The ACI-REF Program: Empowering Prospective Computational Researchers

Thursday, 18 December 2014
Martin Cuma1, Wim Cardoen1, Galen Collier2, Robert M Freeman Jr.3, Aaron Kitzmiller3, Lauren Michael4, Ken-ichi Nomura5, Anita Orendt1 and Lori Tanner2, (1)University of Utah, Salt Lake City, UT, United States, (2)Clemson University, Clemson, SC, United States, (3)Harvard University, Cambridge, MA, United States, (4)University of Wisconsin Madison, Madison, WI, United States, (5)University of Southern California, Los Angeles, CA, United States
The ACI-REF program, Advanced Cyberinfrastructure - Research and Education Facilitation, represents a consortium of academic institutions seeking to further advance the capabilities of their respective campus research communities through an extension of the personal connections and educational activities that underlie the unique and often specialized cyberinfrastructure at each institution. This consortium currently includes Clemson University, Harvard University, University of Hawai’i, University of Southern California, University of Utah, and University of Wisconsin. Working together in a coordinated effort, the consortium is dedicated to the adoption of models and strategies which leverage the expertise and experience of its members with a goal of maximizing the impact of each institution’s investment in research computing.

The ACI-REFs (facilitators) are tasked with making connections and building bridges between the local campus researchers and the many different providers of campus, commercial, and national computing resources. Through these bridges, ACI-REFs assist researchers from all disciplines in understanding their computing and data needs and in mapping these needs to existing capabilities or providing assistance with development of these capabilities.

From the Earth sciences perspective, we will give examples of how this assistance improved methods and workflows in geophysics, geography and atmospheric sciences. We anticipate that this effort will expand the number of researchers who become self-sufficient users of advanced computing resources, allowing them to focus on making research discoveries in a more timely and efficient manner.