Hiding latency becomes easier as the size of the problem increases because the amount of time spent computing increases faster than does the time spent exchanging data between processor groups. In large problems, such as solar convection, the time spent computing overwhelmingly exceeds the time spent exchanging data. The LCSE team plans to apply this same strategy for latency tolerance to enable very widely separated computing resources connected by the new NSF vBNS network to cooperate on the solution of single, tightly coupled, grand challenge applications like the stellar convection problem. In the outer layers of stars like the sun, heat is transported by convection. Deep within a star, regions of gas heated by conduction become buoyant and rise toward the surface where the heat can be radiated directly into space.
Gas cooled near the surface becomes denser and sinks.
These rising and sinking flows of gas create complicated patterns of turbulence that affect the evolution of the star. For instance, the turbulent convection flow can redistribute angular momentum as well as heat, which causes gases to rotate more slowly near a star's poles than near its equator. Previous models of stellar convection were limited to small areas on the surface of the star, areas too small to help scientists understand how such differential rotation becomes established in a star. This simulation was the first attempt at a high-resolution model of an entire star to better visualize its complex dynamics. Major funding to support its mission is received from NSF, the Defense Advanced Research Projects Agency, the DOD Modernization Program, NASA, other governmental agencies, NCSA's corporate partners, the state of Illinois, and the University of Illinois.