TTS Research Computing Resources
For additional information, please contact Lionel Zupan, Director of Research and Geospatial Technology Services (RGTS), at x74933 or via email Lionel.Zupan@Tufts.edu.
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 163 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).
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.
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, xfer.cluster.tufts.edu, is also provided to accommodate large data transfers.
New Cluster Specific Information for Fall 2014 semester
Click New Cluster.
Legacy Cluster documentation
Note: The cluster wiki pages are in the process of updating to reflect changes to the new cluster. The new cluster will be available during the fall 2014 semester.
To access the former pages: See pdf files.
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.
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.
Expectations |
|---|
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 cluster-support@tufts.edu 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
Support venue
If you have any questions about cluster related usage, applications, or assistance with software, please contact cluster-support@tufts.edu.
MODULES: Cluster software environment
Installed Cluster Software
Compilers, Editors, etc...
Frequently Asked Questions - FAQs:
Cluster Connections/Logins
Parallel programming related information
User Account related FAQs:
X based graphics FAQs
Application specific Information FAQs
Linux and cluster information FAQs
Compilation FAQs
Miscellaneous FAQs
How do Tufts students and faculty make use of the cluster?
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)
Note: this facility is expected to close end of spring 2015 semester. Plans for a future home and service is under consideration.
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 cluster-support@tufts.edu.