Gygi Research Group at UC DavisWelcome to the Electronic Structure Laboratory at the University of California Davis. Our research focuses on the development of numerical algorithms and high-performance software for electronic structure computations and First-Principles Molecular Dynamics (FPMD) simulations.
News: DOE creates the Midwest Center for Computational Materials (MICCoM) at Argonne National LaboratoryMICCoM will develop methods and optimized codes to compute structural, electronic properties, and transport coefficients from atomistic and first principles simulations, integrating ab initio molecular dynamics (MD) with classical and continuum codes. As a member of MICCoM, the UC Davis Electronic Structure Laboratory will develop high-performance quantum simulation algorithms and implementations of first-principles molecular dynamics.
Graduate course/Winter 2018The course ECS289K Introduction to Quantum Simulations was taught in the Winter quarter of 2018.
News[2018-07-28] Qbox online documentation update
[2018-07-15] Qbox 1.64.0 is available, including range-separated hybrid DFTs.
See the Qbox home page for details and documentation. The SG15 table of ONCV pseudopotentials is available at www.quantum-simulation.org, and a full description is given in:
M. Schlipf and F. Gygi, Comput. Phys. Comm. 196, 36-44 (2015). http://dx.doi.org/10.1016/j.cpc.2015.05.011.
High-Performance First-Principles Molecular DynamicsIn order to enable accurate numerical simulations of atomic-scale properties of matter for applications in chemistry, physics and materials science, we are developing scalable algorithms for First-Principles Molecular Dynamics (FPMD). FPMD combines a quantum-mechanical description of electronic structure with a classical description of statistical properties. Our goal is to efficiently use the power of the largest supercomputers available today to extend the range of applications of FPMD. We develop advanced simulation features such as on-the-fly computation of spectroscopic data and coupling of FPMD simulations with efficient statistical sampling algorithms. Code development is carried out using C++/MPI/OpenMP and targets platforms such as Cray XE6, IBM BlueGene/Q, as well as computers based on the Intel Multi-Integrated Core (MIC) architecture (ANL Aurora). This project is supported by the US Department of Energy Office of Basic Energy Sciences through grant DE-SC0008938 and is pursued in collaboration with Prof. G. Galli (UChicago), Dr. E. Schwegler (Quantum Simulations Group, Lawrence Livermore National Laboratory), and other international collaborators.
Algorithm research projectsWe are developing specialized parallel algorithms to accelerate the most time-consuming steps of electronic structure computations. We explore the problem of data compression for efficient storage of electronic wave function when solving the electronic structure problem, and more generally the problem of generating optimally localized electronic wave functions. This problem is related to algorithms for simultaneous approximate diagonalization of symmetric/hermitian matrices, used in signal processing applications.
Qbox projectWe develop and support Qbox, a C++/MPI implementation of FPMD for massively parallel computers. Qbox is available in source form under a GPL license. See the Qbox home page.
Qbox latest features includes an implementation of Optimized Norm-Conserving Vanderbilt (ONCV) pseudopotentials and the option to include an applied electric field.
Qbox implements the plane-wave, pseudopotential electronic structure method and was designed for scalability on thousands of processors. It has been ported to large parallel platforms, including BlueGene/P, BlueGene/Q, Cray XT-5, Cray XE-6, and a variety of Linux/Intel clusters. It is currently used in projects involving simulations of liquids, semiconductor nanostructures, and materials science. Qbox achieved a performance of 207 TFlops on the BlueGene/L computer. The paper Large-Scale Electronic Structure Calculations of High-Z Metals on the BlueGene/L Platform was awarded the 2006 ACM/IEEE Gordon Bell Prize for Peak Performance. The design of Qbox is described in the following architecture paper.