4.2 Login nodes

Role of Login Nodes in an HPC Cluster

Login nodes are the main entry point to an HPC cluster for human users. You do not run your heavy computations here. Instead, you connect, prepare your work, and then hand it off to the cluster’s scheduler and compute nodes. Understanding what login nodes are for, and just as important what they are not for, is essential to using any shared system correctly and politely.

What Login Nodes Are Used For

When you first access an HPC system, you typically connect via SSH to a hostname such as login1.cluster.example.edu. This brings you to a login node. From the user’s point of view, this node provides a familiar Linux shell, your home directory, and the basic tools you need to get ready for cluster work.

Common appropriate activities on login nodes include editing source code and scripts, compiling small or medium programs, organizing files and directories, preparing data sets, creating and testing batch job scripts, running very short or very lightweight test runs, and monitoring the status of submitted jobs.

You can think of the login node as your “workspace” inside the cluster. You arrange your code and data there, and then you submit jobs that will run on the compute nodes. The login node is not the place where the main numerical work of your simulation or data analysis happens.

Typical Software and Environment on Login Nodes

Login nodes usually provide a richer and more interactive environment than compute nodes, because they are intended to be used directly by people. Text editors such as vim, nano, or emacs are almost always present. Version control tools like git are commonly available. You will also find the environment modules system that lets you load compilers, MPI stacks, numerical libraries, and application software.

Login nodes also expose the same shared filesystems that the compute nodes use. For example, your home directory, project directories, and scratch areas are typically mounted on the login node. When you place code or data in these locations, your batch jobs running on compute nodes can access them.

In addition, most clusters configure login nodes to be the primary place to run commands that interact with the job scheduler. Commands like sbatch, squeue, scancel, or cluster-specific monitoring tools are intended to be used from a login node prompt. This makes the login node the central control point where you submit jobs, inspect queues, and check your job outputs.

Resource Limits and Performance Characteristics

Login nodes are shared by many users simultaneously and are not intended to deliver the peak performance you expect from compute nodes. To prevent misuse and protect responsiveness, administrators often enforce explicit resource limits on login nodes.

These limits can include caps on CPU time per process, memory usage, and the number of processes you can start, and limits on how long an individual process may run. On some systems, any process that uses full CPU for more than a few minutes is automatically killed. On others, administrators monitor usage and may terminate inappropriate jobs manually.

You might notice that a login node feels slower when many users are active. This is another reason not to perform heavy work there. The hardware of a login node may be similar to a compute node in terms of CPU type or memory size, but the crucial difference is that resources are not exclusively reserved for your tasks. There is no batch scheduling on a login node. All interactive commands compete with other users’ commands for the same cores and memory.

Because of these constraints, performance measurements taken on login nodes are usually misleading. Never use a login node to benchmark your code or collect timing numbers meant to represent real performance. That type of measurement belongs on compute nodes under controlled job allocations.

Appropriate and Inappropriate Workloads

It is helpful to classify tasks as appropriate or inappropriate for login nodes.

Appropriate workloads include editing code, writing documentation or notes, compiling your program if the build is not extremely heavy, configuring and testing build systems like make or cmake with small test builds, running single-process test programs that finish in a few seconds, and generating or inspecting small plots and quick analyses of job outputs.

Inappropriate workloads include any long-running numerical simulation or data processing job, heavy multi-threaded or multi-process runs, large parameter sweeps or loops over many input files, memory-intensive runs that approach the capacity of the node, and high I/O load tasks that continuously read or write large files.

A useful rule of thumb is that anything you could imagine waiting for interactively on your laptop for a short time is probably safe on a login node if it is not too memory hungry. Anything you would expect to run for minutes to hours or longer, or that uses many cores, should be submitted to the scheduler and run on compute nodes.

Login Nodes and Job Submission

The main workflow involving login nodes centers around job submission. After logging in, you create or modify your job scripts. These are text files that specify which resources you need and what commands to run. On systems that use SLURM, you submit a job with a command such as sbatch job.slurm. Similar commands exist for other schedulers.

The login node forwards your request to the scheduler, which then decides when and where your job will run on the available compute nodes. From the login node, you can monitor your jobs with squeue, examine standard output and error files as they are produced in your working directory, and cancel or modify jobs if permitted.

Importantly, the login node does not execute the job steps described in your script, except for trivial pre-processing that you might explicitly perform before submission. Once submitted, the actual computation takes place entirely on compute nodes inside the allocations managed by the scheduler.

This separation simplifies the user experience. You always connect to the same familiar login host name, and from there you control your jobs. You do not manually connect to random compute nodes for routine work. The scheduler and the cluster infrastructure handle all of that for you.

Multiple Login Nodes and Load Balancing

Many clusters provide several login nodes behind a single address. When you connect to login.cluster.example.edu, a load balancer may route you to login1, login2, or another node. This spreading of users helps keep any single login node from becoming overloaded.

From the user’s point of view, each login node looks similar. Your home directory and shared filesystems are the same, your environment modules behave the same, and the scheduler commands work in the same way. However, your interactive processes only exist on the specific login node that your current SSH session uses.

This has some practical consequences. For example, if you start a long editing session or a small test run, then disconnect and reconnect later, you might land on a different login node. Unless you use a persistent session tool such as tmux or screen, your original processes will not be visible. Those processes might even continue to run on the old login node if they were not terminated, which can lead to confusion.

For that reason, many users rely on terminal multiplexers on login nodes. These tools keep your session alive on the login node even if your network connection drops. They also give you a stable place to run monitoring commands or develop code without losing state whenever you disconnect.

Security and Access Control on Login Nodes

Login nodes are usually the only cluster nodes accessible from outside networks. They form a security boundary between the external world and the internal cluster networks that connect compute nodes, management nodes, and storage.

Secure access mechanisms such as SSH keys, multi-factor authentication, or VPNs are often enforced at the login nodes. Once you pass the authentication step, you gain access to the internal cluster environment. Compute nodes typically do not accept direct incoming SSH connections from the internet. If you do connect to a compute node interactively, your connection originates from a login node, not from your local machine.

Because of their security role, login nodes often have stricter policies and more intensive logging than other nodes. Administrators may audit connections and commands, enforce password policies, and monitor for suspicious activity. It is important to treat login nodes as shared and controlled resources, follow your site’s usage policies, and never attempt to bypass restrictions or run unauthorized services.

Data Movement Through Login Nodes

Login nodes are usually the primary gateway for moving data into and out of the cluster. Tools like scp, rsync, or graphical SFTP clients connect to a login node to transfer files. From the login node, files can be saved to shared filesystems that compute nodes can see.

Although you can technically use a login node to copy large data sets, you should be aware of the impact. Very large transfers during busy hours can compete with other users’ interactive work and may saturate network links. Some sites provide dedicated data transfer nodes separate from login nodes for heavy data movement. In that case, the documentation will instruct you to use specific host names for large transfers and to keep login nodes for light and moderate file operations.

Whenever you move data through a login node, store it in project or scratch areas recommended by the site, not only in your home directory. This helps keep storage balanced and avoids hitting quotas unexpectedly. It also ensures that your compute jobs will have efficient access to the data later.

Interactive Sessions and Short Test Jobs

Even if heavy computations must run on compute nodes, you might still need interactive access to those nodes to debug, profile, or test performance. The correct way to do this usually starts from a login node.

On systems with SLURM, for example, you can request an interactive allocation with a command like:

salloc -N 1 -n 4 -t 00:30:00

This command is run from the login node. The scheduler then grants you resources on one or more compute nodes. You may then be dropped into a shell running on a compute node, or you can start interactive tasks from within that allocation.

The login node remains the control point that initiates and manages these allocations, but the computations themselves do not occur there. If you exit the interactive session, you return to the login node prompt. This pattern maintains a clear distinction between management and computation.

For very short test runs that last only a few seconds and consume negligible resources, some clusters tolerate direct execution on login nodes. You must follow local policy. Often the documentation will specify acceptable limits, such as “test jobs under one minute and single core only.” When in doubt, err on the side of using the scheduler even for tests.

Good Citizenship on Login Nodes

Because login nodes are shared among many users, your behavior directly affects the experience of others. There are some common sense practices that help keep login nodes responsive and reliable.

Avoid running large loops over datasets directly on the login node. If you need to process many files, write a script and submit it as a batch job, or use an array job mechanism. Do not run multi-threaded or MPI programs on the login node, even if they seem to start successfully. Limit the number of background processes you start, and regularly check that you are not leaving stray jobs running after you log out.

When compiling very large codes, consider doing the heavy compilation step inside a short interactive allocation on a compute node instead of on the login node. This reduces load on the shared entry point and uses the cluster’s resources more fairly.

Finally, respect any specific site policies. Many clusters publish explicit guidelines such as “No job longer than 10 minutes on login nodes” or “No more than one CPU-intensive process per user.” These rules exist to keep the system usable for everyone and are a normal part of working in a multi-user HPC environment.

Summary

Login nodes form the interactive front door to an HPC cluster. They provide you with a shell environment, access to shared filesystems, tools for code development, and commands to interact with the job scheduler. At the same time, they are protected, resource-limited systems that must stay responsive and secure for all users.

By using login nodes only for light interactive work, job preparation, monitoring, and moderate data transfers, and by moving real computation to the compute nodes through the scheduler, you align with the design of the cluster and help maintain a smooth experience for yourself and others.