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On the BorowskyGafni simulation algorithm, brief announcement
 Proceedings of the 15th ACM Symposium on Principles of Distributed Computing
, 1996
"... Consider a read/write asynchronous shared memory system. In [1], Borowsky and G&i describe an algorithm that allows a set of f + 1 processes, any ~ of which may exhibit stopping failures, to “simulate ” a larger number n of processes, also with at most ~ failures. This simulation algorithm is us ..."
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for this to happen, it must be clear exactly what the simulation algorithm is, and what it guarantees. We began this research with the modest aim of stating and proving precise correctness guarantees for the BorowskyGafni simulation algorithm, using the 1/0 automaton model (e.g. [2] ) and standard proof techniques
On the BorowskyGafni simulation algorithm (extended abstract
 In Proceedings of the FourthIsraeli Symposium on Theory of Computing and Systems
, 1996
"... The first precise description of a version of the BorowskyGafni faulttolerant simulation algorithm is given, along with a careful description of what it accomplishes and a proof of correctness. The algorithm implements a notion of faulttolerant reducibility between decision problems. This notion ..."
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The first precise description of a version of the BorowskyGafni faulttolerant simulation algorithm is given, along with a careful description of what it accomplishes and a proof of correctness. The algorithm implements a notion of faulttolerant reducibility between decision problems. This notion
Understanding the Set Consensus Partial Order Using the BorowskyGafni Simulation (Extended Abstract)
 In Distributed Algorithms, 10th International Workshop, volume 1151 of LNCS
, 1996
"... ) Soma Chaudhuri and Paul Reiners Iowa State University, Ames, IA 50011, USA Abstract. We present a complete characterization of the Set Consensus Partial Order, a refinement of the Consensus Hierarchy of Herlihy. We define the (n; k)set consensus problem as the kset consensus problem for n proce ..."
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Cited by 11 (0 self)
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consensus objects. The model we consider is the asynchronous shared memory model. To prove our results, we use the BorowskyGafni Simulation technique, a powerful tool which has been used to prove several impossibility results about shared memory algorithms. Lynch and Rajsbaum gave a formal description
A Fast Algorithm for Particle Simulations
, 1987
"... this paper to the case where the potential (or force) at a point is a sum of pairwise An algorithm is presented for the rapid evaluation of the potential and force fields in systems involving large numbers of particles interactions. More specifically, we consider potentials of whose interactions a ..."
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Cited by 1145 (19 self)
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this paper to the case where the potential (or force) at a point is a sum of pairwise An algorithm is presented for the rapid evaluation of the potential and force fields in systems involving large numbers of particles interactions. More specifically, we consider potentials of whose interactions
Randomized Algorithms
, 1995
"... Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available, or the simp ..."
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Cited by 2210 (37 self)
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Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
Qualitative Simulation
 Artificial Intelligence
, 2001
"... Qualitative simulation predicts the set of possible behaviors... ..."
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Cited by 513 (31 self)
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Qualitative simulation predicts the set of possible behaviors...
The Viterbi algorithm
 Proceedings of the IEEE
, 1973
"... vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A ..."
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Cited by 985 (3 self)
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vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A799A804, 1964. [9] T. C. Mo, “Theory of electrodynamics in media in noninertial frames and applications, ” J. Math. Phys., vol. 11, pp. 25892610, 1970.
Simulating Physics with Computers
 SIAM Journal on Computing
, 1982
"... A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. ..."
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Cited by 601 (1 self)
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A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration
Discrete Choice Methods with Simulation
, 2002
"... This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logi ..."
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Cited by 1277 (20 self)
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moments, and the method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as antithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis– Hastings algorithm and its variant Gibbs
Results 1  10
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