Probabilistic structural mechanics research for parallel processing computers

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical

Exploiting parallelism in n-D convex hull algorithms

PhD ThesisThe convex hull is a problem of primary importance because of its applications in computational geometry. A number of sequential and parallel algorithms for computing the convex hull of a finite set of points in the lower dimensions are known. In compar- ison, the general n-D problem is not as well understood and parallel algorithms are not so prevalent because the 2-D and 3-D methods are not easily extended to the general case. This thesis presents parallel algorithms for evaluating the general n- D convex hull problem (where 2-D and 3-D are special cases) using Swart's sequential algorithm. One of our methods combines a gift-wrapping technique with partitioning and merge algorithms > where the original list is split into p 1 partitions followed by the computation of the subhulls using the sequential n-D gift-wrapping method. The partial hulls are then combined using a fanin tree. The second method computes the convex hull in parallel by wrapping around the edges until a complete facial lattice structure of the polytope is generated. Several parameterised versions of the proposed algorithms have been implemented on the shared memory and message passing architectures. In the former, performance on an Encore Multimax using Encore Parallel Threads and the more lightweight Microthread programming utilities are examined. In the latter, performance on a transputer based machine using CS- Tools is discussed. We have shown that our techniques will be useful in the construction of faster algorithms which employ the n-D convex hull algorithms as a sub-algorithmCommonwealth Scholarship Commission in the United Kingdo

A parallel functional language compiler for message-passing multicomputers

The research presented in this thesis is about the design and implementation of Naira, a parallel, parallelising compiler for a rich, purely functional programming language. The source language of the compiler is a subset of Haskell 1.2. The front end of Naira is written entirely in the Haskell subset being compiled. Naira has been successfully parallelised and it is the largest successfully parallelised Haskell program having achieved good absolute speedups on a network of SUN workstations. Having the same basic structure as other production compilers of functional languages, Naira's parallelisation technology should carry forward to other functional language compilers. The back end of Naira is written in C and generates parallel code in the C language which is envisioned to be run on distributed-memory machines. The code generator is based on a novel compilation scheme specified using a restricted form of Milner's 7r-calculus which achieves asynchronous communication. We present the first working implementation of this scheme on distributed-memory message-passing multicomputers with split-phase transactions. Simulated assessment of the generated parallel code indicates good parallel behaviour. Parallelism is introduced using explicit, advisory user annotations in the source' program and there are two major aspects of the use of annotations in the compiler. First, the front end of the compiler is parallelised so as to improve its efficiency at compilation time when it is compiling input programs. Secondly, the input programs to the compiler can themselves contain annotations based on which the compiler generates the multi-threaded parallel code. These, therefore, make Naira, unusually and uniquely, both a parallel and a parallelising compiler. We adopt a medium-grained approach to granularity where function applications form the unit of parallelism and load distribution. We have experimented with two different task distribution strategies, deterministic and random, and have also experimented with thread-based and quantum- based scheduling policies. Our experiments show that there is little efficiency difference for regular programs but the quantum-based scheduler is the best in programs with irregular parallelism. The compiler has been successfully built, parallelised and assessed using both idealised and realistic measurement tools: we obtained significant compilation speed-ups on a variety of simulated parallel architectures. The simulated results are supported by the best results obtained on real hardware for such a large program: we measured an absolute speedup of 2.5 on a network of 5 SUN workstations. The compiler has also been shown to have good parallelising potential, based on popular test programs. Results of assessing Naira's generated unoptimised parallel code are comparable to those produced by other successful parallel implementation projects

Computer algebra and transputers applied to the finite element method

Recent developments in computing technology have opened new prospects for computationally intensive numerical methods such as the finite element method. More complex and refined problems can be solved, for example increased number and order of the elements improving accuracy. The power of Computer Algebra systems and parallel processing techniques is expected to bring significant improvement in such methods. The main objective of this work has been to assess the use of these techniques in the finite element method. The generation of interpolation functions and element matrices has been investigated using Computer Algebra. Symbolic expressions were obtained automatically and efficiently converted into FORTRAN routines. Shape functions based on Lagrange polynomials and mapping functions for infinite elements were considered. One and two dimensional element matrices for bending problems based on Hermite polynomials were also derived. Parallel solvers for systems of linear equations have been developed since such systems often arise in numerical methods. Both symmetric and asymmetric solvers have been considered. The implementation was on Transputer-based machines. The speed-ups obtained are good. An analysis by finite element method of a free surface flow over a spillway has been carried out. Computer Algebra was used to derive the integrand of the element matrices and their numerical evaluation was done in parallel on a Transputer-based machine. A graphical interface was developed to enable the visualisation of the free surface and the influence of the parameters. The speed- ups obtained were good. Convergence of the iterative solution method used was good for gated spillways. Some problems experienced with the non-gated spillways have lead to a discussion and tests of the potential factors of instability

A computing structure for data acquisition in high energy physics

A review of the development of parallel computing ispresented, followed by a summary of currently recognised typesof parallel computer and a brief summary of some applicationsof parallel computing in the field of high energy physics.The computing requirement at the data acquisition stageof a particular set of high energy physics experiments isdetailed, with reference to the computing system currently inuse. The requirement for a parallel processor to process thedata from these experiments is established and a possiblecomputing structure put forward.The topology proposed consists of a set of rings ofprocessors stacked to give a cylindrical arrangement, ananalytical approach is used to verify the suitability andextensibility of the suggested scheme. Using simulationresults the behaviour of rings and cylinders of processorsusing different algorithms for the movement of data within thesystem and different patterns of data input is presented anddiscussed.Practical hardware and software details for processingequipment capable of supporting such a structure as presentedhere is given, various algorithms for use with this equipment,e. g. program distribution, are developed and the software forthe implementation of the cylindrical structure is presented.Appendices of constructional information and all programlistings are included

The instruction of systolic array (ISA) and simulation of parallel algorithms

Systolic arrays have proved to be well suited for Very Large Scale Integrated technology (VLSI) since they: -Consist of a regular network of simple processing cells, -Use local communication between the processing cells only, -Exploit a maximal degree of parallelism. However, systolic arrays have one main disadvantage compared with other parallel computer architectures: they are special purpose architectures only capable of executing one algorithm, e.g., a systolic array designed for sorting cannot be used to form matrix multiplication. Several approaches have been made to make systolic arrays more flexible, in order to be able to handle different problems on a single systolic array. In this thesis an alternative concept to a VLSI-architecture the Soft-Systolic Simulation System (SSSS), is introduced and developed as a working model of virtual machine with the power to simulate hard systolic arrays and more general forms of concurrency such as the SIMD and MIMD models of computation. The virtual machine includes a processing element consisting of a soft-systolic processor implemented in the virtual.machine language. The processing element considered here was a very general element which allows the choice of a wide range of arithmetic and logical operators and allows the simulation of a wide class of algorithms but in principle extra processing cells can be added making a library and this library be tailored to individual needs. The virtual machine chosen for this implementation is the Instruction Systolic Array (ISA). The ISA has a number of interesting features, firstly it has been used to simulate all SIMD algorithms and many MIMD algorithms by a simple program transformation technique, further, the ISA can also simulate the so-called wavefront processor algorithms, as well as many hard systolic algorithms. The ISA removes the need for the broadcasting of data which is a feature of SIMD algorithms (limiting the size of the machine and its cycle time) and also presents a fairly simple communication structure for MIMD algorithms. The model of systolic computation developed from the VLSI approach to systolic arrays is such that the processing surface is fixed, as are the processing elements or cells by virtue of their being embedded in the processing surface. The VLSI approach therefore freezes instructions and hardware relative to the movement of data with the virtual machine and softsystolic programming retaining the constructions of VLSI for array design features such as regularity, simplicity and local communication, allowing the movement of instructions with respect to data. Data can be frozen into the structure with instructions moving systolically. Alternatively both the data and instructions can move systolically around the virtual processors, (which are deemed fixed relative to the underlying architecture). The ISA is implemented in OCCAM programs whose execution and output implicitly confirm the correctness of the design. The soft-systolic preparation comprises of the usual operating system facilities for the creation and modification of files during the development of new programs and ISA processor elements. We allow any concurrent high level language to be used to model the softsystolic program. Consequently the Replicating Instruction Systolic Array Language (RI SAL) was devised to provide a very primitive program environment to the ISA but adequate for testing. RI SAL accepts instructions in an assembler-like form, but is fairly permissive about the format of statements, subject of course to syntax. The RI SAL compiler is adopted to transform the soft-systolic program description (RISAL) into a form suitable for the virtual machine (simulating the algorithm) to run. Finally we conclude that the principles mentioned here can form the basis for a soft-systolic simulator using an orthogonally connected mesh of processors. The wide range of algorithms which the ISA can simulate make it suitable for a virtual simulating grid