Julia

Julia: A fast dynamic language for technical computing. Dynamic languages have become popular for scientific computing. They are generally considered highly productive, but lacking in performance. This paper presents Julia, a new dynamic language for technical computing, designed for performance from the beginning by adapting and extending modern programming language techniques. A design based on generic functions and a rich type system simultaneously enables an expressive programming model and successful type inference, leading to good performance for a wide range of programs. This makes it possible for much of the Julia library to be written in Julia itself, while also incorporating best-of-breed C and Fortran libraries.


References in zbMATH (referenced in 190 articles , 1 standard article )

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  1. Andy Nowacki: SeisModels.jl: A Julia package for models of the Earth’s interior (2020) not zbMATH
  2. Cazeaux, Paul; Luskin, Mitchell; Massatt, Daniel: Energy minimization of two dimensional incommensurate heterostructures (2020)
  3. Chirre, Andrés; Gonçalves, Felipe; de Laat, David: Pair correlation estimates for the zeros of the zeta function via semidefinite programming (2020)
  4. de Laat, David: Moment methods in energy minimization: new bounds for Riesz minimal energy problems (2020)
  5. Downward, Anthony; Dowson, Oscar; Baucke, Regan: Stochastic dual dynamic programming with stagewise-dependent objective uncertainty (2020)
  6. Duarte, Victor; Duarte, Diogo; Fonseca, Julia; Montecinos, Alexis: Benchmarking machine-learning software and hardware for quantitative economics (2020)
  7. Eliasof, Moshe; Sharf, Andrei; Treister, Eran: Multimodal 3D shape reconstruction under calibration uncertainty using parametric level set methods (2020)
  8. Haller, George; Karrasch, Daniel; Kogelbauer, Florian: Barriers to the transport of diffusive scalars in compressible flows (2020)
  9. Hicken, Jason E.: Entropy-stable, high-order summation-by-parts discretizations without interface penalties (2020)
  10. Hudson, Thomas; Legoll, Frédéric; Lelièvre, Tony: Stochastic homogenization of a scalar viscoelastic model exhibiting stress-strain hysteresis (2020)
  11. Justin Angevaare, Zeny Feng, Rob Deardon: Infectious Disease Transmission Network Modelling with Julia (2020) arXiv
  12. Koutsoumpelias, Alexandros Grosdos; Wageringel, Markus: Moment ideals of local Dirac mixtures (2020)
  13. Legat, Benoît; Tabuada, Paulo; Jungers, Raphaël M.: Sum-of-squares methods for controlled invariant sets with applications to model-predictive control (2020)
  14. Mark van der Loo: Monitoring data in R with the lumberjack package (2020) arXiv
  15. Mikhlin, Yuri; Onizhuk, Anton; Awrejcewicz, Jan: Resonance behavior of the system with a limited power supply having the Mises girder as absorber (2020)
  16. Mossaiby, Farshid; Shojaei, Arman; Boroomand, Bijan; Zaccariotto, Mirco; Galvanetto, Ugo: Local Dirichlet-type absorbing boundary conditions for transient elastic wave propagation problems (2020)
  17. Oliveira, José V. jun.; Cribari-Neto, Francisco; Nobre, Juvêncio S.: Influence diagnostics and model validation for the generalized extreme-value nonlinear regression model (2020)
  18. Poirion, Pierre-Louis; Toubaline, Sonia; D’Ambrosio, Claudia; Liberti, Leo: Algorithms and applications for a class of bilevel MILPs (2020)
  19. Tarek, Mohamed; Ray, Tapabrata: Adaptive continuation solid isotropic material with penalization for volume constrained compliance minimization (2020)
  20. Vavasis, Stephen A.; Papoulia, Katerina D.; Hirmand, M. Reza: Second-order cone interior-point method for quasistatic and moderate dynamic cohesive fracture (2020)

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Further publications can be found at: http://julialang.org/publications/