SUNDIALS

SUNDIALS was implemented with the goal of providing robust time integrators and nonlinear solvers that can easily be incorporated into existing simulation codes. The primary design goals were to require minimal information from the user, allow users to easily supply their own data structures underneath the solvers, and allow for easy incorporation of user-supplied linear solvers and preconditioners. The main numerical operations performed in these codes are operations on data vectors, and the codes have been written in terms of interfaces to these vector operations. The result of this design is that users can relatively easily provide their own data structures to the solvers by telling the solver about their structures and providing the required operations on them. The codes also come with default vector structures with pre-defined operation implementations for both serial and distributed memory parallel environments in case a user prefers not to supply their own structures. In addition, all parallelism is contained within specific vector operations (norms, dot products, etc.) No other operations within the solvers require knowledge of parallelism. Thus, using a solver in parallel consists of using a parallel vector implementation, either the one provided with SUNDIALS, or the user’s own parallel vector structure, underneath the solver. Hence, we do not make a distinction between parallel and serial versions of the codes.


References in zbMATH (referenced in 132 articles , 1 standard article )

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  1. Constantinescu, Emil M.: Generalizing global error estimation for ordinary differential equations by using coupled time-stepping methods (2018)
  2. Carsten Burstedde, Jose A. Fonseca, Stefan Kollet: Enhancing speed and scalability of the ParFlow simulation code (2017) arXiv
  3. McKenzie, Ross; Pryce, John: Structural analysis based dummy derivative selection for differential algebraic equations (2017)
  4. Nama, Nitesh; Huang, Tony Jun; Costanzo, Francesco: Acoustic streaming: an arbitrary Lagrangian-Eulerian perspective (2017)
  5. Barajas-Solano, David A.; Tartakovsky, Daniel M.: Stochastic collocation methods for nonlinear parabolic equations with random coefficients (2016)
  6. Blom, David S.; Birken, Philipp; Bijl, Hester; Kessels, Fleur; Meister, Andreas; van Zuijlen, Alexander H.: A comparison of Rosenbrock and ESDIRK methods combined with iterative solvers for unsteady compressible flows (2016)
  7. Boiger, R.; Hasenauer, J.; Hroß, S.; Kaltenbacher, B.: Integration based profile likelihood calculation for PDE constrained parameter estimation problems (2016)
  8. Hansen, M.A.; Sutherland, J.C.: Pseudotransient continuation for combustion simulation with detailed reaction mechanisms (2016)
  9. Harwood, Stuart M.; Barton, Paul I.: Efficient polyhedral enclosures for the reachable set of nonlinear control systems (2016)
  10. Linaro, Daniele; Storace, Marco: BAL: a library for the \itbrute-force analysis of dynamical systems (2016)
  11. Loffeld, John; Woodward, Carol S.: Considerations on the implementation and use of Anderson acceleration on distributed memory and GPU-based parallel computers (2016)
  12. Morii, Youhi; Terashima, Hiroshi; Koshi, Mitsuo; Shimizu, Taro; Shima, Eiji: ERENA: a fast and robust Jacobian-free integration method for ordinary differential equations of chemical kinetics (2016)
  13. Ong, Benjamin W.; Haynes, Ronald D.; Ladd, Kyle: Algorithm 965: RIDC methods: a family of parallel time integrators (2016)
  14. Skote, Martin; Ibrahim, Imran Halimi: Utilizing the L-PSJA for controlling cylindrical wake flow (2016)
  15. Tasora, Alessandro; Serban, Radu; Mazhar, Hammad; Pazouki, Arman; Melanz, Daniel; Fleischmann, Jonathan; Taylor, Michael; Sugiyama, Hiroyuki; Negrut, Dan: Chrono: an open source multi-physics dynamics engine (2016)
  16. Birken, Philipp: Termination criteria for inexact fixed-point schemes. (2015)
  17. Cheng, Yingda; Christlieb, Andrew J.; Zhong, Xinghui: Numerical study of the two-species Vlasov-Ampère system: energy-conserving schemes and the current-driven ion-acoustic instability (2015)
  18. Dargaville, S.; Farrell, T.W.: A least squares based finite volume method for the Cahn-Hilliard and Cahn-Hilliard-reaction equations (2015)
  19. Elsheikh, Atiyah: An equation-based algorithmic differentiation technique for differential algebraic equations (2015)
  20. Gul, R.; Bernhard, S.: Parametric uncertainty and global sensitivity analysis in a model of the carotid bifurcation: identification and ranking of most sensitive model parameters (2015)

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