A team of computational scientists and engineers from Lawrence Berkeley National Laboratory (Berkeley Lab), Oak Ridge National Laboratory (ORNL) and NVIDIA has been awarded the ACM Gordon Bell Prize for applying an exascale-class deep learning application to extreme climate data and breaking the exaop (1 billion billion calculations) computing barrier for the first time with a deep learning application.

Ankur Mahesh, a UC Berkeley undergraduate student working under the mentorship of Berkeley Lab climate research scientist Travis O’Brien, was part of the team led by Prabhat at NERSC. Ankur’s contribution was funded as part of the CASCADE SFAwhich is supported by the Regional and Global Model Analysis component of the DOE Earth and Environmental System Modeling program. Read complete article here.