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 333 articles , 1 standard article )

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  1. Adjé, Assalé: Quadratic maximization of reachable values of affine systems with diagonalizable matrix (2021)
  2. Alessandro Cheli: Metatheory.jl: Fast and Elegant Algebraic Computation in Julia with Extensible Equality Saturation (2021) not zbMATH
  3. Ali Bagci: JRAF: A Julia Package for Computation of the Relativistic Molecular Auxiliary Functions (2021) arXiv
  4. Anton Plietzsch, Raphael Kogler, Sabine Auer, Julia Merino, Asier Gil-de-Muro, Jan Liße, Christina Vogel, Frank Hellmann: PowerDynamics.jl - An experimentally validated open-source package for the dynamical analysis of power grids (2021) arXiv
  5. Bertsimas, Dimitris; Dunn, Jack; Wang, Yuchen: Near-optimal nonlinear regression trees (2021)
  6. Bertsimas, Dimitris; Mundru, Nishanth: Sparse convex regression (2021)
  7. Braun, M.: Comparison of densities obtained with competing density functional molecular codes (2021)
  8. Brown et al.: libCEED: Fast algebra for high-order element-based discretizations (2021) not zbMATH
  9. Calandra, Henri; Gratton, Serge; Riccietti, Elisa; Vasseur, Xavier: On high-order multilevel optimization strategies (2021)
  10. Colera, Manuel; Carpio, Jaime; Bermejo, Rodolfo: A nearly-conservative, high-order, forward Lagrange-Galerkin method for the resolution of scalar hyperbolic conservation laws (2021)
  11. Dandurand, Brian C.; Kim, Kibaek; Leyffer, Sven: A bilevel approach for identifying the worst contingencies for nonconvex alternating current power systems (2021)
  12. Ding Ma, Dominique Orban, Michael A. Saunders: A Julia implementation of Algorithm NCL for constrained optimization (2021) arXiv
  13. Dostert, Maria; de Laat, David; Moustrou, Philippe: Exact semidefinite programming bounds for packing problems (2021)
  14. Dowson, Oscar; Kapelevich, Lea: SDDP.jl: a Julia package for stochastic dual dynamic programming (2021)
  15. Dragomir, Radu-Alexandru; d’Aspremont, Alexandre; Bolte, Jérôme: Quartic first-order methods for low-rank minimization (2021)
  16. Eder, Christian; Hofmann, Tommy: Efficient Gröbner bases computation over principal ideal rings (2021)
  17. Francis Banville; Steve Vissault; Timothée Poisot: Mangal.jl and EcologicalNetworks.jl: Two complementary packages for analyzing ecological networks in Julia (2021) not zbMATH
  18. Gabriel Dansereau; Timothée Poisot: SimpleSDMLayers.jl and GBIF.jl: A Framework for Species Distribution Modeling in Julia (2021) not zbMATH
  19. Gael Forget: IndividualDisplacements.jl: a Julia package to simulate and study particle displacements within the climate system (2021) not zbMATH
  20. García, Hernán; Hernández, Camilo; Junca, Mauricio; Velasco, Mauricio: Approximate super-resolution of positive measures in all dimensions (2021)

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