Abstract
We report the results of a scaling effort that increases both the speed and resolution of the SIESTA magnetohydrodynamics equilibrium code. SIESTA is capable of computing three-dimensional plasma equilibria with magnetic islands at high spatial resolutions for toroidally confined plasmas. Starting with a small-scale parallel implementation, we identified scale-dependent bottlenecks of the code and developed scalable alternatives for each performance-significant functionality, cumulatively improving both its runtime speed (on the same number of processors) and its scalability (across larger number of processors) by an order of magnitude. The net outcome is an improvement in speed by over 10-fold, utilizing a few thousand processors, enabling SIESTA to simulate high spatial-resolution scenarios in under an hour for the first time.
Kalyan Perumalla
As a Federal Program Manager in Advanced Scientific Computing Research at the U.S. Dept. of Energy, Office of Science, Kalyan Perumalla manages a $100-million R&D portfolio covering AI, HPC, Quantum, SciDAC, and Basic Computer Science. In his 25-year R&D leadership experience, he previously led advanced R&D as Distinguished Research Staff Member at the Oak Ridge National Laboratory (ORNL) developing scalable software and applications on the world’s largest supercomputers for 17 years, including as a line manager and a founding group leader. He has held senior faculty and adjunct appointments at UTK, GT, and UNL, and was an IAS Fellow at Durham University.