High performance first principles method for complex magnetic properties
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
Large-scale electronic structure calculations of high-Z metals on the BlueGene/L platform
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
A scalable method for ab initio computation of free energies in nanoscale systems
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Liquid water: obtaining the right answer for the right reasons
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
World-highest resolution global atmospheric model and its performance on the Earth Simulator
State of the Practice Reports
Taking a quantum leap in time to solution for simulations of high-Tc superconductors
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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Methods based on the many-body Green's function are generally accepted as the path forward beyond Kohn-Sham based density functional theory, in order to compute from first principles electronic structure of materials with strong correlations and excited-state properties in nano- and materials science. Here we present an efficient method to compute the screened Coulomb interactionW, the crucial and computationally most demanding ingredient in the GW method, within the framework of the all-electron Linearized Augmented Plane Wave method. We use the method to compute from first principles, within the constrained random phase approximation (c-RPA), the frequency-dependent screened Hubbard U-matrix defined for a Wannier basis in which we downfold the many-body Hamiltonian for La2CuO4, the canonical parent compound of several cuprate high-temperature superconductors. These results were computed at scale on the Cray XT5 at ORNL, sustaining 1.30 petaflop. We discuss the details of the algorithm and its implementation that allowed us to reach high efficiency and short time to solution on today's petaflop supercomputers.