Analysis of Means of Simulation Modeling of Parallel Algorithms

  • D. V. Weins
  • B. M. Glinskiy
  • I. G. Chernykh
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 965)


At the ICMMG, an integral approach to creating algorithms and software for exaflop computers is being developed. Within the framework of this approach, the study touches upon the scalability of parallel algorithms by using the method of simulation modeling with the help of an AGNES modeling system. Based on a JADE agent platform, AGNES has a number of essential shortcomings in the modeling of hundreds of thousands and millions of independent computing cores, which is why it is necessary to find an alternative tool for simulation modeling.

Various instruments of agent and actor modeling were studied in the application to modeling of millions of computing cores, such as QP/C++, CAF, SObjectizer, Erlang, and Akka. As a result, on the basis of ease of implementation, scalability, and fault tolerance, the Erlang functional programming language was chosen, which originally was developed to create telephony programs. Today Erlang is meant for developing distribution computing systems and includes means for generating parallel lightweight processes and their interaction through exchange of asynchronous messages in accordance with an actor model.

Testing the performance of this tool in the implementation of parallel algorithms on future exaflop supercomputers is carried out by investigating the scalability of the statistical simulation algorithm by the Monte Carlo methods on a million computing cores. The results obtained in this paper are compared with the results obtained earlier by using AGNES.


Simulation modeling Actor model Scalability Erlang 



This work was supported by the Russian Foundation for Basic Research (Grants No. 16-07-00434, 18-37-00279, and 18-07-00757).

The Siberian Supercomputer Center of the Siberian Branch of the Russian Academy of Sciences (SB RAS) is gratefully acknowledged for providing supercomputer facilities.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The Institute of Computational Mathematics and Mathematical Geophysics SB RASNovosibirskRussia

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