Refreshing the mesh,
and other career tales
Posted March 31, 2010
Several scientists supported by the Department of Energy’s Office of Advanced Scientific Computing Research (ASCR) were among those who recently received awards in DOE’s new Early Career Research Program. ASCR Discovery talked with them to learn what they will investigate over the course of their five-year awards.
Picture a six-faced cube with eight corner points, blow it up and slap it onto a globe. The six faces are rectangular patches that can be subdivided infinitely. This technique allows Christiane Jablonowski, University of Michigan assistant professor of atmospheric and space sciences and scientific computing, to place a “refinement region” of tight grid-spacing atop a uniform-resolution, cubed-sphere mesh.
“The refined patch lets us, for example, capture and track tropical hurricanes with high accuracy,” she says. The technique is called adaptive mesh refinement (AMR).
AMR is the foundation for a new “dynamical core,” which makes up the heart of every climate and weather model and describes the fluid flow behind wind, temperature, pressure and density, Jablonowski says.
Jablonowski, who heads Michigan’s atmospheric dynamic modeling group, plans to use her award to develop more precise and reliable climate models using AMR techniques. It’s the only model that can be directed to zoom in on features of interest (in this case an isolated idealized storm system) at the minuscule resolution (for atmospheric science, anyway) of 1 kilometer while maintaining the flexibility to portray other features at a resolution of 100 kilometers.
Many atmospheric science models use latitude-longitude grids for their mesh, but converging meridians at the poles present mathematical problems.
“This will be a major test case of the efficacy of our modeling approach,” she says.
The model’s dynamical core will use the power of hundreds of thousands of processors working in parallel. Besides two graduate students, Jablonowski’s collaborators include researchers at DOE’s Lawrence Berkeley National Laboratory and the National Center for Atmospheric Research.
Patrick Chiang, assistant professor of computer science at Oregon State University, is working on an energy-efficient interconnect for microchips in future massively parallel computing systems.
“It turns out that the energy consumed to make a computation is much less than the energy used to move that computed result somewhere else within the system,” Chiang says. “This is the case at every level — within a single integrated microprocessor, connecting multiple chips inside a single server, and connecting multiple servers in a data center. The goal of my research is to tackle innovative ways in silicon to reduce this energy at all of these levels.”
At the on-chip interconnect, where data must be moved to and from hundreds of computational units in a multicore processor, he and his team will take advantage of bandwidth advances that enable better system operations and lower power consumption. Off the chip, for short distances on a motherboard, he and his group hope to reduce the “clock distribution energy” that comes with data transfer to or from a computer and to or from a peripheral component, consuming significant power.
Finally, between separate racks that may be several meters apart in a data center, his group is working on energy-efficient, gigahertz analog-digital converters. Encoding data into multiple signals at a given time can significantly improve the off-chip bandwidth, he says.