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Symbolic Implementation of Multivector Algebra in Julia Language
Gevorkyan M.N., Kulyabov D.S., Korolkova A.V., Demidova A.V., Velieva T.R.
in the Julia language. It mixes computer algebra calculations with numerical calculations for better
ОБЗОР БИБЛИОТЕКИ DIFFERENTIALEQUATIONS.JL ДЛЯ РЕШЕНИЯ ДИФФЕРЕНЦИАЛЬНЫХ УРАВНЕНИЙ ЧИСЛЕННЫМИ МЕТОДАМИ
Комаров П.О.
equations by numerical methods - the DifferentialEquations.jl library, created on the basis of the Julia
Statistically significant comparative performance testing of julia and fortran languages in case of runge–kutta methods
Gevorkyan M.N., Korolkova A.V., Kulyabov D.S., Lovetskiy K.P.
and Julia languages. We use the technique described in technical report by Tomas Kalibera and Richard E
Solving the eikonal equation by the FSM method in Julia language
Stepa C.A., Fedorov A.V., Gevorkyan M.N., Korolkova A.V., Kulyabov D.S.
for constructing beams and fronts. The implementation of the FSM method in the Eikonal library of the Julia
Factors of economic innovative development: Cross-country evidence
Natalia L., Julia V.
complex of three components: R&D sphere, degree of real sector development, institutional environment
Land use influence on 3-D distribution of soil microbiological activity in forest-steppe zone of Central Russia
Vasenev Viacheslav, Ryzhkov Oleg, Lakeev Pavel, Tembo Alan, Sarzhanov Dmirty, Sotnikova Julia, Valentini Riccardo
Land use influence on 3-D distribution of soil microbiological activity in forest-steppe zone
Social networking as an advertising tool in Russia and abroad
Ageeva, Y. A., Zavyalova, Z. S., Giniyatova, E. V., Zavyalova, M. P., Deakin, Ann K., Lokotosh, Y. V., Kondratyeva, I. V.
Statistically significant performance testing of Julia scientific programming language
Gevorkyan M.N., Demidova A.V., Korolkova A.V., Kulyabov D.S.
In this article, we compare the support for SIMD instructions for Julia and Fortran. The comparison
Issues in the software implementation of stochastic numerical Runge–Kutta
Gevorkyan M.N., Demidova A.V., Korolkova A.V., Kulyabov D.S.
some implementation details, such as program languages (Python, Julia) and libraries (Jinja2, Numpy
Automatic code generation for stochastic Runge-Kutta methods
Gevorkyan M.N., Demidova A.V., Korolkova A.V., Kulyabov D.S.
, and the code generation algorithms for numerical schemes are described. Python and Julia languages are used

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