Computing Resources

The Data Science Institute provides the following computing resources to members of the Institute, as defined by the Institute by-laws.

SERVERS

A high-end server is available for administrative, research and teaching purposes. The top level specs are:

  • 2x Intel Xeon E5-2620 CPUs @ 2.10GHz (8 cores/16 threads each)
  • 4x Nvidia GTX 1080 Ti GPUs @ 1582MHz (3584 CUDA cores each)
  • 128GB ECC RAM memory
  • 400GB SSD (RAID 1) system drives
  • 30TB HDD (RAID 5) mass storage - available upon request
  • Ubuntu 18.04-2 Linux operating system

This system is primarily intended for machine learning and similar applications, and as such, has the following software already installed:

  • Google TensorFlow
  • Nvidia CUDA drivers (v430.26), Toolkit (v8.x) and cuDNN (v6.x/7.x)
  • C (v7.4x), Python (v2.x/3.x) and R (v3.x) programming languages

It also has a highly-performant web stack installed for hosting static or dynamic websites, consisting of the following components:

  • Nginx (SSL termination)
  • Varnish (cache)
  • Apache (web server)
  • PHP (application layer)
  • Redis (key store)
  • MySQL (database)

Other software or packages may be installed for specific use cases based on your needs and we will do our best to accommodate them.

ACCESS

Email help@datascience.columbia.edu and you will be provided with a local Unix account based on your UNI.


HABAÑERO HPC

On the Habañero High-Performance Cluster (HPC) maintained by Columbia University, the Institute has dedicated resources including:

  • 2x high memory nodes (512 GB each)
  • 6x GPU nodes (2x Nvidia K80/4x P100 GPUs each)
  • 30TB scratch space

Habañero documentation can be found HERE.

ACCESS

Email hpc-support@columbia.edu with a copy to Michael Holve, mh3698@columbia.edu, for approval.


QUESTIONS AND SUPPORT

Questions and support requests should be emailed to help@datascience.columbia.edu with a brief subject line containing the nature of the request.


550 W. 120th St., Northwest Corner 1401, New York, NY 10027    212-854-5660
©2018 Columbia University