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The Grid

The Research Grid at the Columbia Business School is 25+ node, 300+ CPU Linux grid and cluster environment dedicated to supporting academic research and computing. The Business School's Research Grid provides access to powerful computational tools including; Matlab, Sas, Stata, R and Python on a platform vastly more powerful than can be found on any desktop. Users may run interactive or batch jobs with access to large data sets, fast disk space, RAM multiple CPU cores, and GPU capability. Users may access the Grid via a secure-shell or nxclient for a desktop-like environment. Grid utilization may be viewed via ganglia and users can receive a confirmation email at job completion.

Additional information regarding using the Research Grid can be found on our wiki: http://wiki.gsb.columbia.edu/research

Hardware:

  • 30 total nodes (392 cores)
  • 1 Tesla M2070 GPU (488 cores)
  • Each node has either 8, 12 or 16 Intel Xeon Cores
  • Each node has either 32, 96, or 192 GB RAM
  • EMC Isilon Shared Storage with 10GB connectivity
  • Physically separate storage network • Red Hat Linux 6.4 x86_64
  • Redundant power and cooling

Software:

  • OS: Red Hat Enterprise Linux
  • Job Control: Sun Grid Engine v6.2 u5
  • C/C++/Java/Fortran Compilers
  • CPLEX
  • GAUSS
  • Julia Programming Language
  • Mathematica
  • MATLAB
  • Python
  • R/Revolution R
  • Rstudio IDE
  • SAS
  • STATA
  • Stat/Transfer

Databases

The University, the School, the Libraries, and Centers have collected and purchased a wealth of data that can help faculty to address many research questions across disciplines. Issues pertinent to School databases are dealt with by the School's Databases Committee.

Faculty members and doctoral students who would like to request access to a database not currently available at Columbia Business School should follow the procedure outlined in the Policy for Requesting New School-Funded Databases.

 

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