Certain problems arising in engineering are modeled by nonstandard parabolic initial-boundary value problems in one space variable, which involve an integral term over the spatial domain of a function of the desired s...
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Certain problems arising in engineering are modeled by nonstandard parabolic initial-boundary value problems in one space variable, which involve an integral term over the spatial domain of a function of the desired solution. Hence, in the past few years interest has substantially increased in the solutions of these problems. As a result numerous research papers have also been devoted to the subject. Although considerable amount of work has been done in the past, there is still a lack of a completely satisfactory computational scheme. Also, there are some cases that have not been studied numerically yet. In the current article several approaches for the numerical solution of the one-dimensional parabolic equation subject to the specification of mass, which have been considered in the literature, are reported. Finite difference methods have been proposed for the numerical solution of the new nonclassic boundary value problem. To investigate the performance of the proposed algorithm, we consider solving a test problem. (c) 2005 Wiley Periodicals, Inc.
In this article we present a detailed numerical study of three-dimensional structures in gaseous detonations, using a parallelized, unsplit, shock-capturing algorithm. The computational domain consisted of a rectangul...
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In this article we present a detailed numerical study of three-dimensional structures in gaseous detonations, using a parallelized, unsplit, shock-capturing algorithm. The computational domain consisted of a rectangular tube with periodic conditions on its lateral boundaries. A slightly perturbed ZND profile has been used as initial condition. Previous experimental studies in rectangular shock tubes suggest that there are two basic types of detonation structures: rectangular and diagonal ones. Rectangular structures are characterized by triple lines along the front that are parallel to the walls of the flow domain and by the presence of slapping waves on the walls. On the other hand, diagonal structures are characterized by diagonal triple lines and the absence of slapping waves on the walls. Both structures have been numerically reproduced in our study by suitably perturbing the initial conditions. All the important features of the flow fields that have been experimentally observed are reproduced in our simulations. Finally, an analysis of the geometric similarities between the two types of structures is also presented herein. (c) 2005 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
This paper describes a parallel implementation of a Lanczos-based method to solve generalised eigenvalue problems related to the modal computation of arbitrarily shaped waveguides. This efficient implementation is int...
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For solving linear system of equations is known several algorithms. Iteration algorithms are recommended for the large linear systems with sparse matrix. But in the case of general non-symmetrical or n x m matrices th...
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We describe an implementation of a compact parallel algorithm for 3D Delaunay tetrahedralization on a 64-processor shared-memory machine. Our algorithm uses a concurrent version of the Bowyer-Watson incremental insert...
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ISBN:
(纸本)1595933409
We describe an implementation of a compact parallel algorithm for 3D Delaunay tetrahedralization on a 64-processor shared-memory machine. Our algorithm uses a concurrent version of the Bowyer-Watson incremental insertion, and a thread-safe space-efficient structure for representing the mesh. Using the implementation we are able to generate significantly larger Delaunay meshes than have previously been generated - 10 billion tetrahedra on a 64 processor SMP using 200GB of RAM. The implementation makes use of a locality based rela-beling of the vertices that serves three purposes - it is used as part of the space efficient representation, it improves the memory locality, and it reduces the overhead necessary for locks. The implementation also makes use of a caching technique to avoid excessive decoding of vertex information, a technique for backing out of insertions that collide, and a shared work queue for maintaining points that have yet to be inserted. Copyright 2006 ACM.
This paper presents an optimal sequential and an optimal parallel algorithm to compute a minimum cardinality Steiner set and a Steiner tree. The sequential algorithm takes O (n) time and parallel algorithm takes O (lo...
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This paper presents an optimal sequential and an optimal parallel algorithm to compute a minimum cardinality Steiner set and a Steiner tree. The sequential algorithm takes O (n) time and parallel algorithm takes O (log n) time and O (n /log n) processors on an EREW PRAM model.
Weighted threshold functions with positive weights are a natural generalization of unweighted threshold functions. These functions are clearly monotone. However, the naive way of computing them is adding the weights o...
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Weighted threshold functions with positive weights are a natural generalization of unweighted threshold functions. These functions are clearly monotone. However, the naive way of computing them is adding the weights of the satisfied variables and checking if the sum is greater than the threshold;this algorithm is inherently non-monotone since addition is a non-monotone function. In this work we by-pass this addition step and construct a polynomial size logarithmic depth unbounded fan-in monotone circuit for every weighted threshold function, i.e., we show that weighted threshold functions are in mAC(1). (To the best of our knowledge, prior to our work no polynomial monotone circuits were known for weighted threshold functions.) Our monotone circuits are applicable for the cryptographic tool of secret sharing schemes. Using general results for compiling monotone circuits (Yao, 1989) and monotone formulae (Benaloh and Leichter, 1990) into secret sharing schemes, we get secret sharing schemes for every weighted threshold access structure. Specifically, we get: (1) information-theoretic secret sharing schemes where the size of each share is quasi-polynomial in the number of users, and (2) computational secret sharing schemes where the size of each share is polynomial in the number of users. (c) 2005 Elsevier B.V. All rights reserved.
External memory (EM) algorithms are designed for large-scale computational problems in which the size of the internal memory of the computer is only a small fraction of the problem size. Typical EM algorithms are spec...
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External memory (EM) algorithms are designed for large-scale computational problems in which the size of the internal memory of the computer is only a small fraction of the problem size. Typical EM algorithms are specially crafted for the EM situation. In the past, several attempts have been made to relate the large body of work on parallel algorithms to EM, but with limited success. The combination of EM computing, on multiple disks, with multiprocessor parallelism has been posted as a challenge by the ACM Working Group on Storage I/O for Large-Scale Computing. In this paper we provide a simulation technique which produces efficient parallel EM algorithms from efficient BSP-like parallel algorithms. The techniques obtained can accommodate one or multiple processors on the EM target machine, each with one or more disks, and they also adapt to the disk blocking factor of the target machine. When applied to existing BSP-like algorithms, our simulation technique produces improved parallel EM algorithms for a large number of problems.
We consider the problem of isosurface extraction and rendering for large scale time varying data. Such datasets have been appearing at an increasing rate especially from physics-based simulations, and can range in siz...
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Correct prediction of reservoir performance is an important issue for future reservoir development and exploration planning. This leads to the problem of accurate estimation of the rock and fluid properties used in co...
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Correct prediction of reservoir performance is an important issue for future reservoir development and exploration planning. This leads to the problem of accurate estimation of the rock and fluid properties used in construction of reservoir model. Usually, prior reservoir models are built by means of geostatistical algorithms and static information obtained from different sources and then adjusted for better production history matching. However, in some cases, static data can be very sparse and insufficient or misleading, for meaningful prior model construction. Under this scenario, adjusting of prior model would lead to a local minimum in automatic history matching algorithms and hence we will obtain results which may not be meaningful. This paper presents a new methodology for parallel Production data Processing. It assumes limited prior knowledge about static information and emphasizes the importance of production data. This methodology begins with several initial models which represent large amount of uncertainty in prior models. The method goes through a process of cyclic parallel adjustment of multiple reservoir models and reliable information gathering for further models improvements. The algorithm seeks common trends developed in the prior models as a result of partial incorporation of production data. Every generation of multiple models is adjusted by means of gradient-based automatic history matching technique. By using common trends gathered from prior models, new set of solutions (alternate realizations) are proposed. Generalized Changes Map (GCM) is the main source of information in this method. It provides the trend of common changes for all the models and serves as a basis of reliable parameters and spatial relationship selection. GCM captures two types of information: maximum changes occurred in prior model due to integration of production data, and convergence of values towards a common value in multiple models. These parameters form Generalized Dis
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