Getting started with HPC

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This documentation is for researchers who have an HPC account and need to know how to connect, log in, transfer data and run jobs on HPC. An HPC account is required to log into and use HPC resources. To apply for an HPC account see the Applying for an HPC Account page.



HPC is a collection of computers and disk arrays that are connected via fast networks that allow USC researchers to run programs at a larger scale than they would be able to on a laptop or lab computer.

The schematic below gives you a general idea of how these parts connect.

When using HPC, you will notice several differences from the desktop or laptop environment with which you may be familiar.

HPC’s interface is command-line driven – there is no graphical user interface. HPC nodes run the Linux CentOS operating system and not Windows or Mac OS. You must submit your programs to a remote batch processing system to run them – although there is a way to test them interactively before they are submitted.


The workflow for using HPC typically consists of the following steps:

Login to HPC login/head node.

Organize workspace.

Transfer data and files.

Install/run software on HPC.

Test your job interactively on a compute node.

Submit your job to the batch processor, to run it remotely on a compute node.

Monitor your job and check your results when it has completed.

Log in to an HPC Login (or Head) Node To log into HPC, you will need to use a secure shell client. This is a small application that enables you to connect to a remote computer via SSH (Secure SHell), a cryptographic network protocol.

NOTE: HPC does not manage your USC NetID password. If you are having difficulty using your USC NetID and/or password, please contact the ITS Customer Support Center at 213-740-5555.

SSH (Secure Shell) Login On Windows Windows users will need to download a third-party secure shell client to connect to HPC. You may use the client that works best for you. Here are a few of the most popular clients: X-Win32, which is available through the USC software website. This USC-licensed version has a pre-configured connection to HPC. PuTTY, which is a popular third-party client that may be downloaded through the developer’s website. When configuring PuTTY, you will need to enable the Connection=>SSH=>X11=>“Enable X forwarding” option to allow HPC to send graphical displays to your laptop. To connect to HPC using any SSH client, download and install the client and then launch a connection window. You will be asked to provide your USC NetID and password.

NOTE: If you are not using X-Win32, which is preconfigured to connect to HPC, you will need to enter the following hostname in order to connect to HPC: (or

On Mac OS X Mac OS X users can connect to HPC using the Terminal application that is native on these systems. The Terminal application may be found in the Utilities group on the Mac OS X dashboard or in the Finder menu under Goand then Utilities.To connect to HPC using Terminal, open a window and type: ssh (or, where YOUR_USC_NetID is your username for the email that ends in You will then be prompted to enter your USC NetID password.

To enable graphical displays, you will need to install the from XQuartz and use the -Y command when logging into HPC, i.e.:

ssh -Y Duo Two-Factor Authentication (2FA) Duo 2FA is required to access HPC. If you have not already signed up for Duo on your USC NetID account, please go to to enrol. For more information on using Duo with your HPC account, see the Duo Two-Factor Authentication page.

Organize Directories File System Always work in your project directory! All HPC account holders are assigned two folders where they can store files and run programs. These are referred to as the home directory and project directory. Your home directory contains exactly 1 gigabyte (GB) of disk space and is strictly for personal configurations and settings. You will always start in your home directory when you log into HPC.

Your project directory is larger and will be the directory you use for most HPC work. This will also be where you will collaborate with your group. Its disk space can vary. Every user will have their own subdirectory within their group’s project directory where they can store data files. Users affiliated with multiple HPC projects will have multiple project directories so they can easily share their files with the appropriate groups.

Limits on Disk Space and Number of Files HPC is a shared resource so there are quotas on usage to help ensure fair access. There are quotas on the number of files stored and the amount of disk space used.

To check your assigned disk space quota, type the command myquota. It will return results similar to the following:

Disk Quota for /home/rcf-40/ ID 268648

           Used      Soft     Hard
   Files   1905      100000   101000
   Bytes   360.38M   1.00G    1.00G

Disk Quota for /home/rcf-proj2/ ID 735

            Used     Soft     Hard
    Files   645157   1000000  1001000
    Bytes   106.90G  1.00T    1.02T

In this example, the user has access to two different directories. The first is their home directory which has room for up to 100,000 files and 1GB of data. The second is their project directory which has room for up to 1,000,000 files and 1TB of data. Quotas for project directories are shared amongst all group members. If you exceed these limits, you may receive a “disk quota exceeded” or other type error. If your project directory becomes full, please send email to for assistance. Please note that HPC is unable to increase your home directory’s quota.

The myquota command is handy if you forget where your project directory is. You can also use the Checking Your Quotas page to check quotas.

HPC also assigns each project and project member a directory in another location called “staging”. If you need access to a large amount of temporary storage or need a high-performance (parallel) file system, you can keep data in/staging. This area is not backed up and is cleared out about every six months so don’t store data here unless it’s easily reproducible or there is a secondary copy elsewhere.

Compute Time Quota Every project is allocated a default number of computing time. To check the amount of compute time you have available you can use the command mybalance -h. The -h flag gives the results in hours. It will return results similar to:


Account:lc_hpcc Allocated CPU-Hours:5000 Used CPU-Hours:612 Available CPU-Hours:4388 Your compute usage is measured in units of CPU-hours. If you request one cpu cores for 1 hour then you consume 1 core x 1 hours = 1 core-hour. If you request 8 cpu cores for 2 two hours then you consume 8 cores x 2 hours = 16 core-hours. Note that if you leave off the -h in the command above, the results will be displayed in core-minutes.

It is a good idea to check this balance before submitting a large job. Your project PI may request additional core-hours at no cost through the project website (link). If you are in multiple research groups make sure that you keep track of which project you request compute time for or you may consume compute resources for one group while doing work for another.

Transfer Files to HPC HPC has a dedicated data transfer node (DTN),, that is configured for fast file transfers. HPC-transfer is also a Globus endpoint. Use HPC-transfer instead of an HPC-login node when logging in to transfer files. Always transfer files into your project or staging directories where you have sufficient disk space.

Between your laptop and HPC One of the easiest ways to transfer files is to use a utility like FileZilla, a Secure File Transfer Protocol (SFTP) client. It’s also possible to use the command line function scp. You can find a detailed guide on how to install and use these tools at Remember to use as the hostname when you transfer files.

From the Internet to HPC You can transfer a file from the Internet directly to your project directory on HPC (without first downloading to your laptop). For example, if want to transfer a repository from GitHub, use the command git clone REPOSITORY_URL, where REPOSITORY_URL is the link you copied from Github. If you want to transfer a file from a web page, you can use the command wget URL. If you need to transfer data from a private location (i.e., one that requires logging in), the site may or may not allow you to use wget for the transfer.

If you need to frequently transfer files, plan to move large amounts of data, or need assistance transferring data from a private location, feel free to contact us at for advice on how to do this efficiently.

Creating and Editing Files on HPC You can always create files on your personal computer and transfer them to HPC but sometimes it is easiest to create them directly on HPC.

HPC supports the vi/vim, gedit, nano and emacs text editors. Nano is used in HPC training sessions because it is an easy editor to learn. Gedit is a good option if you log in with “X11 forwarding” enabled which is pre-configured on USC’s version of X-Win32 and enabled by XQuartz’s on Mac OS. Vi/vim, which comes standard on all UNIX/Linux machines, and emacs, which is a popular coding environment, both have steeper learning curves.

To edit a file, simply type the editors name, e.g., nano or gedit, at the command line and then type in your file’s text.

Install/Run Software on HPC Once you are logged in you can use software, work with files, run brief tests, or submit Slurm scripts to the job queue. The login nodes are a shared resource so be careful not to do tasks that will impact other users. If your usage impacts other users, we may terminate your process without warning.

Installing Your Own Software on HPC Researchers are encouraged to install any software, libraries, and packages necessary for their work. HPC has a presentation on how to approach installing software on HPC. See

Using HPC-Maintained Software HPC maintains software, compilers, and libraries in the directory /usr/usc. These are programs that support distributed computing, are licensed for use on HPC, or are commonly used by HPC researchers. A current listing of software in /usr/usc/ shows the following:

[ttrojan@hpc-login3 ~]$ cd /usr/usc [ttrojan@hpc-login3 usc]$ ls

acml fftw iperf mvapich2 R amber gaussian java NAMD root aspera gcc_wrap jdk ncview ruby bazel gflags julia netcdf sas bbcp git lam netcdf-fortran schrodinger bin globus lammps nwdb sgems boost glog leveldb opencv singularity caffe gnu libroadrunner OpenGeos stata cellprofiler graph-tool llvm openmpi subversion CGAL gromacs lmod papi swig clang gurobi lua patchelf taxila cmake hadoop magma perl tdk conf hdf5 mathematica petsc tensorflow cuda hdfview matlab pgi udunits cuDNN hello_usc mkl protobuf valgrind cula hpctoolkit modulefiles python VisIt dict igraph mongo2k qchem dmtcp imp mpich qespresso etc imsl mpich2 qiime fdtd intel mpich-mx QT As an example, we’ll look at a program named hello_usc. Let’s look at what’s inside /usr/usc/hello_usc/.

[ttrojan@hpc-login3 usc]$ cd /usr/usc/hello_usc/ [ttrojan@hpc-login3 hello_usc]$ ls 1.0 2.0 3.0 default [ttrojan@hpc-login3 hello_usc]$ We have three versions of this program. We keep multiple versions of most software for compatibility. There is also a “version” called default which is a pointer to the HPC-recommended version, usually the most recent version. To see which version default points to, type the command ls -l.

[ttrojan@hpc-login3 hello_usc]$ ls -l total 28 drwxr-xr-x 3 root root 4096 Sep 28 2016 1.0 drwxr-xr-x 3 root root 4096 Sep 28 2016 2.0 drwxr-xr-x 3 root root 4096 Sep 28 2016 3.0 lrwxrwxrwx 2 root root 3 Apr 24 2015 default -> 3.0 Let’s try using the most recent version, 3.0. Within that directory, you should see another directory named bin and two “setup” scripts.

[ttrojan@hpc-login3 hello_usc]$ ls 3.0 bin setup.csh By convention, executable programs are usually installed into a subdirectory named /bin. If you list the contents of this subdirectory, you will find a program named hello_usc.

[ttrojan@hpc-login3 hello_usc]$ ls 3.0/bin/ hello_usc To use this program on HPC, you must first run a setup script. Setup scripts enable you to run software by modifying your runtime environment. You will find two scripts, and setup.csh, for every software version. The .sh and .csh suffixes indicate that the scripts are compatible with the bash and csh shells (and their derivatives), respectively. Each has its own syntax. Bash is the default shell on HPC so unless you have requested to change your default shell, you will always use For more information about Linux shells, see [link].

To use the script, run the command source.

[@hpc-login3 hello_usc]$ hello_usc -bash: hello_usc: command not found [ttrojan@hpc-login3 hello_usc]$ source /usr/usc/hello_usc/3.0/ [ttrojan@hpc-login3 hello_usc]$ hello_usc

   Hello USC!!!.
   I am version 3.0 running on host: hpc-login3

If you decide that you’d like to use a different version of the program, you can log out and log back in to reset your environment.

NOTE: While it is possible to add a source statement to directly to your login script (.bashrc or .cshrc) to automatically set the program version to use with every script, HPC recommends against doing so as they may conflict with each other and cause unexpected behavior. We recommend you put these statements in each specific job script which will be helpful when troubleshooting problems with your environment.

Test your Job We recommend that you first test your job interactively on a compute node before submitting it remotely so that you’ll be confident that you will have quality results after a job completes. You can do this by requesting an “interactive session”. This will enable you to request one or more compute nodes that you can use without impacting other users.

To request an interactive session, use the command salloc. In the example below, four processors are requested for one hour.

salloc --ntasks=4 --time=1:00:00 After running the command, the job scheduler will add your job to the wait queue. You should see a message similar to the following (where 3271 is the job id).

salloc: Pending job allocation 3271 salloc: job 3271 queued and waiting for resources When the requested resources become available and are allocated to you, you should see more messages. The Slurm prolog is displayed when the job begins.

salloc: job 3271 has been allocated resources salloc: Granted job allocation 3271 salloc: Waiting for resource configuration salloc: Nodes hpc1407 are ready for job

Begin SLURM Prolog Fri Mar 16 15:07:29 2018 Job ID: 3271 Username: ttrojan Accountname: lc_hpcc Name: sh Partition: quick Nodes: hpc1407 TasksPerNode: 4 CPUSPerTask: Default[1] TMPDIR: /tmp/3271.quick Cluster: uschpc HSDA Account: false Note: Settings of SLURM_EXPORT_ENV=NONE are cleared prior to running job-steps End SLURM Prolog

Once your job starts you can test out your programs or scripts to make sure they work properly on HPC. If there is a problem that you cannot resolve, send email to for assistance. Once you are confident that you know how your program will behave, you are ready to try out submitting a job through the batch scheduler.

Submit your Job A job consists of all commands, data, scripts and programs that will be used to obtain results. Jobs are submitted to HPC’s batch processing system (SLURM) which performs the following functions:

Schedules user-submitted jobs Allocates user-requested computing resources Processes user-submitted jobs sbatch Submitted batch job 3291 squeue

             3176     quick job05010   bbruin PD       0:00      1 (Resources)
             3291     quick helloUSC  ttrojan PD       0:00      1 (Priority)
             3181      scec 2018_03_  ggeagle  R 1-01:10:58      5 hpc[4192-4196]

Jobs submitted to the system are processed remotely. The process is recorded and written to an output file, which, by default, is named “slurm-“.

NOTE: Head nodes (hpc-login2, hpc-login3, and hpc-transfer) are shared resources that are used by many users simultaneously. Compute nodes currently are not shared (this may differ on private nodes). You may run short tests on the head nodes but beyond that you will need to use the compute nodes. HPC has only three head nodes and almost 3000 compute nodes!

See the documentation at for instructions on requesting job resources, creating and submitting a job script, and monitoring your job under Slurm.

Monitor your job There are several commands you can use to monitor a job after it has been submitted.

To see if your job has been queued: The first thing you’ll want to check is if your job request was queued. Use the squeue command to view the status of your jobs:

squeue --user username Each job is assigned a unique job identifier (Job ID). It is sufficient to use only the numeric portion of the job id when referencing a job or submitting a ticket.

In the example screenshot below, the job 3271 has been placed in the “quick” partition (PARTITION) based on its requested time of 1 hour. It has been running for 35 minutes and 58 seconds (Time). The job requested 4 tasks and was allocated 1 node (NODES). The status of the job is “R” (running).(ST).

squeue --user ttrojan

             3271     quick       sh  ttrojan  R      35:58      1 hpc1407

See the documentation at for instructions on requesting job resources, creating and submitting a job script, and monitoring your job under Slurm.

To see when your job will start: You can also use the squeue command to determine when your job will start:

squeue --start -j job_id To cancel your job and remove from queue: If you wish to delete your job from the queue, you can use the qdel command. Your job will remain in the queue for a short while but its status will change to ‘C’ for complete.

scancel job_id Getting Help If you need additional assistance getting started with HPC, please see our Getting Help page for information on online and in-person HPC assistance.