A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Una contribució al càlcul de valors i vectors propis i a l'anàlisi de l'escalabilitat

El càlcul de valors i vectors propis és un nucli computacional que forma part de diverses aplicacions de tipus científic i tècnic que requereixen una potència de càlcul molt gran. Aquestes aplicacions no poden resoldre's en sistemes monoprocessadors perquè aquests sistemes no proporcionen la potència de càlcul suficient per resoldre el problema amb un temps raonable. Una solució possible a aquest problema és la utilització de sistemes paral·lels.El contingut d'aquest treball pot dividir-se en quatre parts ben diferenciades; en les tres primeres parts dels valors i vectors propis en sistemes multicomputadors amb diferents topologies: hipercub, malla i torus; en l'última part del treball es proposa una metodologia d'anàlisis de l'escalabilitat de sistemes paral·lels.- En la primera part del treball es proposen un conjunt d'algorismes paral·lels per hipercubs: BR segmentat, alfa-optimal i Grau-4. Tots aquests algorismes es basen en l'algorisme Block Recursive proposat a [42]. Els nous algorismes proposats tenen la capacitat d'utilitzar de forma més eficient el potencial paral·lelisme de comunicacions que ofereix una arquitectura multiple-port amb els que s'aconsegueix una reducció del cost de la comunicació considerable respecte al cost de comunicació de l'algorisme original.- En la segona part del treball es proposa un nou algorisme amb una topologia de comunicació en malla bidimensional (2D). Aquest algorimse l'hem anomenat algorisme 2D. Es veurà que aquest nou algorisme aconsegueix reduir el cost total considerablement respecte als algorismes que han estat proposats per altres autors per malles i torus.- En la tercera part, s'estudia l'eficiència de l'algorisme BR-segmentat (algorisme amb una topologia de comunicació en hipercub proposat en la primera part de la tesi) un cop mapejat en un multicomputador amb una topologia en malla o en torus. A l'hora de realitzar el mapeig s'ha aplicat i ampliat una metodologia desenvolupada en el grup de treball que ens permet realitzar el mapeig de forma eficient i sistemàtic d'una topologia en hipercub a una topologia en malla o torus. El cost de la comunicació del nou algorisme es compara amb el cost de l'algorisme 2D proposat en la segona part del treball.- Finalment, en l'última part d'aquest treball es proposa una metodologia d'anàlisi de l'escalabilitat de sistemes paral·lels orientada a l'usuari final del sistema. S'utilitza l'algorisme 2D mapejat en una línia per mostrar un exemple d'aplicació de la metodologia

Parallel solution of power system linear equations

At the heart of many power system computations lies the solution of a large sparse set of linear equations. These equations arise from the modelling of the network and are the cause of a computational bottleneck in power system analysis applications. Efficient sequential techniques have been developed to solve these equations but the solution is still too slow for applications such as real-time dynamic simulation and on-line security analysis. Parallel computing techniques have been explored in the attempt to find faster solutions but the methods developed to date have not efficiently exploited the full power of parallel processing. This thesis considers the solution of the linear network equations encountered in power system computations. Based on the insight provided by the elimination tree, it is proposed that a novel matrix structure is adopted to allow the exploitation of parallelism which exists within the cutset of a typical parallel solution. Using this matrix structure it is possible to reduce the size of the sequential part of the problem and to increase the speed and efficiency of typical LU-based parallel solution. A method for transforming the admittance matrix into the required form is presented along with network partitioning and load balancing techniques. Sequential solution techniques are considered and existing parallel methods are surveyed to determine their strengths and weaknesses. Combining the benefits of existing solutions with the new matrix structure allows an improved LU-based parallel solution to be derived. A simulation of the improved LU solution is used to show the improvements in performance over a standard LU-based solution that result from the adoption of the new techniques. The results of a multiprocessor implementation of the method are presented and the new method is shown to have a better performance than existing methods for distributed memory multiprocessors

Computational methods and software systems for dynamics and control of large space structures

Two key areas of crucial importance to the computer-based simulation of large space structures are discussed. The first area involves multibody dynamics (MBD) of flexible space structures, with applications directed to deployment, construction, and maneuvering. The second area deals with advanced software systems, with emphasis on parallel processing. The latest research thrust in the second area involves massively parallel computers

Research summary, January 1989 - June 1990

The Research Institute for Advanced Computer Science (RIACS) was established at NASA ARC in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 62 universities with graduate programs in the aerospace sciences, under a Cooperative Agreement with NASA. RIACS serves as the representative of the USRA universities at ARC. This document reports our activities and accomplishments for the period 1 Jan. 1989 - 30 Jun. 1990. The following topics are covered: learning systems, networked systems, and parallel systems

Higher-Order DGFEM Transport Calculations on Polytope Meshes for Massively-Parallel Architectures

In this dissertation, we develop improvements to the discrete ordinates (S_N) neutron transport equation using a Discontinuous Galerkin Finite Element Method (DGFEM) spatial discretization on arbitrary polytope (polygonal and polyhedral) grids compatible for massively-parallel computer architectures. Polytope meshes are attractive for multiple reasons, including their use in other physics communities and their ease in handling local mesh refinement strategies. In this work, we focus on two topical areas of research. First, we discuss higher-order basis functions compatible to solve the DGFEM S_N transport equation on arbitrary polygonal meshes. Second, we assess Diffusion Synthetic Acceleration (DSA) schemes compatible with polytope grids for massively-parallel transport problems. We first utilize basis functions compatible with arbitrary polygonal grids for the DGFEM transport equation. We analyze four different basis functions that have linear completeness on polygons: the Wachspress rational functions, the PWL functions, the mean value coordinates, and the maximum entropy coordinates. We then describe the procedure to extend these polygonal linear basis functions into the quadratic serendipity space of functions. These quadratic basis functions can exactly interpolate monomial functions up to order 2. Both the linear and quadratic sets of basis functions preserve transport solutions in the thick diffusion limit. Maximum convergence rates of 2 and 3 are observed for regular transport solutions for the linear and quadratic basis functions, respectively. For problems that are limited by the regularity of the transport solution, convergence rates of 3/2 (when the solution is continuous) and 1/2 (when the solution is discontinuous) are observed. Spatial Adaptive Mesh Refinement (AMR) achieved superior convergence rates than uniform refinement, even for problems bounded by the solution regularity. We demonstrated accuracy in the AMR solutions by allowing them to reach a level where the ray effects of the angular discretization are realized. Next, we analyzed DSA schemes to accelerate both the within-group iterations as well as the thermal upscattering iterations for multigroup transport problems. Accelerating the thermal upscattering iterations is important for materials (e.g., graphite) with significant thermal energy scattering and minimal absorption. All of the acceleration schemes analyzed use a DGFEM discretization of the diffusion equation that is compatible with arbitrary polytope meshes: the Modified Interior Penalty Method (MIP). MIP uses the same DGFEM discretization as the transport equation. The MIP form is Symmetric Positive De_nite (SPD) and e_ciently solved with Preconditioned Conjugate Gradient (PCG) with Algebraic MultiGrid (AMG) preconditioning. The analysis from previous work was extended to show MIP's stability and robustness for accelerating 3D transport problems. MIP DSA preconditioning was implemented in the Parallel Deterministic Transport (PDT) code at Texas A&M University and linked with the HYPRE suite of linear solvers. Good scalability was numerically verified out to around 131K processors. The fraction of time spent performing DSA operations was small for problems with sufficient work performed in the transport sweep (O(10^3) angular directions). Finally, we have developed a novel methodology to accelerate transport problems dominated by thermal neutron upscattering. Compared to historical upscatter acceleration methods, our method is parallelizable and amenable to massively parallel transport calculations. Speedup factors of about 3-4 were observed with our new method

[Activity of Institute for Computer Applications in Science and Engineering]

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science