Exascale Computing


Chun-Hsi (Vincent) Huang, Computer Science & Engineering, (860) 486-5472; huang@engr.uconn.edu


Fellowships are available for doctoral students.


This research centers on the challenges involved in designing and developing exascale supercomputing. Exascale computing refers to computing capabilities representing a thousandfold increase over the currently existing petascale (1015 operations/sec) processing power. Exascale capability will enable the U.S. to maintain its leadership role during the petascale era and to continue to innovate in multiple industries, including aerospace, energy, healthcare, information technology and manufacturing, etc. The challenge to attain exascale capability is complex and involves technical hurdles such as exploiting massive parallelism at the algorithm level, coping with software run-time errors from a billion processing elements, efficient large-scale inter-processor and processor- memory communications, as well as reducing the power requirements for future hardware.

The GAANN Fellows will have unparalleled access to work closely with internationally-renowned faculty, state-of-the-art instrumentation and analysis laboratories, and a collegial and supportive environment that promotes professional development, networking opportunities and personal growth. They will also serve as mentors to K-12 teachers and K-16 students by participating in joint research and outreach activities.

Core Faculty:

Mohammad (Maifi) Khan
Chun-Hsi (Vincent) Huang
Sanguthevar Rajasekaran