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M&CS High Performance Computing

Documentation by M&CS

This section of the documentation is maintained by M&CS. For suggestions to these pages, please contact Hub MetaForum.

Introduction

A part of the TU/e umbrella cluster can be used by the Department of Mathematics and Computer Science. It is made available for all research staff for small- to medium-scale job-based compute needs. The facility originates from a collectively expressed need by M&CS research in 2019 for low-barrier (close to home but serviced) compute resources that could facilitate most of the computations. The main goal was to enable an experimental environment to test jobs where one would not have to worry about unnecessarily burning rented compute hours from external resources.

When using the system, be aware of the impact your type of job has on the experience of others that you share the hardware with: the remarks later on this page aim to help you with this.

Characteristics

  • Ideal for getting started with high performance job-based computing
  • Account life cycle management by LIS
    • Get access to the M&CS cluster within 2 working days
    • Don't worry about account creation and forgetting passwords: use your TU/e account
  • Setup and maintenance done by the Eindhoven Supercomputing Center
  • Funded by department-wide funds
    • No funding proposal/credits needed
    • Unfunded research possible
      • Experimental use: get to know high-performance computing
      • Small to medium-scale compute needs
      • BSc/MSc seminar or thesis projects²
      • EngD/PhD candidates
  • Share resources fairly
    • No reservations possible, all nodes are available for all M&CS research
    • Get an equal fraction of resources using Slurm's Fairshare¹
  • Next steps: commercial HPC infrastructure, Snellius

Documentation

For documentation on the umbrella cluster, you can use the navigation on the left of this page.

Technical specifications

All specifications of the machines in the cluster can be found here. Users are given their own 'home' folder under /home/[username] and shared scratch space is available under /scratch-shared/[username]. The M&CS nodes have an additional 2 TB of node-specific scratch space available under $TMPDIR. Please review this page to see what storage is appropriate for different types of data (and for how long data will be stored). The mentioned file systems are not backed up.

Community

We have a mailinglist and a Teams environment for all communication concerning this cluster. Please subscribe if you want to think along about cluster development/expansion; know about technical changes or outages; be informed about workshops and hand-on sessions, etcetera. Next to that, feel free to reach out to fellow users when you have doubts about their way of using the cluster.

Specialised support

Support on your code and/or scripts is available! Contact TU/e Supercomputing Center for a consultant.

Policies & guidelines

The cluster is essentially a fixed and shared set of hardware by all researchers of M&CS. Policy states that all hardware must remain available for everybody at all times: this means isolation of machines for individual cases is not possible. Also take into account, you can expect that there are waiting times (of unexpected length), improper use of resources by others and that in the end, the cluster might not be a suitable place for your type of job. Know that we do have alternatives (please contact your Research IT consultant for the options).

  • Please consider at any time the impact of the job you’re about to run (given (expected) wall time, allocation of resources, etc.). Be especially considerate of running jobs that need less resources than what has been allocated (e.g. if you allocate 16 cores, but your script only starts 4 threads); this prevents others from using the unused resources.
  • Do not compile code or run compute tasks on the log-in node.
  • Practical suggestions, tips, and practices on how to use the cluster are collected and shared on this website. For tips on using the GPU nodes, plesae see this page for best practices.

If you have any questions about whether the M&CS HPC cluster is the best fit for your work, please review the other solutions or contact your Research IT consultant.

Rules (partition policies; technically enforced)

  • Slurm's Fairshare is used¹
  • Wall-time limit (7 days for M&CS)
  • Required to specify the number of cores/RAM explicitly for GPU queue

¹ For each researcher, usage in the last 5 minutes is computed as a fraction of available resources. Jobs from researchers with a lower usage fraction are started first. This allows for a fair distribution of jobs during popular times.
² Access for students should be requested by the supervisor. The supervisor is expected to be familiar with the service and able to assist in ensuring efficent resource usage. For large-scale use in education (e.g. courses), please contact Hub MetaForum to look for a better alternative.