Skip to main content
Log in

MathPartner computer algebra

  • Published:
Programming and Computer Software Aims and scope Submit manuscript

Abstract

In this paper, we describe general characteristics of the MathPartner computer algebra system (CAS) and Mathpar programming language thereof. MathPartner can be used for scientific and engineering calculations, as well as in high schools and universities. It allows one to carry out both simple calculations (acting as a scientific calculator) and complex calculations with large-scale mathematical objects. Mathpar is a procedural language; it supports a large number of elementary and special functions, as well as matrix and polynomial operators. This service allows one to build function images and animate them. MathPartner also makes it possible to solve some symbolic computation problems on supercomputers with distributed memory. We highlight main differences of MathPartner from other CASs and describe the Mathpar language along with the user service provided.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Hooft, G. and Veltman, M.J.G., Elucidation of the quantum structure of electroweak interactions, Usp. Fiz. Nauk, 2000, vol. 170, no. 11, pp. 118–1224.

    Google Scholar 

  2. Blumlein, J., Broadhurst, D.J., and Vermaseren, J.A.M., The multiple zeta value data mine, Comput. Phys. Commun., 2010, vol. 181, pp. 582–625.

    Article  MathSciNet  MATH  Google Scholar 

  3. Computer Algebra: Symbolic and Algebraic Computation, Buchberger, B., Collins, G.E., and Loos, R., Eds., New York: Springer, 1983, 2nd ed.

  4. Gathen, J. von zur and Gerhard, J., Modern Computer Algebra, Cambridge Univ. Press, 2013.

    Book  MATH  Google Scholar 

  5. Malaschonok, G.I., Way to parallel symbolic computations, Proc. Int. Conf. Cloud Computing, Education, Research, Development, Moscow, 2011. www.unicluster. ru/conf/2011/docs.

    Google Scholar 

  6. Publications of MathPartner Project. http://mathpar.com/downloads/publications2015.pdf.

  7. Malaschonok, G.I., Language Guide “Mathpar”, Tambov: Publishing House of TSU, 2013.

    Google Scholar 

  8. Malashonok, G.I., On the project of parallel computer algebra, Vestn. Tambov. Univ. Ser. Estestv. Tekh. Nauki, 2009, vol. 14, no. 4, pp. 744–748.

    Google Scholar 

  9. Malashonok, G.I., Project of parallel computer algebra, Vestn. Tambov. Univ. Ser. Estestv. Tekh. Nauki, 2010, vol. 15, no. 6, pp. 1724–1729.

    Google Scholar 

  10. Malaschonok, G.I., Pereslavtseva, O.N., and Ivashov, D.S., Parallel Symbolic Computation: Supercomputer Technologies in Science, Education, and Industry, Sadovnichiy, V.A., Savina, G.I., Voevodin, V.V., Eds, Moscow State Univ. Press, 2013.

  11. Kireev, S.A. and Malaschonok, G.I., Tropical computing with the web service MathPartner, Tambov Univ. Rep. Ser. Nat. Tech. Sci., 2014, vol. 19, no. 2, pp. 539–550.

    Google Scholar 

  12. Malaschonok, G.I., Valeev, Yu.D., and Lapaev, A.O., On the choice of multiplication algorithm for polynomials and polynomial matrices, Zap. Nauchn. Semin. POMI, 2009, vol. 373, pp. 157–188.

    Google Scholar 

  13. Malaschonok, G.I., Effective matrix methods in commutative domains, Formal Power Series and Algebraic Combinatorics, Krob, D., Mikhalev, A.A., and Mikhalev, A.V., Eds., Berlin: Springer, 2000, pp. 506–517.

  14. Akritas, A.G. and Malaschonok, G.I., Computations in modules over commutative domain, Proc. Int. Workshop on Computer Algebra in Scientific Computing, Berlin: Springer, 2007, pp. 11–23.

    Chapter  Google Scholar 

  15. Malaschonok, G.I., Generalized Bruhat decomposition in commutative domains, Proc. Int. Workshop on Computer Algebra in Scientific Computing, Berlin: Springer, 2013, pp. 231–242.

    Chapter  Google Scholar 

  16. Malaschonok, G. and Scherbinin, A., Triangular decomposition of matrices in a domain, Proc. Int. Workshop on Computer Algebra in Scientific Computing, Switzerland: Springer, 2015, pp. 290–304.

    Google Scholar 

  17. Malaschonok, N.A., Parallel Laplace method with assured accuracy by symbolic computations, Proc. Int. Workshop on Computer Algebra in Scientific Computing, Berlin: Springer, 2006, pp. 251–260.

    Chapter  Google Scholar 

  18. Malaschonok, N.A., An algorithm for symbolic solving of differential equations and estimation of accuracy, Proc. Int. Workshop on Computer Algebra in Scientific Computing, Berlin: Springer, 2009, pp. 213–225.

    Chapter  Google Scholar 

  19. Malashonok, N.A. and Rybakov, M.A., Symbolic–numerical solution of systems of linear ordinary differential equations with required accuracy, Program. Comput. Software, 2013, vol. 39, no. 3, pp. 150–157.

    Article  MathSciNet  MATH  Google Scholar 

  20. Malaschonok, G.I. and Valeev, Y.D., Recursive parallelization of symbolic-number algorithms, Tambov Univ. Rep. Ser. Nat. Tech. Sci., 2006, vol. 11, no. 4, pp. 536–549.

    Google Scholar 

  21. Malaschonok, G.I., Avetisan, A.I., Valeev, Yu.D., and Zuev, M.S., Parallel algorithms of computer algebra, Proc. Inst. Syst. Program. Rus. Acad. Sci., Ivannikov, V.P., Ed., Moscow: TSP RAS, 2004, vol. 8, no. 2, pp. 169–180.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G. I. Malaschonok.

Additional information

Original Russian Text © G.I. Malaschonok, 2017, published in Programmirovanie, 2017, Vol. 43, No. 2.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malaschonok, G.I. MathPartner computer algebra. Program Comput Soft 43, 112–118 (2017). https://doi.org/10.1134/S0361768817020086

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0361768817020086

Navigation