Cost-efficient simulations of large-scale electronic structures in the standalone manycore architecture

Abstract

The tight-binding (TB) model is complementary to the ab-initio methods that can be represented by the well-known Density Functional Theory since the empirical nature of a TB model enables the scope of electronic structure simulations to include realistically sized nanoscale structures that are normally made up of several million atoms. As the major computational hotspot of TB simulations comes from diagonalization of a sparse system matrix whose size is proportional to the number of atoms belonging to a simulation domain, efficient utilization of high performance computers is strongly encouraged. Here we study the feasibility of cost-efficient TB simulations for large-scale electronic structures on the Intel Xeon Phi Knights Landing (KNL) platform, which is equipped with the processor of many-integrated cores and the onboard high-speed memory. Using our in-house code whose scientific fidelity has been validated through various modeling researches, we present detailed discussion on how KNL systems can be exploited to accelerate simulations, and conduct rigorous benchmark tests in competing platforms to justify benefits of the standalone manycore architecture in terms of the time and the energy consumption that must be paid. The capability to handle extremely huge atomic structures in KNL systems is also demonstrated by securing a strong scalability up to 2,500 nodes in the NURION supercomputer for a model problem that has 400 million atoms.