Enabling Technologies for Petascale Electromagnetic Accelerator Simulation

The SciDAC2 accelerator project at SLAC aims to simulate an entire three-cryomodule radio frequency (RF) unit of the International Linear Collider (ILC) main Linac. Petascale computing resources supported by advances in Applied Mathematics (AM) and Computer Science (CS) and INCITE Program are essential to enable such very large-scale electromagnetic accelerator simulations required by the ILC Global Design Effort. This poster presents the recent advances and achievements in the areas of CS/AM through collaborations

Design and Optimization of Large Accelerator Systems through High-Fidelity Electromagnetic Simulations

SciDAC1, with its support for the 'Advanced Computing for 21st Century Accelerator Science and Technology' (AST) project, witnessed dramatic advances in electromagnetic (EM) simulations for the design and optimization of important accelerators across the Office of Science. In SciDAC2, EM simulations continue to play an important role in the 'Community Petascale Project for Accelerator Science and Simulation' (ComPASS), through close collaborations with SciDAC CETs/Institutes in computational science. Existing codes will be improved and new multi-physics tools will be developed to model large accelerator systems with unprecedented realism and high accuracy using computing resources at petascale. These tools aim at targeting the most challenging problems facing the ComPASS project. Supported by advances in computational science research, they have been successfully applied to the International Linear Collider (ILC) and the Large Hadron Collider (LHC) in High Energy Physics (HEP), the JLab 12-GeV Upgrade in Nuclear Physics (NP), as well as the Spallation Neutron Source (SNS) and the Linac Coherent Light Source (LCLS) in Basic Energy Sciences (BES)

Metodos de decomposição de dominio e multigrid para a discretização, por elementos finitos, de equações de Maxuel em duas dimensões

Orientador : Mario Arlindo Casarin JuniorDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação CientificaMestradoMestre em Matemática Aplicad

Domain Decomposition Methods for PDE Constrained Optimization Problems ⋆

Abstract. Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for the parallel numerical solution of such problems involve sequential quadratic programming (SQP), with either reduced or full space approaches. In this paper we propose and investigate a class of parallel full space SQP Lagrange-Newton-Krylov-Schwarz (LNKSz) algorithms. In LNKSz, a Lagrangian functional is formed and differentiated to obtain a Karush-Kuhn-Tucker (KKT) system of nonlinear equations. Inexact Newton method with line search is then applied. At each Newton iteration the linearized KKT system is solved with a Schwarz preconditioned Krylov subspace method. We apply LNKSz to the parallel numerical solution of some boundary control problems of two-dimensional incompressible Navier-Stokes equations. Numerical results are reported for different combinations of Reynolds number, mesh size and number of parallel processors.