Block Locally Optimal Preconditioned Eigenvalue Xolvers (BLOPEX) in hypre and PETSc

We describe our software package Block Locally Optimal Preconditioned Eigenvalue Xolvers (BLOPEX) publicly released recently. BLOPEX is available as a stand-alone serial library, as an external package to PETSc (``Portable, Extensible Toolkit for Scientific Computation'', a general purpose suite of tools for the scalable solution of partial differential equations and related problems developed by Argonne National Laboratory), and is also built into {\it hypre} (``High Performance Preconditioners'', scalable linear solvers package developed by Lawrence Livermore National Laboratory). The present BLOPEX release includes only one solver--the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) method for symmetric eigenvalue problems. {\it hypre} provides users with advanced high-quality parallel preconditioners for linear systems, in particular, with domain decomposition and multigrid preconditioners. With BLOPEX, the same preconditioners can now be efficiently used for symmetric eigenvalue problems. PETSc facilitates the integration of independently developed application modules with strict attention to component interoperability, and makes BLOPEX extremely easy to compile and use with preconditioners that are available via PETSc. We present the LOBPCG algorithm in BLOPEX for {\it hypre} and PETSc. We demonstrate numerically the scalability of BLOPEX by testing it on a number of distributed and shared memory parallel systems, including a Beowulf system, SUN Fire 880, an AMD dual-core Opteron workstation, and IBM BlueGene/L supercomputer, using PETSc domain decomposition and {\it hypre} multigrid preconditioning. We test BLOPEX on a model problem, the standard 7-point finite-difference approximation of the 3-D Laplacian, with the problem size in the range $10^5-10^8$.Comment: Submitted to SIAM Journal on Scientific Computin

Real-space electronic structure calculations for nanoscale systems

In this thesis, basic research focused on quantum systems relevant for the future nanotechnologies is presented. The research is modeling based on electronic structure calculations using the density-functional theory. For the solution of the ensuing Kohn-Sham equations, we have developed a new numerical scheme based on the Rayleigh quotient multigrid method. While an important part of the thesis is formed by software development for three-dimensional first-principles real-space electronic structure calculations, we use axially symmetric model systems in the study of nanostructures. This approximation reduces the computational demands and allows studies of rather large nanoscale systems encompassing hundreds or thousands of electrons. In addition, by restricting the geometry to the axial symmetry and resorting to jellium models, many random effects related to the detailed ionic structure are absent, and the relevant physics is easier to extract from the simulations. Nanowires can be considered as the ultimate conductors in which the atomistic confinement of electrons perpendicular to the wire and the atomistic length of the wire lead to quantum mechanical effects in cohesive and transport properties. The breaking process of a nanowire is studied using the ultimate jellium model, in which the positive background charge compensates in every point the electronic charge. Thereby, the shape of the narrowing constriction is free to vary so that the total energy is minimized. The prospect of molecular electronics is to use single molecules as circuit components. The electronic transport in atomic chains of a few Na atoms between cone-shaped leads is investigated in the thesis. Electrons residing in a Na island on the Cu(111) surface form a quantum dot system, in which the quantum mechanical confinement in all directions determines the electronic properties. We have developed a simple jellium model system which reproduces the characteristics of the confined electron states seen in scanning tunneling microscope experiments.reviewe

Large Scale Computing and Storage Requirements for Basic Energy Sciences Research

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility supporting research within the Department of Energy's Office of Science. NERSC provides high-performance computing (HPC) resources to approximately 4,000 researchers working on about 400 projects. In addition to hosting large-scale computing facilities, NERSC provides the support and expertise scientists need to effectively and efficiently use HPC systems. In February 2010, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR) and DOE's Office of Basic Energy Sciences (BES) held a workshop to characterize HPC requirements for BES research through 2013. The workshop was part of NERSC's legacy of anticipating users future needs and deploying the necessary resources to meet these demands. Workshop participants reached a consensus on several key findings, in addition to achieving the workshop's goal of collecting and characterizing computing requirements. The key requirements for scientists conducting research in BES are: (1) Larger allocations of computational resources; (2) Continued support for standard application software packages; (3) Adequate job turnaround time and throughput; and (4) Guidance and support for using future computer architectures. This report expands upon these key points and presents others. Several 'case studies' are included as significant representative samples of the needs of science teams within BES. Research teams scientific goals, computational methods of solution, current and 2013 computing requirements, and special software and support needs are summarized in these case studies. Also included are researchers strategies for computing in the highly parallel, 'multi-core' environment that is expected to dominate HPC architectures over the next few years. NERSC has strategic plans and initiatives already underway that address key workshop findings. This report includes a brief summary of those relevant to issues raised by researchers at the workshop

Mathematical modeling and numerical simulation of innovative electronic nanostructures

Dans cette thèse, nous nous intéressons à la modélisation et la simulation de dispositifs nanoélectroniques innovants. Premièrement, nous dérivons formellement un modèle avec masse effective pour décrire le transport quantique des électrons dans des nanostructures très fortement confinées. Des simulations numériques illustrent l'intérêt du modèle obtenu pour un dispositif simplifié mais déjà significatif. La deuxième partie est consacrée à l'étude du transport non ballistique dans ces mêmes structures confinées. Nous analysons rigoureusement un modèle de drift-diffusion et puis nous décrivons et implémentons une approche de couplage spatial classique-quantique. Enfin, nous modélisons et simulons un nanodispositif de spintronique. Plus précisement, nous étudions le renversement d'aimantation dans un matériau ferromagnétique multi-couches sous l'effet d'un courant de spin.In this PhD thesis, we are interested in the modeling and the simulation of innovative electronic nanodevices. First, we formally derive an effective mass model describing the quantum motion of electrons in ultra-scaled confined nanostructures. Numerical simulations aim at testing the relevance of the obtained model for a simplified (but already significant) device. The second part is devoted to non-ballistic transport in these confined nanostructures. We rigorously analyse a drift-diffusion model and afterwards we describe and implement a classical-quantum spatial coupling approach. In the last part, we model and simulate a spintronic nanodevice. More precisely, we study the magnetization switching of a ferromagnetic material driven by a spin-current