Scientific and Computational Challenges of the Fusion Simulation Program (FSP)

This paper highlights the scientific and computational challenges facing the Fusion Simulation Program (FSP) a major national initiative in the United States with the primary objective being to enable scientific discovery of important new plasma phenomena with associated understanding that emerges only upon integration. This requires developing a predictive integrated simulation capability for magnetically-confined fusion plasmas that are properly validated against experiments in regimes relevant for producing practical fusion energy. It is expected to provide a suite of advanced modeling tools for reliably predicting fusion device behavior with comprehensive and targeted science-based simulations of nonlinearly-coupled phenomena in the core plasma, edge plasma, and wall region on time and space scales required for fusion energy production. As such, it will strive to embody the most current theoretical and experimental understanding of magnetic fusion plasmas and to provide a living framework for the simulation of such plasmas as the associated physics understanding continues to advance over the next several decades. Substantive progress on answering the outstanding scientific questions in the field will drive the FSP toward its ultimate goal of developing the ability to predict the behavior of plasma discharges in toroidal magnetic fusion devices with high physics fidelity on all relevant time and space scales. From a computational perspective, this will demand computing resources in the petascale range and beyond together with the associated multi-core algorithmic formulation needed to address burning plasma issues relevant to ITER - a multibillion dollar collaborative experiment involving seven international partners representing over half the world's population. Even more powerful exascale platforms will be needed to meet the future challenges of designing a demonstration fusion reactor (DEMO). Analogous to other major applied physics modeling projects (e.g., Climate Modeling), the FSP will need to develop software in close collaboration with computers scientists and applied mathematicians and validated against experimental data from tokamaks around the world. Specific examples of expected advances needed to enable such a comprehensive integrated modeling capability and possible "co-design" approaches will be discussed. _________________________________________________

Performance Evaluation of Plasma and Astrophysics Applications on Modern Parallel Vector Systems

Abstract. The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end computing (HEC) platforms, primarily because of their generality, scalability, and cost effectiveness. However, the growing gap between sustained and peak performance for full-scale scientific applications on such platforms has become major concern in high performance computing. The latest generation of custom-built parallel vector systems have the potential to address this concern for numerical algorithms with sufficient regularity in their computational structure. In this work, we explore two and three dimensional implementations of a plasma physics application, as well as a leading astrophysics package on some of today's most powerful supercomputing platforms. Results compare performance between the the vector-based Cray X1, Earth Simulator, and newly-released NEC SX-8, with the commodity-based superscalar platforms of the IBM Power3, Intel Itanium2, and AMD Opteron. Overall results show that the SX-8 attains unprecedented aggregate performance across our evaluated applications

Performance Evaluation of Plasma and Astrophysics Applications onModern Parallel Vector Systems

The last decade has witnessed a rapid proliferation ofsuperscalar cache-based microprocessors to build high-endcomputing (HEC)platforms, primarily because of their generality,scalability, and costeffectiveness. However, the growing gap between sustained and peakperformance for full-scale scientific applications on such platforms hasbecome major concern in highperformance computing. The latest generationof custom-built parallel vector systems have the potential to addressthis concern for numerical algorithms with sufficient regularity in theircomputational structure. In this work, we explore two and threedimensional implementations of a plasma physics application, as well as aleading astrophysics package on some of today's most powerfulsupercomputing platforms. Results compare performance between the thevector-based Cray X1, EarthSimulator, and newly-released NEC SX- 8, withthe commodity-based superscalar platforms of the IBM Power3, IntelItanium2, and AMDOpteron. Overall results show that the SX-8 attainsunprecedented aggregate performance across our evaluatedapplications

Risk-Based Seismic Design Optimization of Steel Building Systems with Passive Damping Devices

Nonlinear time history analysis software and an optimization algorithm for automating design of steel frame buildings with and without supplemental passive damping systems using the risk- or performance-based seismic design philosophy are developed in this dissertation. The software package developed is suitable for conducting dynamic analysis of 2D steel framed structures modeled as shear buildings with linear/nonlinear viscous and viscoelastic dampers. Both single degree of freedom (SDOF) and multiple degree of freedom (multistory or MDOF) shear-building systems are considered to validate the nonlinear analysis engine developed. The response of both un-damped and damped structures using the 1940 EI Centro (Imperial Valley) ground motion record and sinusoidal ground motion input are used in the validation. Comparison of response simulations is made with the dissertationSEES software system and analytical models based upon established dynamic analysis theory. A risk-based design optimization approach is described and formulation of unconstrained multiple objective design optimization problem statements suitable for this design philosophy are formulated. Solution to these optimization problems using a genetic algorithm are discussed and a prototypical three story, four bay shear-building structure is used to demonstrate applicability of the proposed risk-based design optimization approach for design of moderately sized steel frames with and without supplemental damping components. All programs are developed in MATLAB environment and run on Windows XP operating system. A personal computer cluster with four computational nodes is set up to reduce the computing time and a description of implementation of the automated design algorithm in a cluster computing environment is provided. The prototype building structure is used to demonstrate the impact that the number of design variables has on the resulting designs and to demonstrate the impact that use of supplemental viscous and viscoelastic damping devices have on minimizing initial construction cost and minimizing expected annual loss due to seismic hazard