3,379 research outputs found

    Turbomachinery CFD on parallel computers

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    The role of multistage turbomachinery simulation in the development of propulsion system models is discussed. Particularly, the need for simulations with higher fidelity and faster turnaround time is highlighted. It is shown how such fast simulations can be used in engineering-oriented environments. The use of parallel processing to achieve the required turnaround times is discussed. Current work by several researchers in this area is summarized. Parallel turbomachinery CFD research at the NASA Lewis Research Center is then highlighted. These efforts are focused on implementing the average-passage turbomachinery model on MIMD, distributed memory parallel computers. Performance results are given for inviscid, single blade row and viscous, multistage applications on several parallel computers, including networked workstations

    Architecture independent environment for developing engineering software on MIMD computers

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    Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management

    Parallel matrix inversion techniques

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    In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices on parallel and distributed computers. We propose two algorithms, one for SIMD implementation and the other for MIMD implementation. These algorithms are modified versions of Gaussian elimination and they take into account the sparseness of the matrix. Our algorithms perform better than the general parallel Gaussian elimination algorithm. In order to demonstrate the usefulness of our technique, we implemented the snake problem using our sparse matrix algorithm. Our studies reveal that the proposed sparse matrix inversion algorithm significantly reduces the time taken for obtaining the solution of the snake problem. In this paper, we present the results of our experimental work

    Probabilistic structural mechanics research for parallel processing computers

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    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

    An assessment of the connection machine

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    The CM-2 is an example of a connection machine. The strengths and problems of this implementation are considered as well as important issues in the architecture and programming environment of connection machines in general. These are contrasted to the same issues in Multiple Instruction/Multiple Data (MIMD) microprocessors and multicomputers

    Expanded delta networks for very large parallel computers

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    In this paper we analyze a generalization of the traditional delta network, introduced by Patel [21], and dubbed Expanded Delta Network (EDN). These networks provide in general multiple paths that can be exploited to reduce contention in the network resulting in increased performance. The crossbar and traditional delta networks are limiting cases of this class of networks. However, the delta network does not provide the multiple paths that the more general expanded delta networks provide, and crossbars are to costly to use for large networks. The EDNs are analyzed with respect to their routing capabilities in the MIMD and SIMD models of computation.The concepts of capacity and clustering are also addressed. In massively parallel SIMD computers, it is the trend to put a larger number processors on a chip, but due to I/O constraints only a subset of the total number of processors may have access to the network. This is introduced as a Restricted Access Expanded Delta Network of which the MasPar MP-1 router network is an example

    Highly parallel computation

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    Highly parallel computing architectures are the only means to achieve the computation rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines and current research focuses on which architectures designated as multiple instruction multiple datastream (MIMD) and single instruction multiple datastream (SIMD) have produced the best results to date; neither shows a decisive advantage for most near-homogeneous scientific problems. For scientific problems with many dissimilar parts, more speculative architectures such as neural networks or data flow may be needed

    Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers

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    In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method. Computationally this involves solving a sparse symmetric positive definite (SSPD) system of equations. The choice of direct and indirect methods for the solution of this system, and the design of data structures to take advantage of serial, coarse grain parallel and massively parallel computer architectures, are considered in detail. We put forward arguments as to why integration of the system within a sparse simplex solver is important and outline how the system is designed to achieve this integration
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