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Efficient computational approaches for parallel stochastic simulation on supercomputers. / Marchenko, Mikhail A.

Mathematical Research Summaries. Vol. 2 Nova Science Publishers, Inc., 2017.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

Harvard

Marchenko, MA 2017, Efficient computational approaches for parallel stochastic simulation on supercomputers. in Mathematical Research Summaries. vol. 2, Nova Science Publishers, Inc.

APA

Marchenko, M. A. (2017). Efficient computational approaches for parallel stochastic simulation on supercomputers. In Mathematical Research Summaries (Vol. 2). Nova Science Publishers, Inc..

Vancouver

Marchenko MA. Efficient computational approaches for parallel stochastic simulation on supercomputers. In Mathematical Research Summaries. Vol. 2. Nova Science Publishers, Inc. 2017

Author

Marchenko, Mikhail A. / Efficient computational approaches for parallel stochastic simulation on supercomputers. Mathematical Research Summaries. Vol. 2 Nova Science Publishers, Inc., 2017.

BibTeX

@inbook{a7c0decdde4548b4baf111eb56a5024f,
title = "Efficient computational approaches for parallel stochastic simulation on supercomputers",
abstract = "The Monte Carlo method (or the method of stochastic simulation) is often used to solve real-life problems. But the main issue of the Monte Carlo simulation is usually the value of its computational cost. Nevertheless, using parallel high performance computers it is possible to get results of simulation in a reasonable time. A question is how to develop justified and effective parallel algorithms and programs. In this chapter, we provide some computational approaches for effective parallel stochastic simulation. As an example, we apply these approaches to study stochastic evolution of electron avalanches in gases.",
author = "Marchenko, {Mikhail A.}",
year = "2017",
month = jan,
day = "1",
language = "English",
isbn = "9781536120226",
volume = "2",
booktitle = "Mathematical Research Summaries",
publisher = "Nova Science Publishers, Inc.",

}

RIS

TY - CHAP

T1 - Efficient computational approaches for parallel stochastic simulation on supercomputers

AU - Marchenko, Mikhail A.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - The Monte Carlo method (or the method of stochastic simulation) is often used to solve real-life problems. But the main issue of the Monte Carlo simulation is usually the value of its computational cost. Nevertheless, using parallel high performance computers it is possible to get results of simulation in a reasonable time. A question is how to develop justified and effective parallel algorithms and programs. In this chapter, we provide some computational approaches for effective parallel stochastic simulation. As an example, we apply these approaches to study stochastic evolution of electron avalanches in gases.

AB - The Monte Carlo method (or the method of stochastic simulation) is often used to solve real-life problems. But the main issue of the Monte Carlo simulation is usually the value of its computational cost. Nevertheless, using parallel high performance computers it is possible to get results of simulation in a reasonable time. A question is how to develop justified and effective parallel algorithms and programs. In this chapter, we provide some computational approaches for effective parallel stochastic simulation. As an example, we apply these approaches to study stochastic evolution of electron avalanches in gases.

UR - http://www.scopus.com/inward/record.url?scp=85034995650&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:85034995650

SN - 9781536120226

VL - 2

BT - Mathematical Research Summaries

PB - Nova Science Publishers, Inc.

ER -

ID: 10066096