2013/03/13 by Nicola Varini, Davide Ceresoli, Layla Martin-Samos +3 · 48 citations
Chemistry · Materials Science · Physics and Astronomy · #Advanced NMR Techniques and Applications #Atomic and Subatomic Physics Research #Computational science #Computer science #Density functional theory #Electronic structure #Parallel computing #Petascale computing #Physics #Quantum mechanics #Scalability #Solid-state spectroscopy and crystallography #Statistical physics #Supercomputer #cond-mat.mtrl-sci
paper · pdf · doi:10.1016/j.cpc.2013.03.003
published in Computer Physics Communications 184(8), 1827-1833 (Elsevier BV)
openalex publication_date 2013/03/13 · arxiv created 2013/05/31 · arxiv updated 2013/06/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
One of the most promising techniques used for studying the electronic properties of materials is based on Density Functional Theory (DFT) approach and its extensions. DFT has been widely applied in traditional solid state physics problems where periodicity and symmetry play a crucial role in reducing the computational workload. With growing compute power capability and the development of improved DFT methods, the range of potential applications is now including other scientific areas such as Chemistry and Biology. However, cross disciplinary combinations of traditional Solid-State Physics, Chemistry and Biology drastically improve the system complexity while reducing the degree of periodicity and symmetry. Large simulation cells containing of hundreds or even thousands of atoms are needed to model these kind of physical systems. The treatment of those systems still remains a computational challenge even with modern supercomputers. In this paper we describe our work to improve the scalability of Quantum ESPRESSO \citeQuantum-Espresso for treating very large cells and huge numbers of electrons. To this end we have introduced an extra level of parallelism, over \emphelectronic bands, in three kernels for solving computationally expensive problems: the Sternheimer equation solver (Nuclear Magnetic Resonance, package QE-GIPAW), the Fock operator builder (electronic ground-state, package PWscf) and most of the Car-Parrinello routines (Car-Parrinello dynamics, package CP). Final benchmarks show our success in computing the Nuclear Magnetic Response (NMR) chemical shift of a large biological assembly, the electronic structure of defected amorphous silica with hybrid exchange-correlation functionals and the equilibrium atomic structure of height Porphyrins anchored to a Carbon Nanotube, on many thousands of CPU cores.