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

For additional information, please contact Lionel Zupan, Director of Research and Geospatial Technology Services (RGTS), at x74933 or via email

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 Research and Geospatial 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.   By late Dec. 2014 there will be approximately 170+ compute nodes, 2600 cores and a peak performance of roughly 60+ Teraflops. In this HPC environment, TTS also provides researchers with access to commercial and open-source research software applications, tools for bioinformatics and statistics, and networked and secure storage for research data (400+ TB CIFS and NFS storage on NetApp appliances).

Finally, TTS also maintains a Center for Scientific Visualization. Tufts HPC is connected via high speed links to Internet2 sites.

Each cluster node has 12, 16 or 20 cores using  three  different  Intel CPUs.   Compute node memory ranges from 24 to 256 and larger gigabytes of memory.

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 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.

New Cluster Specific Information

Click New Cluster.

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 timeshare mainframes or super computing centers.

Legacy Cluster documentation

    See pdf files.

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 LSF 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 Center for Scientific Visualization (or VisWall)

A description may be found here. The user guide is available here. Also, visit the Tufts Visualization Awards program.

See the attached EduCause document on Visualization for general information and direction this technology provides. You may find it under this wiki page "Page Operations" section above.

The unique facilities at the Tufts Center for Scientific Visualization allow researchers to display 2D or 3D high-resolution images and video at 4K resolution (4096x2160) on a rear-projected, 15 by 8 foot screen. Users can also bring their personal laptop to the Viswall and display their images or video at a quarter of the maximum resolution, which is standard HD (2048x1080).

Applications are run from one of three operating systems: Red Hat Linux, Windows, or Mac OS X. The HP workstation, which runs Red Hat Linux 5 or Windows XP, has 8 Intel processor cores and 16GB of RAM. The Apple MacPro, which runs Mac OS X 10.6, has 8 Intel processor cores and 16GB of RAM. Visualization processing can be handled on one of these two machines, or remotely at Tufts' cluster computing facility which is connected to the Center for Scientific Visualization via 10 Gigabit Ethernet.

The Viswall has recently been upgraded to improve usability, which is now handled by a simple touch-screen interface.

The research cluster is available to VisWall users for additional computational resources. Current connectivity follows standard practices using ssh and x11 forwarding. Viswall users with a cluster account may forward cluster based application graphic output for display on the VisWall. As of mid-May 2009, a new and dedicated 10Gig fiber network connects the cluster nodes with the Viswall. This provides for a novel and very high speed connection for moving massive amounts of data.

If you intend to use this facility, a short mandatory training class is required. Contact via email to make arrangements.

4. 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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