There is extreme urgency in identifying the possible paths forward to extending Moore’s law in silicon (Si) complementary metal-oxide-semiconductor (CMOS) based computing technologies. A fundamental materials problem that must be addressed is leakage current through the HfO2 gate dielectric. There is evidence that impurities like nitrogen and fluorine are able to reduce leakage currents, however current computational studies are limited to density functional theory (DFT), which do not provide the necessary fidelity. For this project, researchers propose to use QMCPACK to study the energetics of point defects near a HfO2 interface using quantum Monte Carlo (QMC) methods. Because of the number of electrons required in these simulations, they necessitate and will be enabled by the large aggregate memory and peak performance offered by Aurora.
The research team’s software development efforts will focus on performance characterization of the B-spline evaluation on Aurora’s tiered memory system. They will also enhance the usability of Quantum Espresso, the DFT code that generates the initial trial wave functions for QMCPACK. Efforts to achieve performance portability of QMCPACK are outside the scope of the Aurora Early Science Program (ESP) and will be funded through a recently awarded Exascale Computing Project (ECP) field work proposal. An Intel Parallel Computing Center (IPCC) that was jointly awarded to the ALCF and Sandia National Laboratories will support efforts to develop nested threading, enabling even more on-node concurrency, as well as increasing the fraction SIMD-izable code in QMCPACK.
The team believes this Aurora ESP project, along with the ECP and IPCC efforts, will provide an excellent test bed for the theoretical and algorithmic developments that are outcomes of a recently awarded DOE Center for Material Science focused on functional materials.
The proposed research aims to advance knowledge of the HfO2/Si interface necessary to extend current Si-CMOS technology; it also aims to advance fundamental science necessary to advance computing beyond Moore’s Law and current Si-CMOS by focusing on central problems that gate potential applications of topological insulators.