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148
The PERFECT Club Benchmarks: Effective Performance Evaluation of Supercomputers
 International Journal of Supercomputer Applications
, 1988
"... This report consists of two major portions. First is the presentation of a methodology for measuring the performance of supercomputers. This includes a set of thirteen Fortran programs that total well over 50,000 lines of source code. They represent applications in a number of areas of engineering a ..."
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Cited by 204 (3 self)
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This report consists of two major portions. First is the presentation of a methodology for measuring the performance of supercomputers. This includes a set of thirteen Fortran programs that total well over 50,000 lines of source code. They represent applications in a number of areas of engineering and scientific computing, and in many cases they represent codes that are currently used by a number of computational research and development groups. We also present the PERFECT Fortran standard which is simply a set of guidelines that allow portability to a number of types of machines. Furthermore, we present some performance measures and a methodology for recording and sharing results among a group of diverse users on different machines. The second portion of the paper presents some of the results we have obtained over the past year and a half. The results should not be used to compare machines, except in a very preliminary sense. Rather, the results are presented to show how the methodolo...
Theories for Mutagenicity: A Study in FirstOrder and FeatureBased Induction
 Artificial Intelligence
, 1996
"... A classic problem from chemistry is used to test a conjecture that in domains for which data are most naturally represented by graphs, theories constructed with Inductive Logic Programming (ILP) will significantly outperform those using simpler featurebased methods. One area that has long been asso ..."
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Cited by 152 (30 self)
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A classic problem from chemistry is used to test a conjecture that in domains for which data are most naturally represented by graphs, theories constructed with Inductive Logic Programming (ILP) will significantly outperform those using simpler featurebased methods. One area that has long been associated with graphbased or structural representation and reasoning is organic chemistry. In this field, we consider the problem of predicting the mutagenic activity of small molecules: a property that is related to carcinogenicity, and an important consideration in developing less hazardous drugs. By providing an ILP system with progressively more structural information concerning the molecules, we compare the predictive power of the logical theories constructed against benchmarks set by regression, neural, and treebased methods. 1 Introduction Constructing theories to explain observations occupies much of the creative hours of scientists and engineers. Programs from the field of Inductiv...
Cellular Texture Generation
, 1995
"... We propose an approach for modeling surface details such as scales, feathers, or thorns. These types of cellular textures require a representation with more detail than texturemapping but are inconvenient to model with handcrafted geometry. We generate ..."
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Cited by 68 (2 self)
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We propose an approach for modeling surface details such as scales, feathers, or thorns. These types of cellular textures require a representation with more detail than texturemapping but are inconvenient to model with handcrafted geometry. We generate
Convergence analysis of pseudotransient continuation
 SIAM J. Num. Anal
, 1998
"... Abstract. Pseudotransient continuation (Ψtc) is a wellknown and physically motivated technique for computation of steady state solutions of timedependent partial differential equations. Standard globalization strategies such as line search or trust region methods often stagnate at local minima. Ψ ..."
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Cited by 61 (25 self)
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Abstract. Pseudotransient continuation (Ψtc) is a wellknown and physically motivated technique for computation of steady state solutions of timedependent partial differential equations. Standard globalization strategies such as line search or trust region methods often stagnate at local minima. Ψtc succeeds in many of these cases by taking advantage of the underlying PDE structure of the problem. Though widely employed, the convergence of Ψtc is rarely discussed. In this paper we prove convergence for a generic form of Ψtc and illustrate it with two practical strategies.
A Versatile and Robust Model for Geometrically Complex Deformable Solids
, 2004
"... In this paper, we present a versatile and robust model for geometrically complex deformable solids. Our approach can be applied to deformable tetrahedral meshes and to deformable triangle meshes. The model considers elastic and plastic deformation. It handles a large variety of material properties r ..."
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Cited by 59 (15 self)
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In this paper, we present a versatile and robust model for geometrically complex deformable solids. Our approach can be applied to deformable tetrahedral meshes and to deformable triangle meshes. The model considers elastic and plastic deformation. It handles a large variety of material properties ranging from stiff to fluidlike behavior. Due to the computational efficiency of our approach, complex environments consisting of up to several thousand primitives can be simulated at interactive speed.
Projective methods for stiff differential equations: problems with gaps in their eigenvalue spectrum
 SIAM J. SCI. COMP
, 2001
"... We show that there exist classes of explicit numerical integration methods that can handle very stiff problems if the eigenvalues are separated into two clusters, one containing the "stiff", or fast components, and one containing the slow components. These methods have large average step sizes relat ..."
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Cited by 57 (16 self)
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We show that there exist classes of explicit numerical integration methods that can handle very stiff problems if the eigenvalues are separated into two clusters, one containing the "stiff", or fast components, and one containing the slow components. These methods have large average step sizes relative to the fast components. Conventional implicit methods involve the solution of nonlinear equations at each step, which for large problems requires significant communication between processors on a multiprocessor machine. For such problems the methods proposed here have significant potential for speed improvement.
Biochemical knowledge discovery using Inductive Logic Programming
, 1998
"... Machine Learning algorithms are being increasingly used for knowledge discovery tasks. Approaches can be broadly divided by distinguishing discovery of procedural from that of declarative knowledge. Client requirements determine which of these is appropriate. This paper discusses an experimental ..."
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Cited by 47 (6 self)
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Machine Learning algorithms are being increasingly used for knowledge discovery tasks. Approaches can be broadly divided by distinguishing discovery of procedural from that of declarative knowledge. Client requirements determine which of these is appropriate. This paper discusses an experimental application of machine learning in an area related to drug design. The bottleneck here is in finding appropriate constraints to reduce the large number of candidate molecules to be synthesisedand tested. Such constraints canbe viewed as declarative specifications of the structural elements necessary for high medicinal activity and low toxicity. The firstorder representation used within Inductive Logic Programming (ILP) provides an appropriate description language for such constraints. Within this application area knowledge accreditation requires not only a demonstration of predictive accuracy but also, and crucially, a certification of novel insight into the structural chemistry. Thi...
Qualitative and Quantitative Simulation: Bridging the Gap
 Artificial Intelligence
, 1997
"... Shortcomings of qualitative simulation and of quantitative simulation motivate combining them to do simulations exhibiting strengths of both. The resulting class of techniques is called semiquantitative simulation. One approach to semiquantitative simulation is to use numeric intervals to represe ..."
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Cited by 44 (1 self)
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Shortcomings of qualitative simulation and of quantitative simulation motivate combining them to do simulations exhibiting strengths of both. The resulting class of techniques is called semiquantitative simulation. One approach to semiquantitative simulation is to use numeric intervals to represent incomplete quantitative information. In this research we demonstrate semiquantitative simulation using intervals in an implemented semiquantitative simulator called Q3. Q3 progressively refines a qualitative simulation, providing increasingly specific quantitative predictions which can converge to a numerical simulation in the limit while retaining important correctness guarantees from qualitative and interval simulation techniques. Q3's simulations are based on a technique we call step size refinement. While a pure qualitative simulation has a very coarse step size, representing the state of a system trajectory at relatively few qualitatively distinct states, Q3 interpolates newly expl...
Method of Invariant Manifold for Chemical Kinetics
 Chemical Engineering Science
, 2002
"... In this paper, we review the construction of lowdimensional manifolds of reduced description for equations of chemical kinetics from the standpoint of the method of invariant manifold (MIM). MIM is based on a formulation of the condition of invariance as an equation, and its solution by Newton iter ..."
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Cited by 37 (21 self)
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In this paper, we review the construction of lowdimensional manifolds of reduced description for equations of chemical kinetics from the standpoint of the method of invariant manifold (MIM). MIM is based on a formulation of the condition of invariance as an equation, and its solution by Newton iterations. A review of existing alternative methods is extended by a thermodynamically consistent version of the method of intrinsic lowdimensional manifolds. A gridbased version of MIM is developed, and model extensions of lowdimensional dynamics are described. Generalizations to open systems are suggested. The set of methods covered makes it possible to effectively reduce description in chemical kinetics.
A MultiAlgorithm, MultiTimescale Method for Cell Simulation
, 2004
"... Motivation: Many important problems in cell biology require the dense nonlinear interactions between functional modules to be considered. The importance of computer simulation in understanding cellular processes is now widely accepted, and a variety of simulation algorithms useful for studying certa ..."
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Cited by 30 (3 self)
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Motivation: Many important problems in cell biology require the dense nonlinear interactions between functional modules to be considered. The importance of computer simulation in understanding cellular processes is now widely accepted, and a variety of simulation algorithms useful for studying certain subsystems have been designed. Many of these are already widely used, and a large number of models constructed on these existing formalisms are available. A significant computational challenge is how we can integrate such subcellular models running on different types of algorithms to construct higher order models. Results: A modular, objectoriented simulation metaalgorithm based on a discreteevent scheduler and Hermite polynomial interpolation has been developed and implemented. It is shown that this new method can efficiently handle many components driven by different algorithms and different timescales. The utility of this simulation framework is demonstrated further with a ‘composite ’ heatshock response model that combines the Gillespie–Gibson stochastic algorithm and deterministic differential equations. Dramatic improvements in performance were obtained without significant accuracy drawbacks. A multitimescale demonstration of coupled harmonic oscillators is also shown. Availability: An implementation of the method is available as part of ECell Simulation Environment Version 3 downloadable from