An LLNL-led effort that performed an unprecedented global climate model simulation on the world’s first exascale supercomputer has won the first-ever Association for Computing Machinery (ACM) Gordon Bell Prize for Climate Modelling, ACM officials announced.
In recent years, the Lab has boosted its recruiting profile even further by offering the prestigious Sidney Fernbach Postdoctoral Fellowship in the Computing Sciences. The fellowship fosters creative partnerships between new and experienced scientists. In short, it ensures an annual cycle that refreshes advanced research in computer sciences at the Lab.
A team from LLNL and seven other DOE labs is a finalist for the new ACM Gordon Bell Prize for Climate Modeling for running an unprecedented high-resolution global atmosphere model on the world’s first exascale supercomputer.
As part of the Exascale Computing Project’s ExaSGD project, a team including LLNL researchers ran HiOp, an open source optimization solver, on 9,000 nodes of Oak Ridge National Laboratory’s Frontier exascale supercomputer.
The event brought together 35 University of California students—ranging from undergraduates to graduate-level students from a diversity of majors—to work in groups to solve four key tasks, using actual electrocardiogram data to predict heart health.
Using explainable artificial intelligence techniques can help increase the reach of machine learning applications in materials science, making the process of designing new materials much more efficient.
For the physicists, computer scientists, and code developers who have worked on fusion for decades, computer simulations have been inexorably tied to the National Ignition Facility’s quest for ignition.
The new model addresses a problem in simulating RAS behavior, where conventional methods come up short of reaching the time- and length-scales needed to observe biological processes of RAS-related cancers.