Design and analysis of numerical algorithms for the solution of linear systems on parallel and distributed architectures

The increasing availability of parallel computers is having a very significant impact on all aspects of scientific computation, including algorithm research and software development in numerical linear algebra. In particular, the solution of linear systems, which lies at the heart of most calculations in scientific computing is an important computation found in many engineering and scientific applications. In this thesis, well-known parallel algorithms for the solution of linear systems are compared with implicit parallel algorithms or the Quadrant Interlocking (QI) class of algorithms to solve linear systems. These implicit algorithms are (2x2) block algorithms expressed in explicit point form notation. [Continues.

Performance Analysis of Hardware/Software Co-Design of Matrix Solvers

Solving a system of linear and nonlinear equations lies at the heart of many scientific and engineering applications such as circuit simulation, applications in electric power networks, and structural analysis. The exponentially increasing complexity of these computing applications and the high cost of supercomputing force us to explore affordable high performance computing platforms. The ultimate goal of this research is to develop hardware friendly parallel processing algorithms and build cost effective high performance parallel systems using hardware in order to enable the solution of large linear systems. In this thesis, FPGA-based general hardware architectures of selected iterative methods and direct methods are discussed. Xilinx Embedded Development Kit (EDK) hardware/software (HW/SW) codesigns of these methods are also presented. For iterative methods, FPGA based hardware architectures of Jacobi, combined Jacobi and Gauss-Seidel, and conjugate gradient (CG) are proposed. The convergence analysis of the LNS-based Jacobi processor demonstrates to what extent the hardware resource constraints and additional conversion error affect the convergence of Jacobi iterative method. Matlab simulations were performed to compare the performance of three iterative methods in three ways, i.e., number of iterations for any given tolerance, number of iterations for different matrix sizes, and computation time for different matrix sizes. The simulation results indicate that the key to a fast implementation of the three methods is a fast implementation of matrix multiplication. The simulation results also show that CG method takes less number of iterations for any given tolerance, but more computation time as matrix size increases compared to other two methods, since matrix-vector multiplication is a more dominant factor in CG method than in the other two methods. By implementing matrix multiplications of the three methods in hardware with Xilinx EDK HW/SW codesign, the performance is significantly improved over pure software Power PC (PPC) based implementation. The EDK implementation results show that CG takes less computation time for any size of matrices compared to other two methods in HW/SW codesign, due to that fact that matrix multiplications dominate the computation time of all three methods while CG requires less number of iterations to converge compared to other two methods. For direct methods, FPGA-based general hardware architecture and Xilinx EDK HW/SW codesign of WZ factorization are presented. Single unit and scalable hardware architectures of WZ factorization are proposed and analyzed under different constraints. The results of Matlab simulations show that WZ runs faster than the LU on parallel processors but slower on a single processor. The simulation results also indicate that the most time consuming part of WZ factorization is matrix update. By implementing the matrix update of WZ factorization in hardware with Xilinx EDK HW/SW codesign, the performance is also apparently improved over PPC based pure software implementation

The Parallel Implementation of the Waveform Relaxation Method for Transient Stability Simulations

In this paper, the authors extend the results of their earlier paper on waveform relamtion (WR), which is a parallel algorithm for transient stability analysis. The WR algorithm is extended to a structure-preserving power system model in which the loads are retained. This results in a system of differential/ algebraic equations (DAEs). Power systems exhibit several unique dynamic properties which may be exploited in an advantageous manner by the WR algorithm. This leads to a greater computational efficiency than most other direct methods of simulation. This paper presents several theoretical results as well as computational results on parallel implementation

Parallel computing in network optimization

Caption title.Includes bibliographical references (p. 82-95).Supported by the NSF. CCR-9103804Dimitri Bertsekas ... [et al.]

The Use of Parallel Processing in VLSI Computer-Aided Design Application

Coordinated Science Laboratory was formerly known as Control Systems LaboratorySemiconductor Research Corporation / 87-DP-10

Strategies for producing fast finite element solutions of the incompressible Navier-Stokes equations on massively parallel architectures

To take advantage of the inherent flexibility of the finite element method in solving for flows within complex geometries, it is necessary to produce efficient implementations of the method. Segregation of the solution scheme and the use of parallel computers are two ways of doing this. Here, the optimisation of a sequential segregated finite element algorithm is discussed, together with the various strategies by which this is done. Furthermore, the implications of parallelising the code onto a massively parallel computer, the MasPar, are explored. This machine is of Single Instruction Multiple Data type and so modifications to the computer code have been necessary. A general methodology for the implementation of finite element programs is presented based on projecting the levels of data within the algorithm into a form which is ideal for parallelisation. Application of this methodology, in a high level language, has resulted in a code which runs at just under 30MFlops (in double precision). The computations are performed with minimal inter-processor communication and this represents an efficiency of 20% of the theoretical peak speed. Even though only high level language constructs have been used, this efficiency is comparable with other work using low level constructs on machines of this architecture. In particular, the use of data parallel arrays and the utilisation of the non-unique machine specific features of the computer architecture have produced an efficient, fast program

Application of Holomorphic Embedding to the Power-Flow Problem

abstract: With the power system being increasingly operated near its limits, there is an increasing need for a power-flow (PF) solution devoid of convergence issues. Traditional iterative methods are extremely initial-estimate dependent and not guaranteed to converge to the required solution. Holomorphic Embedding (HE) is a novel non-iterative procedure for solving the PF problem. While the theory behind a restricted version of the method is well rooted in complex analysis, holomorphic functions and algebraic curves, the practical implementation of the method requires going beyond the published details and involves numerical issues related to Taylor's series expansion, Padé approximants, convolution and solving linear matrix equations. The HE power flow was developed by a non-electrical engineer with language that is foreign to most engineers. One purpose of this document to describe the approach using electric-power engineering parlance and provide an understanding rooted in electric power concepts. This understanding of the methodology is gained by applying the approach to a two-bus dc PF problem and then gradually from moving from this simple two-bus dc PF problem to the general ac PF case. Software to implement the HE method was developed using MATLAB and numerical tests were carried out on small and medium sized systems to validate the approach. Implementation of different analytic continuation techniques is included and their relevance in applications such as evaluating the voltage solution and estimating the bifurcation point (BP) is discussed. The ability of the HE method to trace the PV curve of the system is identified.Dissertation/ThesisMasters Thesis Electrical Engineering 201