Good Conduct on Frontera

You share Frontera with many, sometimes hundreds, of other users, and what you do on the system affects others. All users must follow a set of good practices which entail limiting activities that may impact the system for other users. Exercise good conduct to ensure that your activity does not adversely impact the system and the research community with whom you share it.

TACC staff has developed the following guidelines to good conduct on Frontera. Please familiarize yourself especially with the first two mandates. The next sections discuss best practices on limiting and minimizing I/O activity and file transfers. And finally, we provide job submission tips when constructing job scripts to help minimize wait times in the queues.

Do Not Run Jobs on the Login Nodes

Frontera's few login nodes are shared among all users. Dozens, (sometimes hundreds) of users may be logged on at one time accessing the file systems. Think of the login nodes as a prep area, where users may edit and manage files, compile code, perform file management, issue transfers, submit new and track existing batch jobs etc. The login nodes provide an interface to the "back-end" compute nodes.

The compute nodes are where actual computations occur and where research is done. Hundreds of jobs may be running on all compute nodes, with hundreds more queued up to run. All batch jobs and executables, as well as development and debugging sessions, must be run on the compute nodes. To access compute nodes on TACC resources, one must either submit a job to a batch queue or initiate an interactive session using the idev utility.

A single user running computationally expensive or disk intensive task/s will negatively impact performance for other users. Running jobs on the login nodes is one of the fastest routes to account suspension. Instead, run on the compute nodes via an interactive session (idev or by submitting a batch job.

Do not run jobs or perform intensive computational activity on the login nodes or the shared file systems.
Your account may be suspended and you will lose access to the queues if your jobs are impacting other users.

Dos & Don'ts on the Login Nodes

  • Do not run research applications on the login nodes; this includes frameworks like MATLAB and R, as well as computationally or I/O intensive Python scripts. If you need interactive access, use the idev utility or Slurm's srun to schedule one or more compute nodes.

    DO THIS: Start an interactive session on a compute node and run Matlab.

    login1$ idev
nid00181$ matlab

    DO NOT DO THIS: Run Matlab or other software packages on a login node

    login1$ matlab

  • Do not launch too many simultaneous processes; while it's fine to compile on a login node, a command like "make -j 16" (which compiles on 16 cores) may impact other users.

    DO THIS: build and submit a batch job. All batch jobs run on the compute nodes.

    login1$ make mytarget
login1$ sbatch myjobscript

    DO NOT DO THIS: Invoke multiple build sessions.

    login1$ make -j 12

    DO NOT DO THIS: Run an executable on a login node.

    login1$ ./myprogram

  • That script you wrote to poll job status should probably do so once every few minutes rather than several times a second.

Do Not Stress the Shared File Systems

The TACC Global Shared File System, Stockyard, is mounted on most TACC HPC resources as the /work ($WORK) directory. This file system is accessible to all TACC users, and therefore experiences a lot of I/O activity (reading and writing to disk, opening and closing files) as users run their jobs, read and generate data including intermediate and checkpointing files. As TACC adds more users, the stress on the $WORK file system is increasing to the extent that TACC staff is now recommending new job submission guidelines in order to reduce stress and I/O on Stockyard.

TACC staff now recommends that you run your jobs out of the $SCRATCH file system instead of the global $WORK file system.

To run your jobs out $SCRATCH:

  • Copy or move all job input files to $SCRATCH
  • Make sure your job script directs all output to $SCRATCH
  • Once your job is finished, move your output files to $WORK to avoid any data purges.

Compute nodes should not reference $WORK unless it's to stage data in or out, and only before or after jobs.

Consider that $HOME and $WORK are for storage and keeping track of important items. Actual job activity, reading and writing to disk, should be offloaded to your resource's $SCRATCH file system (see File System Usage Recommendations. You can start a job from anywhere but the actual work of the job should occur only on the $SCRATCH partition. You can save original items to $HOME or $WORK so that you can copy them over to $SCRATCH if you need to re-generate results.

More File System Tips

  • Don't run jobs in your $HOME directory. The $HOME file system is for routine file management, not parallel jobs.

  • Watch all your file system quotas. If you're near your quota in $WORK and your job is repeatedly trying (and failing) to write to $WORK, you will stress that file system. If you're near your quota in $HOME, jobs run on any file system may fail, because all jobs write some data to the hidden $HOME/.slurm directory.

  • Avoid storing many small files in a single directory, and avoid workflows that require many small files. A few hundred files in a single directory is probably fine; tens of thousands is almost certainly too many. If you must use many small files, group them in separate directories of manageable size.

  • TACC resources, with a few exceptions, mount three file systems: /home, /work and /scratch. Please follow each file system's recommended usage.

File System Usage Recommendations

File System Best Storage Practices Best Activities
$HOME cron jobs
small scripts
environment settings		 compiling, editing
$WORK store software installations
original datasets that can't be reproduced
job scripts and templates		 staging datasets
$SCRATCH Temporary Storage
I/O files
job files
temporary datasets		 all job I/O activity
see TACC's Scratch File System Purge Policy.

Limit Input/Output (I/O) Activity

In addition to the file system tips above, it's important that your jobs limit all I/O activity. This section focuses on ways to avoid causing problems on each resources' shared file systems.

  • Limit I/O intensive sessions (lots of reads and writes to disk, rapidly opening or closing many files)

  • Avoid opening and closing files repeatedly in tight loops. Every open/close operation on the file system requires interaction with the MetaData Service (MDS). The MDS acts as a gatekeeper for access to files on Lustre's parallel file system. Overloading the MDS will affect other users on the system. If possible, open files once at the beginning of your program/workflow, then close them at the end.

  • Don't get greedy. If you know or suspect your workflow is I/O intensive, don't submit a pile of simultaneous jobs. Writing restart/snapshot files can stress the file system; avoid doing so too frequently. Also, use the hdf5 or netcdf libraries to generate a single restart file in parallel, rather than generating files from each process separately.

If you know your jobs will require significant I/O, please submit a support ticket and an HPC consultant will work with you. See also Managing I/O on TACC Resources for additional information.

File Transfer Guidelines

In order to not stress both internal and external networks, be mindful of the following guidelines:

  • When creating or transferring large files to Stockyard ($WORK) or the $SCRATCH file systems, be sure to stripe the receiving directories appropriately. See STRIPING for more information.

  • Avoid too many simultaneous file transfers. You share the network bandwidth with other users; don't use more than your fair share. Two or three concurrent scp sessions is probably fine. Twenty is probably not.

  • Avoid recursive file transfers, especially those involving many small files. Create a tar archive before transfers. This is especially true when transferring files to or from Ranch.

Job Submission Tips

  • Request Only the Resources You Need Make sure your job scripts request only the resources that are needed for that job. Don't ask for more time or more nodes than you really need. The scheduler will have an easier time finding a slot for a job requesting 2 nodes for 2 hours, than for a job requesting 4 nodes for 24 hours. This means shorter queue waits times for you and everybody else.

  • Test your submission scripts. Start small: make sure everything works on 2 nodes before you try 20. Work out submission bugs and kinks with 5 minute jobs that won't wait long in the queue and involve short, simple substitutes for your real workload: simple test problems; hello world codes; one-liners like ibrun hostname; or an ldd on your executable.

  • Respect memory limits and other system constraints. If your application needs more memory than is available, your job will fail, and may leave nodes in unusable states. Use TACC's Remora tool to monitor your application's needs.