data Classification System – Definitions[3].
  • This is a shared environment with limited storage, RAM, or CPU with no quotas. Please be nice.
  • Data is not backed up and all data deleted when students graduate. This policy may be revised.
  • Students must contact instructors for course related questions and support.