Bridges-2 EM

RP account needed

Bridges-2 Extreme Memory is a specialized computing resource at the Pittsburgh Supercomputing Center designed for applications that require very large amounts of shared memory. It provides nodes with up to 4 TB of RAM, enabling workloads that cannot be efficiently parallelized across multiple nodes.

Extreme Memory (EM) nodes contain 96 CPU cores and are well suited for memory-intensive applications such as statistics, graph analytics, genome sequence assembly, and other data-intensive workloads.

Resources are allocated in core-hours (Service Units), allowing users to request the number of cores needed to obtain the required memory for their applications.

Jobs

Jobs run in the EM partition and are charged in core-hours, where 1 core-hour equals 1 Service Unit (SU). For example, using one full node (96 cores) for one hour results in 96 SUs. Specific details are documented on the Accounting for Usage page on the Bridges-2 guide.

Jobs can use at most one full EM node and must specify the number of cores requested. Core counts must be requested in multiples of 24 (24, 48, 72, or 96 cores). Memory is allocated proportionally based on the number of cores requested, at approximately 1 TB per 24 cores.

Users must also specify a walltime limit when submitting jobs, or system defaults will be applied.

For more detail, please visit the Bridges-2 Extreme Memory page or the Summary table for the EM partition on the Bridges-2 guide.

Note that the EM partition does not support interactive jobs or access through OnDemand. EM jobs must be submitted in batch mode. Because of this, EM jobs must be submitted from the command line on a Bridges-2 login node. Connect via SSH first (see the Login to Bridges-2 section below), then save your batch script to your file space and submit it with the sbatch command.

When the job is submitted, sbatch echoes back a job id. You can check your job's progress with:

squeue -u PSC-username

A sample script job on the EM partition would look like this:

#!/bin/bash
#SBATCH -N 1
#SBATCH -p EM
#SBATCH -t 5:00:00
#SBATCH -n 96

# type 'man sbatch' for more information and options
# this job will ask for 1 full EM node (96 cores) and 5 hours of runtime
# this job would potentially charge 480 EM SUs

# echo commands to stdout
set -x

# move to working directory
# this job assumes:
# - all input data is stored in this directory
# - all output should be stored in this directory
# - please note that groupname should be replaced by your groupname
# - PSC-username should be replaced by your PSC username
# - path-to-directory should be replaced by the path to your directory where the executable is

cd /ocean/projects/groupname/PSC-username/path-to-directory

#run pre-compiled program which is already in your project space

./a.out

After that, you need a sbatch command to submit a job to the EM partition. An example requesting an entire node for 5 hours is:

sbatch -p EM -t 5:00:00 --ntasks-per-node=96 myscript.job

where:

-p indicates the intended partition
-t is the walltime requested in the format HH:MM:SS
--ntasks-per-node is the number of cores requested per node
myscript.job is the name of your batch script.

Detailed information about batch jobs can be found in the Batch Jobs page of the guide.

Queue specifications

Metrics updated 2026-06-16

Name Purpose Nodes CPU cores / node GPUs / node Node RAM Jobs
30 days
Wait Time
30-day trend
Wall Time
30-day trend
EM Extreme Memory jobs requiring very large shared memory. Designed for applications that require terabytes of memory and cannot use distributed-memory approaches. 4 Intel Xeon Platinum 8260M CPUs (96 cores) 4 TB 194
EM wait time: average 2.0 hours, range 0 to 26.7 hours over 30 days
EM wall time: average 9.9 hours, range 0.1 to 18 hours over 30 days

Software

The following software packages are among the most frequently used on Bridges-2 EM, based on job data from XDMoD.

Most Frequently Used

Application Description Research Discipline Jobs
python Python is a high-level, interpreted programming language known for its simplicity and readability. It supports multiple programming paradigms and has a vast ecosystem of libraries and frameworks. Computer & Information Sciences, Software Engineering, Systems & Development 12,550
r R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows, and MacOS. Computer Science 58
lammps LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) is a classical molecular dynamics code designed for simulating large-scale atomistic systems. It is highly versatile and can be used to model a wide range of materials and complex molecular structures. Chemical Sciences 37
q-espresso 15
samtools Samtools is a suite of programs for interacting with high-throughput sequencing data generated in sequence alignment/map (SAM) format, such as those produced by the Short Read Mapping (SHRiMP) or Burrows-Wheeler Aligner (BWA) aligners. It allows various operations on SAM/BAM files, including indexing, sorting, merging, and manipulating sequence alignments. Biological Sciences 10
gromacs GROMACS (GROningen MAssive Parallel MD for Molecular Dynamics) is a versatile package for molecular dynamics simulations with a strong emphasis on high-performance computing capabilities. Biological Sciences 4
cp2k CP2K is an open-source quantum chemistry and solid state physics software package designed to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It can be used to study a wide range of properties, including electronic structures, molecular dynamics, and vibrational spectra. Physical Sciences 2
orca Orca is a flexible, efficient, and powerful quantum chemistry software written by Frank Neese and co-workers. It provides accurate and reliable computational simulations of molecular structures and properties based on quantum mechanical methods. Chemical Sciences 1

Datasets

Name Description
2019nCoVR: 2019 Novel Coronavirus Resource

COVID-19 genomic surveillance data and metadata (hosted by NGDC).

Webpage: https://ngdc.cncb.ac.cn/ncov/?lang=en.
Path in Bridges-2: /ocean/datasets/community/alphafold.

AlphaFold

Predicted protein structures for the human proteome and other key proteins.

Webpage: https://alphafold.ebi.ac.uk/.
Path in Bridges-2: at /ocean/datasets/community/alphafold.

CIFAR-10

60,000 labeled images across 10 classes; standard image-classification benchmark.

Webpage: https://www.cs.toronto.edu/~kriz/cifar.html.Path in Bridges-2: /ocean/datasets/community/cifar.

COCO

Large-scale image dataset for object detection, segmentation, and captioning.

Webpage: https://cocodataset.org/.
Path in Bridges-2: /ocean/datasets/community/COCO.

CosmoFlow

~10,000 cosmological dark-matter simulations. Access requires a request via the CosmoFlow request form.

Webpage: https://portal.nersc.gov/project/m3363/.
Path in Bridges-2: /ocean/datasets/community/cosmoflow.

ImageNet

Image dataset organized by WordNet hierarchy.

Webpage: http://image-net.org/.
Path in Bridges-2: /ocean/datasets/community/imagenet.

MNIST

Classic handwritten-digit dataset for image-processing benchmarks.

Path in Bridges-2: /ocean/datasets/community/mnist.

Natural Languge Tool Kit Data

Corpora, grammars, and trained models for NLP.

Webpage: http://www.nltk.org/nltk_data/.
Path in Bridges-2: /ocean/datasets/community/nltk.

OpenWebText

Path in Bridges-2: /ocean/datasets/community/openwebtext.

PREVENT-AD

Longitudinal multimodal data from cognitively healthy older adults at risk for Alzheimer's, from two prevention trials.

Path in Bridges-2: /ocean/datasets/community/prevent_ad.

TCGA Images

Path in Bridges-2: /ocean/datasets/community/tcga_images.

Genomics datasets

These datasets are available to anyone with an allocation on Bridges-2. They are stored under /ocean/datasets/community/genomics.

AUGUSTUS, BLAST, CheckM, Dammit, Homer, Kraken2, Pfam, Prokka Repbase

 


Storage

File System

Directory Path Quota Purge Backup Notes
$HOME /jet/home/PSC-username 25 GB 3 months after allocation expires Daily
$PROJECT /ocean/projects/groupname/PSC-username 3 months after allocation expires None Quota size depends on allocation
$LOCAL Node-local (no global path) Immediately after job ends None Quota varies by node type
$RAMDISK Node memory (no filesystem path) Immediately after job ends None Quota depends on allocated node memory

File Transfer

A variety of transfer methods are available for Bridges-2. All transfers must be initiated from your local machine through the dedicated Data Transfer Node (data.bridges2.psc.edu) rather than the login nodes, to avoid disrupting interactive use. DTNs are specifically built to be high-speed data connectors. Use rsync, scp, or sftp for standard command-line transfers, or Globus for large datasets or transfers with many files, since it can automatically retry and resume after interruptions.

For more information, please visit https://www.psc.edu/resources/bridges-2/user-guide#transferring-files and https://www.psc.edu/resources/bridges-2/user-guide#file-spaces.

Supported Methods Data Transfer Node URL
GLOBUS | RECOMMENDED PSC Bridges-2 /ocean and /jet filesystems https://app.globus.org
RSYNC data.bridges2.psc.edu
SCP data.bridges2.psc.edu
SFTP data.bridges2.psc.edu