AbstractThe paper deals with the performance analysis of three Monte Carlo algorithms for some models of computer architectures. To estimate the performance and the speedup of these algorithms, we introduce a special modification of the criterion for the time required to achieve a preset probable error and consider a serial (von Neumann) architecture, a pipeline architecture, and two MIMD (Multiple Instruction stream, Multiple Data stream) parallel architectures. An approach to constructing Monte Carlo vector algorithms to be efficiently run on pipeline computers has also been considered
(parallel computers and algorithms too). In this sense the paper is devoted to a complex performance...
A Monte Carlo simulation of a simple statistical physics model is decomposed onto a multi-processor ...
The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each indi...
AbstractThe paper deals with the performance analysis of three Monte Carlo algorithms for some model...
Abstract. We argue that Monte Carlo algorithms are ideally suited to parallel computing, and that “p...
We argue that Monte Carlo algorithms are ideally suited to parallel computing, and that “parallel Mo...
The increasing availability of multi-core and multiprocessor architectures provides new opportunitie...
In recent years, parallel processing has become widely available to researchers. It can be applied i...
The conventional particle transport Monte Carlo algorithm is ill suited for modem vector supercomput...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
The efficient parallel implementation of a 3-D Monte Carlo device simulator is described. The parall...
International audienceMonte Carlo methods are a wide range of computational algorithms which depend ...
Typically, parallel algorithms are developed to leverage the processing power of multiple processors...
Emerging many-core computer architectures provide an incentive for computational methods to exhibit ...
Markov Chain Monte Carlo (MCMC) is a family of stochastic algorithms which are used to draw random s...
(parallel computers and algorithms too). In this sense the paper is devoted to a complex performance...
A Monte Carlo simulation of a simple statistical physics model is decomposed onto a multi-processor ...
The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each indi...
AbstractThe paper deals with the performance analysis of three Monte Carlo algorithms for some model...
Abstract. We argue that Monte Carlo algorithms are ideally suited to parallel computing, and that “p...
We argue that Monte Carlo algorithms are ideally suited to parallel computing, and that “parallel Mo...
The increasing availability of multi-core and multiprocessor architectures provides new opportunitie...
In recent years, parallel processing has become widely available to researchers. It can be applied i...
The conventional particle transport Monte Carlo algorithm is ill suited for modem vector supercomput...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
The efficient parallel implementation of a 3-D Monte Carlo device simulator is described. The parall...
International audienceMonte Carlo methods are a wide range of computational algorithms which depend ...
Typically, parallel algorithms are developed to leverage the processing power of multiple processors...
Emerging many-core computer architectures provide an incentive for computational methods to exhibit ...
Markov Chain Monte Carlo (MCMC) is a family of stochastic algorithms which are used to draw random s...
(parallel computers and algorithms too). In this sense the paper is devoted to a complex performance...
A Monte Carlo simulation of a simple statistical physics model is decomposed onto a multi-processor ...
The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each indi...