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In this paper we propose a new approach to parallel and distributed simulation of discrete event systems. Most parallel and distributed discrete event simulation algorithms are concerned with the simulation of one “large” discrete event system. In this case the computational intensity is due to the size and complexity of the simulated system. In(More)
We discuss the simulation of M replications of a uniformizable Markov chain simultaneously and in parallel (the so-called parallel replicated approach). Distributed implementation on a number of processors and parallel SIMD implementation on massively parallel computers are described. We investigate various ways of inducing correlation across replications(More)
Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of(More)
This paper introduces a new stochastic global optimization method targeting protein-protein docking problems, an important class of problems in computational structural biology. The method is based on finding general convex quadratic underestimators to the binding energy function that is funnel-like. Finding the optimum underestimator requires solving a(More)
We discuss a way of simulating M replications of a uniformizable Markov chain simultaneously and in parallel (the so-called parallel replication approach), Simulation is performed to estimate the expectation of some cumulative reward over a finite deterministic time horizon. Distributed implementation on a number of processors and parallel SIMD(More)
The technique of control variates requires that the user identify a set of variates that are correlated with the estimation variable and whose means are known to the user. We relax the known mean requirement and instead assume the means are to be estimated. We argue that this strategy can be beneficial in parametric studies, analyze the properties of(More)
The purpose of this paper is twofold. First, it serves to describe a new strategy, called Structured Database Monte Carlo (SDMC), for efficient Monte Carlo simulation. Its second aim is to show how this approach can be used for efficient pricing of path-dependent options via simulation. We use efficient simulation of a sample of path-dependent options to(More)
Our work is motivated by energy minimization in the space of rigid affine transformations of macromolecules, an essential step in computational protein-protein docking. We introduce a novel representation of rigid body motion that leads to a natural formulation of the energy minimization problem as an optimization on the [Formula: see text] manifold, rather(More)