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ABSTRACT: A number of numerical methods for mildly nonlinear elliptic boundary value problems on general domains is presented. The discretization procedures considered are: a fourth-order FFT-type method, collocation using Hermite bicubic splines and Galerkin with linear triangular as well as quadratic quadrilateral isoparametric elements. The linearized collocation and Galerkin equations are solved by various direct methods available in the ELLPACK system. A comparative study of the above equation solvers is presented for different domain geometries and compilers. The evaluation of software for the general mildly nonlinear elliptic equations is performed over 36 instances from a population of 16 parametrized problems with ‘real world’ and ‘mathematical’ behaviour. The performance data suggests that collocation is an effective method for such general problems, while Galerkin with quadratic quadrilateral isoparametric elements is uniformly superior to the one with linear elements.
International Journal for Numerical Methods in Engineering 06/2005; 19(5):665 - 709. · 2.01 Impact Factor
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ABSTRACT: A neurofuzzy methodology is presented for motion planning in semi-autonomous mobile robots. The robotic automata considered are devices whose main feature is incremental learning from a human instructor. Fuzzy descriptions are used for the robot to acquire a repertoire of behaviors from an instructor which it may subsequently refine and recall using neural adaptive techniques. The robot is endowed with sensors providing local environmental input and a neurofuzzy internal state processing predictable aspects of its environment. Although it has no prior knowledge of the presence or the position of any obstructing objects, its motion planner allows it to make decisions in an unknown terrain. The methodology is demonstrated through a robot learning to travel from some start point to some target point without colliding with obstacles present in its path. The skills acquired are similar to those possessed by an automobile driver. The methodology has been successfully tested with a simulated robot performing a variety of navigation tasks.
02/2004;
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ABSTRACT: We outline the design of a recommendation system (MyPYTHIA) implemented as a Web portal. MyPYTHIA's design objectives include evaluating the quality and performance of scientific software on Grid platforms, creating knowledge about which software and computational services should be selected for solving particular problems, selecting parameters of software (or of computational services) based on user-specified computational objectives, providing access to performance data and knowledge bases over the Web and enabling recommendations for targeted application domains. MyPYTHIA uses a combination of statistical analysis, pattern extraction techniques and a database of software performance to map feature-based representations of problem instances to appropriate software. MyPYTHIA's open architecture allows the user to customize it for conducting individual case studies. We describe the architecture as well as several scientific domains of knowledge enabled by such case studies. Copyright © 2002 John Wiley & Sons, Ltd.
Concurrency and Computation Practice and Experience 10/2002; 14(13‐15):1481 - 1505. · 0.64 Impact Factor
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ABSTRACT: The traditional approach for estimating the performance of
numerical methods is to combine an operation's count with an asymptotic
error analysis. This analytic approach gives a general feel of the
comparative efficiency of methods, but it rarely leads to very precise
results. It is now recognized that accurate performance evaluation can
be made only with actual measurements on working software. Given that
such an approach requires an enormous amount of performance data related
to actual measurements, the development of novel approaches and systems
that intelligently and efficiently analyze these data is of great
importance to scientists and engineers. The paper presents intelligent
knowledge acquisition approaches and an integrated prototype system,
which enables the automatic and systematic analysis of performance data.
The system analyzes the performance data which is usually stored in a
database with statistical, and inductive learning techniques and
generates knowledge which can be incorporated in a knowledge base
incrementally. We demonstrate the use of the system in the context of a
case study, covering the analysis of numerical algorithms for the
pricing of American vanilla options in a Black and Scholes modeling
framework. We also present a qualitative and quantitative comparison of
two techniques used for the automated knowledge acquisition phase
IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans 12/2001; · 2.12 Impact Factor
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ABSTRACT: this document, we describe the initial design of a generic MPSE framework based on a network of computational agents assuming a net-centric run-time support environment. Moreover, we present the realization of this framework for designing a prototype MPSE (GasTurbnLab) for supporting simulations needed for the design of efficient gas turbine engines
05/2001;
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V.S. Adve,
R. Bagrodia,
J.C. Browne,
E. Deelman,
A. Dube, E.N. Houstis,
J.R. Rice,
R. Sakellariou,
D.J. Sundaram-Stukel,
P.J. Teller,
M.K. Vernon
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ABSTRACT: The POEMS project is creating an environment for end-to-end performance modeling of complex parallel and distributed systems, spanning the domains of application software, runtime and operating system software, and hardware architecture. Toward this end, the POEMS framework supports composition of component models from these different domains into an end-to-end system model. This composition can be specified using a generalized graph model of a parallel system, together with interface specifications that carry information about component behaviors and evaluation methods. The POEMS Specification Language compiler will generate an end-to-end system model automatically from such a specification. The components of the target system may be modeled using different modeling paradigms and at various levels of detail. Therefore, evaluation of a POEMS end-to-end system model may require a variety of evaluation tools including specialized equation solvers, queuing network solvers, and discrete event simulators. A single application representation based on static and dynamic task graphs serves as a common workload representation for all these modeling approaches. Sophisticated parallelizing compiler techniques allow this representation to be generated automatically for a given parallel program. POEMS includes a library of predefined analytical and simulation component models of the different domains and a knowledge base that describes performance properties of widely used algorithms. The paper provides an overview of the POEMS methodology and illustrates several of its key components. The modeling capabilities are demonstrated by predicting the performance of alternative configurations of Sweep3D, a benchmark for evaluating wavefront application technologies and high-performance, parallel architectures.
IEEE Transactions on Software Engineering 12/2000; · 1.98 Impact Factor
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ABSTRACT: The enormous amount of data that can be collected in any
performance evaluation study of a complex system indicates the need for
methodologies and systems capable of analyzing, fusing and reducing
high-dimensional data spaces with very high speed. In this paper, we
devise and present an adaptation of the Knowledge Discovery in Databases
(KDD) framework introduced by U. Fayyad et al. (1996) that supports the
above functionality for performance data of complex software/hardware
system pairs. The KDD framework considered integrates database
technology along with data mining techniques for uncovering patterns
from performance data and static system characteristics. A case study is
presented to demonstrate the effectiveness and applicability of the KDD
approach for the performance evaluation of complex systems. The data
mining tools utilized are general-purpose, public-domain and independent
of the specific performance database involved. We are currently
implementing the proposed KDD framework within an end-to-end performance
evaluation system for designing complex parallel and distributed systems
referred to as POEMS (Performance-Oriented End-to-end Modeling System)
Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on; 02/1999
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ABSTRACT: In this paper we present a paradigm for simulating complex systems. Such systems, typically found in Scientific and Engineering domains (simulating an engine, designing an airplane wing), involve multiple physical phenomena with complicated geometry. The computational techniques we propose use cooperating agents. Our focus in this paper will be on phenomenon modeled by PDEs, although much of the proposed methodology is equally applicable to any scientific computing task. We subdivide the physical object into components of simple geometric shapes modeled by a single, homogeneous mathematical model for which a problem solving environment (PSE) exists. PSEs are viewed as agents which solve the PDE on each component independently. The interfaces between the components must have physical interface conditions satisfied; mediator agents use relaxation techniques for this. We briefly describe an agent-based architecture and its implementation (SciAgents ) for building simulation systems that i...
01/1999;
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ABSTRACT: This paper is concerned with the numerical solution of the American option valuation problem formulated as a parabolic free boundary/initial value model. We introduce and analyze a front-tracking finite difference method and compare it with other commonly used techniques. The numerical experiments performed indicate that the front-tracking method considered is an efficient alternative for approximating simultaneously the option value and free boundary functions associated with the valuation problem.
Computational Economics 11/1998; 12(3):255-273. · 0.51 Impact Factor
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ABSTRACT: Neurofuzzy approaches for predicting financial time series are
investigated and shown to perform well in the context of various trading
strategies involving stocks and options. The horizon of prediction is
typically a few days and trading strategies are examined using
historical data. Two methodologies are presented wherein neural
predictors are used to anticipate the general behavior of financial
indexes (moving up, down, or staying constant) in the context of stocks
and options trading. The methodologies are tested with actual financial
data and show considerable promise as a decision making and planning
tool
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) 09/1998; · 3.08 Impact Factor
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ABSTRACT: this article is two fold. First we review the various parallelization techniques proposed to speed up the existing computational PDE models, that are based on the divide and conquer computational paradigm and involve some form of decomposition of the geometric or algebraic data-structures associated with these computations. Second, we review the parallel algorithms proposed to solve various classes of algebraic systems which are applicable to discrete PDE systems. For the sake of brevity of this exposition we focus on computational models derived from elliptic PDE models. Most of the parallelization techniques presented here are applicable to general semi-discrete and steady-state models. Specifically, we consider PDE models consisting of a PDE equation Lu = f , defined on some regionOmega and subject to some auxiliary condition Bu = g on the boundary ofOmega (= @OmegaGamma5
06/1998;
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IEEE Internet Computing 06/1998; · 2.00 Impact Factor
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ABSTRACT: Presents the design and prototype implementation of a system built
around the FINANZIA system that aims in the automated analysis and
classification of option pricing algorithms based on experimental data.
The main objective is to assist in the generation, storage and
evaluation of large amounts of experimental option pricing data and to
facilitate the identification of performance properties of the pricing
algorithms with respect to the various problems. The analysis of the
data is achieved using statistical and inductive logic techniques and
the identified properties are used to expand the knowledge base. We
demonstrate the use of the system in the context of a case study
covering the pricing of American vanilla options in a Black &
Scholes (1973) modeling framework
Computational Intelligence for Financial Engineering (CIFEr), 1998. Proceedings of the IEEE/IAFE/INFORMS 1998 Conference on; 04/1998
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ABSTRACT: Neurofuzzy approaches for predicting financial time series are investigated and shown to perform well in the context of various trading strategies involving stocks and options. The horizon of prediction is typically a few days and trading strategies are examined using historical data. Two methodologies are presented wherein neural predictors are used to anticipate the general behavior of financial indexes (moving up, down, or staying constant) in the context of stocks and options trading. The methodologies are tested with actual financial data and show considerable promise as a decision making and planning tool.
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) 02/1998; 28(4):520-31. · 3.08 Impact Factor
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ABSTRACT: This paper is concerned with the numerical solution of the American option valuation problem formulated as a parabolic free boundary/initial value model. We introduce and analyze a front-tracking finite difference method and compare it with other commonly used techniques. The numerical experiments performed indicate that the front-tracking method considered is an efficient alternative for approximating simultaneously the option value and free boundary functions associated with the valuation problem. Citation Copyright 1998 by Kluwer Academic Publishers.
Computational Economics. 01/1998; 12(3):255-73.
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ABSTRACT: The Internet offers scientists around the world access to
high-powered problem-solving environments (PSEs). With Purdue
University's Net Pellpack PSE server, they can solve complex partial
differential equations with common World Wide Web browsers that support
Java applets
IEEE Computational Science and Engineering 08/1997;
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ABSTRACT: Rapid advances in high performance computing (HPC) and the
Internet are heralding a paradigm shift to network-based scientific
software servers, libraries, repositories and problem solving
environments. According to this new paradigm, vital pieces of software
and information required for a computation are distributed across a
network and need to be identified and `linked' together at run time;
this implies a `net-centric' and collaborative scenario for scientific
computing. This scenario requires the application to dynamically choose
the best among several competing resources that can solve a given
problem. For these systems to become ubiquitous, efficient mechanisms
for collaboration and automatic inference of the abilities of multiple
`compute servers' need to be established. The authors demonstrate a
methodology to facilitate collaborative scientific computing. Their idea
is comprised of (i) a concept of `reasonableness' to automatically
generate exemplars for learning the mapping from problems to `servers'
and (ii) a neuro-fuzzy technique developed earlier by the authors that
conducts supervised classification on the exemplars generated. The
techniques work in an on-line manner and cater to mutually non-exclusive
classes which are critical in the collaborative networked computing
landscape
Neural Networks,1997., International Conference on; 07/1997
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ABSTRACT: A neurofuzzy methodology is presented for motion planning in semi-autonomous mobile robots. The robotic automata considered are devices whose main feature is incremental learning from a human instructor. Fuzzy descriptions are used for the robot to acquire a repertoire of behaviors from an instructor which it may subsequently refine and recall using neural adaptive techniques. The robot is endowed with sensors providing local environmental input and a neurofuzzy internal state processing predictable aspects of its environment. Although it has no prior knowledge of the presence or the position of any obstructing objects, its motion planner allows it to make decisions in an unknown terrain. The methodology is demonstrated through a robot learning to travel from some start point to some target point without colliding with obstacles present in its path. The skills acquired are similar to those possessed by an automobile driver. The methodology has been successfully tested with a simulated robot performing a variety of navigation tasks.
Journal of Intelligent and Robotic Systems 06/1997; 19(3):339-356. · 0.83 Impact Factor
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ABSTRACT: this paper we present a software framework for a virtual laboratory and report on our experiences in designing and implementing two software prototyping laboratories, microelectronics material (MicroSoftLab) and bioseparation (BioSoftLab) chemical engineering laboratories. Introduction to SoftLab 2 of 25 SoftLab : A virtual laboratory framework for computational science
05/1997;
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ABSTRACT: The software and protocols associated with information browsing systems are largely designed with static access points and wired networks in mind; HTTP and the Web are a case in point. Static hosts are connected to wired, high bandwidth networks, and are capable of transmitting and receiving large amounts of data without significant delays. As such, the size and format of the data files being received by the browser/client has never been a concern. However, this causes problems when information access is desired on mobile hosts, since data transmission over a wireless network is much slower than on a wired network. Mobile computers are also relatively resource-poor, compared to their desktop counterparts. This fact is ignored by HTTP servers, and large data files are transmitted to computers that cannot properly display them. Also, mobile computers operate in constantly changing network environments. It is possible for a mobile computer to become temporarily disconnected from a network when it changes base stations or goes out of range of a base station. A mobile host may also doze off to preserve battery power and thus be disconnected. The information browsing system and protocol associated with mobile computers should thus be able to tolerate the fault of temporary disconnection. The article addresses these problems in the context of Web browsing from a mobile host. It investigates an efficient model for browsing and describes the design of a smart Web browsing application which performs transactions based on the user's available resources and manages disconnection
Research Issues in Data Engineering, 1997. Proceedings. Seventh International Workshop on; 05/1997
