Parallel Systems

Designing and optimizing both hardware and software to more efficiently operate on a large scale is the focus of our research into parallel systems. Our work on synchronizing mobile and location-based computing to more efficiently use cloud computing and data pushes the limits of systems. We also focus on high-performance computing, big data and how to best utilize multiple processors to accelerate computations while minimizing bugs and maximizing reliability.

Computer Science faculty in this area include:
Randall Bramley, Volker Brendel, Arun Chauhan, Funda Ergun, Geoffrey Charles Fox, Minaxi Gupta, Christopher Haynes, Raquel Hill, Steven Johnson, Apu Kapadia, Andrew Lumsdaine, Ryan Newton, Feng Qian, Gregory J. E. Rawlins, Jeremy Siek, Martin Swany, Sam Tobin-Hochstadt, Grigory Yaroslavtsev