The Tufts High Performance Compute (HPC) cluster delivers 35,845,920 cpu hours and 59,427,840 gpu hours of free compute time per year to the user community.

Teraflops: 60+ (60+ trillion floating point operations per second) cpu: 4000 cores gpu: 6784 cores Interconnect: 40GB low latency ethernet

For additional information, please contact Research Technology Services at

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TTS Research Computing Resources

     Tufts Technology Services(TTS) Research computing options

     High-performance computing research cluster

     Bioinformatics server

     Research Storage

     Visualization Center

     GIS Center

     See overview for additional information about TTS Technology Services.

1. Tufts High-performance computing research cluster

What is a Cluster?

Cluster computing is the result of connecting many local computers (nodes) together via a high speed connection to provide a single shared resource. Its distributed processing system allows complex computations to run in parallel as the tasks are shared among the individual processors and memory. Applications that are capable of utilizing cluster systems break down the large computational tasks into smaller components that can run in serial or parallel across the cluster systems, enabling a dramatic improvement in the time required to process large problems and complex tasks.

Typical Cluster Usage at Tufts

Faculty, Research Staff and students use this resource in support of a variety of research projects. See how.

Tufts Linux Research Cluster

Tufts Technology Services TTS provides a wide array of services in support of Tufts research community.  High Performance Computing(HPC) hardware from Cisco and IBM is used to create  the cluster.   The hardware complement includes Cisco  blades,  IBM  M3 and M4 iDataplexes, nVidia GPUs and a 10Gb/s interconnect Cisco network.

m4 nodes:      Intel(R) Xeon(R) CPU E5-2670 0 @ 2.60GHz
Cicso nodes:  Intel(R) Xeon(R) CPU E5-2660 v2 @ 2.20GHz
m3 nodes:      Intel(R) Xeon(R) CPU    X5675  @ 3.07GHz


By late Dec. 2014 there is  approximately 163 compute nodes. Total slurm managed cpu/core count is ~3600 and a peak performance of roughly 60+ Teraflops. In this HPC environment, TTS also provides researchers with access to commercial engineering software, popular open-source research software applications and tools for bioinformatics and statistics.  Secure networked storage for research data (400+ TB CIFS and NFS storage on NetApp appliances) is available. 

Each cluster node has 12, 16 or 20 cores using  three different  Intel CPUs.   Compute node memory ranges from 24 to 384 gigabytes of memory.

GPU computing is supported by 12 nVidia GPU models:

K20,  M2070, M2050


The Linux operating system on each node is configured identically across every machine. In addition there is a login node and a file transfer node supporting the compute nodes. Client/user workstations access the cluster via the Tufts Network using ssh based connection client software. Remote ssh access for researchers is also supported.  The user login node has an additional network interface  that connects to the compute nodes using private IP addressing via 10Gig network hardware. This scheme allows the compute nodes to be a "virtual" resource managed by slurm job queueing software. This approach also allows the cluster to scale to a large number of nodes thus providing the structure for future growth. The login node of the cluster is reserved for the use of compilers, running shell tools, and launching and submitting programs to compute nodes. The login node is not intended for running  research programs, or for general computing purposes, and all jobs are to be submitted to compute nodes using slurm. 

A separate  file transfer node,,  is also provided to accommodate large data transfers.

Grant Applications related information

Content to support applications can be found here.

Cluster User Accounts

Click Account Information for additional information about cluster accounts.

Orientation for new cluster users

This content is for someone that has never used linux or time share mainframes or super computing centers.


Research Cluster Restrictions

Conditions and use of the research cluster include and are not limited to the following expectations. Additional related details may be found throughout this page.


no user root access

supported OS is RedHat 6 Enterprise version

no user ability to reboot node(s)

all cluster login access is via the login headnode

no user machine room access to cluster hardware

no alternative linux kernels other than the current REDHAT version

no access to 10Gig Ethernet network hardware or software

no user cron or at access

no user servers/demons such as: HTTP(apache), FTP. etc.

Cluster quality of service is managed through slurm

all user jobs destined for compute nodes are submitted via slurm  commands

all compute nodes follow a naming convention

only Tufts Technology Services NFS approved research storage is supported

idle nodes are scheduled by slurm

no user contributed direct connect storage such as usb memory, or external disks

only limited outgoing Internet access from the headnode will be allowed; exceptions must be reviewed

allow approximate 2-week turn around for software requests

whenever possible, commercial software limit to the two most recent versions

Only user home directories and optional research NFS mounted storage is backed up

temporary public storage file systems have no quota and are subject to automated file deletions

Cluster does not export file systems to user desktops

Cluster does not support Virtual Machine instances

Software request policy

Please send your request via email to and address the following questions:

  • What is the the name of the software?
  • Where can additional information about the software be found?
  • Who are the intended users of the software?
  • When is it needed by?
  • Will it be used in support of a grant and if so what grant?
  • What if any special requirements are needed?

Note: A software request normally may take up to 2 weeks. However depending on the installation complexity and number of packages requested it may take longer. When it appears that an assessment of the tasks suggest longer than 2 weeks we will contact you with an estimate so that prioritization can be made.

Recent Cluster News

Click News

Cluster Storage Options

Click here for details.

Network Concurrent Software Licenses

Click here

Support venue

If you have any questions about cluster related usage, applications, or assistance with software, please contact

MODULES: Cluster software environment

Click here

Installed Cluster Software

Click here

Compilers, Editors, etc...

Click here

Frequently Asked Questions - FAQs:

Cluster Connections/Logins

Click here

Parallel programming related information

Click here

User Account related FAQs:

Click here

X based graphics FAQs

Click here

Application specific Information FAQs

Click here

Linux and cluster information FAQs

Click here

Compilation FAQs

Click here

Miscellaneous FAQs

Click here

How do Tufts students and faculty make use of the cluster?

See How

2. Bioinformatics services

A separate server is used to support these services in some cases. However some software may require installation on the linux research cluster. Check the Installed Software for Bioinformatic software available on the cluster. To make a special request for software installation, please follow the instructions as noted elsewhere on this page.

Emboss services can be found here


3. Tufts GIS Center

Tufts GIS Center and resources can be found here.

Tufts GeoPortal
Many organizations and institutions are developing large spatial data repositories. Discovering and accessing these data sets pose many challenges. As a result, Tufts and Harvard are collaboratively developing an open source, federated web application to discover, preview, and retrieve geospatial data as part of global and national spatial data infrastructure. The Open Geoportal combines an intuitive, map-based search interface along with traditional text-based metadata search tools for rapid data discovery. Tufts instance of The Open Geoportal can be found here.

Tufts Research Cluster indirectly supports GIS spatial statistical computation with the availability of modern spatial statistics programs as found in R. This is a useful resource when faced with either complex estimation tasks, long runtimes or access to more memory than is often available on desktop workstations. R programs such as the following are available:

fields, ramps, spatial, geoR, geoRglm, RandomFields, sp, spatialCovariance, spatialkernel, spatstat, spBayes, splancs,

For additional information please contact

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