What is the HPC hardware ecosystem at Lafayette?

The current computational cluster includes:

  • A head/login node with dual Intel 10-core Xeon Gold 5215 (Skylake) 2.5GHz processors, 192GB of memory, and 24TB of storage
  • Three compute nodes, each with dual Intel 20-core Xeon Gold 6230 (Skylake) 2.1GHz processors (for a total of 120 cores), 192GB of memory, and 1TB of disk space
  • One high-memory compute node, with dual Intel 18-core Xeon Gold 6240 (Skylake) 2.6GHz processors, 768GB of memory, and 1TB of disk space
  • All nodes are connected by an EDR InfiniBand (100Gb/sec) network
  • SLURM is used as the scheduler
  • All nodes run on Red Hat Enterprise Linux (RHEL) version 7

In addition, through our Red Hat Enterprise Virtualization (RHEV) service, we offer the ability to stand up virtual machines (VMs) with various configurations for research and teaching needs.

How are SLURM jobs prioritized?

In situations where insufficient computational resources (e.g., cores, memory, etc.) are available to handle all pending jobs, SLURM relies on a “fair-share” algorithm to determine priority. Essentially, if you have not used many computational resources recently, you will have an earlier queue position than another user who has used a greater amount of resources.

Can I purchase computational nodes on the cluster to which I have exclusive access?

In general, nodes that comprise the computational cluster are available for general use. If you would like dedicated access to resources purchased, e.g., as part of a grant or with startup funds, it is possible to provide you and any other relevant users (e.g., your research lab, department, etc.) priority access through SLURM that can preempt existing and subsequent requests for those resources. In such cases, during times when your portion of the cluster is unused, those resources would be available for general use.

What about research computing or custom-built systems?

While the computational cluster and VMs are suitable for many research and teaching use cases, in certain instances other solutions may be necessary. The Research and High-Performance Computing team is always available to consult on your individual needs.

  • If you require specialized high-performance computational systems, such as a dedicated system with multiple GPUs or other resources to which you need ongoing exclusive access, in many cases we can install such systems in our colocation facility. Doing so can provide benefits such as redundant power, appropriate cooling, secure access, and data backup services; in some cases, we might be able to assist with system-level management (e.g., OS patches, user management, etc.) so that you can concentrate on conducting your research rather than system administration.
  • In certain cases, workstations or servers many need to be located in labs or other spaces. Depending on their configuration, we still may be able to assist with certain system administration tasks.

How can I use Stata?

Stata/MP 16 is available on the cluster, providing the ability to use up to 8 cores for parallel tasks. When logged into the cluster, you must first load the appropriate module:

module load stata/16

To launch the command-line version:

stata-mp

To launch the GUI version, you need to make sure you enabled X-forwarding when you connected to the cluster:

ssh -Y username@hpc.lafayette.edu

TheĀ -Y flag ensures that you can run GUI versions of certain programs, such as Stata. Assuming that is done, you can launch the GUI version with:

xstata-mp