Research Computing

 

Large-scale computational resources

Research Computing is dedicated to enabling research, accelerating discovery, and spurring innovation at Arizona State University (ASU) through the application of advanced computational resources to grand challenges in science, engineering, and health. Offering a team of systems professionals, architects, scientific software engineers, and research facilitators, ASU Research Computing provides technical expertise in all areas of computing, including parallel computing, big data analytics, scientific visualization, high-speed networking, and cybersecurity. 

Research Computing provides ASU faculty and students access to accelerated high performance computing resources comprising:

  • 14,000 CPU cores,
  • 300 GPU accelerators,
  • Dedicated virtual machines (VM) for specific research environments, and 
  • A FISMA Moderate secure computing environment with support for sensitive or federally regulated data.

Additionally, big data storage, hands-on training, scientific software optimization, and proposal support round out Research Computing’s offerings.

 

Popular software applications

A variety of software packages are available on Research Computing's resources. Below is a representation of some of our most popular software applications.

  • Matlab
  • Python—and Juypter interface—including many modules, including tensorflow, numpy, scipy and pandas
  • R—and RStudio interface—including many packages such as tidyverse and bioinformatics tools and other statistics packages such as sas and stata
  • Domain-specific packages, such as LAMMPS, WRF, GATK, Rosetta and Gromacs

 

Browser-Based Interactive Computing Environment

Accessing Research Computing resources has never been easier than with our browser-based interactive computing environment powered by Open OnDemand. By logging in through Open OnDemand single sign-on, using your ASURITE login and password, you can manage file systems, create and monitor jobs, view and manage interactive sessions, and so much more!

 

Additional information

 

Citing Research Computing

Please reference ASU Research Computing in any research report, journal or publication that requires citation of any author's work. The minimal content of a citation should include:

Research Computing, Arizona State University

Our suggested acknowledgement is:

The authors acknowledge Research Computing at Arizona State University for providing {HPC, storage, etc.} resources that have contributed to the research results reported within this paper. URL: http://www.researchcomputing.asu.edu

Select one or more of the items within the braces, {}.

 

Investigator Resources

Research Computing provides a variety of resources to the ASU research community with the goal of enabling research, accelerating scientific discovery, and spurring innovation through the use of advanced computational resources. 

The following research and proposal resources are available to you:

  • Customized proposal support or a personal consultation
  • Letter of Support
  • Hardware quotes for proposal budgets
  • Data Management Plan
  • Facilities Statement
  • Acknowledgment Guidelines

These resources and more information can be found by visiting our Investigator Resources Page or email us if you would like to schedule a consultation to discuss your research proposal. 

 

Leadership

  • Douglas Jennewein, Senior Director, Research Computing, Research Technology Office
  • Ian Shaeffer, Operations Manager, Research Computing, Research Technology Office

 

Location and Office Hours

Research Computing Office Hours


Contacts

Name Role Phone Email Location
Ian Shaeffer
Operations Manager
 

 
IanS@asu.edu
 

 
Douglas Jennewein
Senior Director
 

 
douglas.jennewein@asu.edu
 

 
Marisa Brazil
Associate Director
 

 
marisa.brazil@asu.edu
 

 
Richard Gould
Director
 

 
richard.gould@asu.edu
 

 

Services List


Search available services: View: by category alphabetically
Co-Located Equipment for Research Purposes (6)
Consulting Sevices (2)
Storage (1)
Virtual Machines - Internal Hosting w/o Dedicated Hardware (3)
Virtual Machines with Dedicated Hardware (3)