ABOUT THIS AWARD

The Gordon Bell Prize is awarded each year to recognize outstanding achievement in high-performance computing. The purpose of the award is to track the progress over time of parallel computing, with particular emphasis on rewarding innovation in applying high-performance computing to applications in science, engineering, and large-scale data analytics. Prizes may be awarded for peak performance or special achievements in scalability and time-to-solution on important science and engineering problems. Financial support of the $10,000 award is provided by Gordon Bell, a pioneer in high-performance and parallel computing.

LATEST NEWS

The 2015 Gordon Bell Prize

A 10-member team won the 2015 ACM Gordon Bell Prize for their submission entitled An Extreme-Scale Implicit Solver for Complex PDEs: Highly Heterogeneous Flow in Earth’s Mantle. The winning team was announced during SC15 in Austin, Texas.

The 10-member team led by Johann Rudi of the University of Texas at Austin receuved the 2015 ACM Gordon Bell Prize for their entry entitled An Extreme-Scale Implicit Solver for Complex PDEs: Highly Heterogeneous Flow in Earth’s Mantle. The winning team includes representatives from the University of Texas at Austin, IBM Corporation, California Institute of Technology and the Courant Institute of Mathematical Sciences at New York University.
 
The award was bestowed during SC15 in Austin, Texas.
 
The group’s submission demonstrates that, contrary to conventional wisdom, implicit solvers can be designed that enable efficient global convection modeling of the earth’s interior, allowing researchers to gain new insights into the geological evolution of the planet.
 
Team members include Costas Bekas (IBM), Alessandro Curioni (IBM), Omar Ghattas (University of Texas at Austin), Michael Gurnis (California Institute of Technology), Yves Ineichen (IBM), Tobin Isaac (University of Texas at Austin), Cristiano Malossi (IBM), Johann Rudi (University of Texas at Austin), Georg Stadler (Courant Institute of Mathematical Sciences), and Peter W.J. Staar (IBM).