Child pages
  • OSG

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

Skip to end of metadata
Go to start of metadata



If you could access hundreds, thousands, or even more computers for your
scholarly work, what could you do?  How could it transform your work?  What
discoveries might you make?

We are seeking applicants for the Open Science Grid (OSG) User School 2016,
which takes place 25-29 July at the beautiful University of Wisconsin in
Madison.  Participants will learn to use high throughput computing (HTC) to
harness vast amounts of computing power for research, applicable to nearly
any field of study (e.g., physics, chemistry, engineering, life sciences,
earth sciences, agricultural and animal sciences, economics, social
sciences, medicine, and more).

Using lectures, discussions, roleplays, and lots of hands-on work with OSG
experts in HTC, participants will learn how HTC systems work, how to run
and manage many jobs and huge datasets to implement a full scientific
computing workflow, and where to turn for help and more info.

Worried about costs?  Successful applicants will receive financial support
to attend the OSG School, covering all basic travel, hotel, and food costs.
This is a great deal!

Ideal candidates are graduate students whose research involves or could
involve large-scale computing - work that cannot be done on one laptop or a
handful of computers.  And every year, we accept some post-doctoral
students, faculty, staff, and advanced undergraduates, so make a good case
for yourself!


     Application Period (OPEN NOW): 14 March - 15 April 2016
     OSG User School: 


Please forward this announcement to help us reach potential participants.
And consider posting our flyer where appropriate:


  • No labels