PLUTO is a freely-distributed software for the numerical solution of mixed hyperbolic/parabolic systems of partial differential equations (conservation laws) targeting high Mach number flows in astrophysical fluid dynamics. The code is designed with a modular and flexible structure whereby different numerical algorithms can be separately combined to solve systems of conservation laws using the finite volume or finite difference approach based on Godunov-type schemes. Equations are discretized and solved on a structured mesh that can be either static or adaptive. For the latter functionality, PLUTO relies on the Chombo library which provides a distributed infrastructure for parallel calculations over block-structured, adaptively refined grids. The static grid version of PLUTO is entirely written in the C programming language while the adaptive mesh refinement (AMR) interface requires also C++ and Fortran. PLUTO is a highly portable software and can run from a single workstation up to several thousands processors using the Message Passing Interface (MPI) to achieve highly scalable parallel performance. The software is developed at the Dipartimento di Fisica, Torino University in a joint collaboration with INAF, Osservatorio Astronomico di Torino and the SCAI Department of CINECA.

References in zbMATH (referenced in 34 articles )

Showing results 1 to 20 of 34.
Sorted by year (citations)

1 2 next

  1. Duan, Junming; Tang, Huazhong: High-order accurate entropy stable adaptive moving mesh finite difference schemes for special relativistic (magneto)hydrodynamics (2022)
  2. Chernykh, Igor; Kulikov, Igor; Tutukov, Alexander: Hydrogen-helium chemical and nuclear galaxy collision: hydrodynamic simulations on AVX-512 supercomputers (2021)
  3. Duan, Junming; Tang, Huazhong: Entropy stable adaptive moving mesh schemes for 2D and 3D special relativistic hydrodynamics (2021)
  4. Heidt, Liam; Flaig, M.; Thornber, B.: The effect of initial amplitude and convergence ratio on instability development and deposited fluctuating kinetic energy in the single-mode Richtmyer-Meshkov instability in spherical implosions (2021)
  5. Keppens, Rony; Teunissen, Jannis; Xia, Chun; Porth, Oliver: \textttMPI-AMRVAC: a parallel, grid-adaptive PDE toolkit (2021)
  6. Minoshima, Takashi; Miyoshi, Takahiro: A low-dissipation HLLD approximate Riemann solver for a very wide range of Mach numbers (2021)
  7. Rueda-Ramírez, Andrés M.; Ferrer, Esteban; Kopriva, David A.; Rubio, Gonzalo; Valero, Eusebio: A statically condensed discontinuous Galerkin spectral element method on Gauss-Lobatto nodes for the compressible Navier-Stokes equations (2021)
  8. James M. Stone, Kengo Tomida, Christopher J. White, Kyle G. Felker: The Athena++ Adaptive Mesh Refinement Framework: Design and Magnetohydrodynamic Solvers (2020) arXiv
  9. Kitamura, Keiichi; Mamashita, Tomohiro; Ryu, Dongsu: SLAU2 applied to two-dimensional, ideal magnetohydrodynamics simulations (2020)
  10. Fujimoto, Takeshi R.; Kawasaki, Taro; Kitamura, Keiichi: Canny-edge-detection/Rankine-Hugoniot-conditions unified shock sensor for inviscid and viscous flows (2019)
  11. Kulikov, I. M.; Chernykh, I. G.; Glinskiy, B. M.; Protasov, V. A.: An efficient optimization of Hll method for the second generation of Intel Xeon Phi processor (2018)
  12. Kulikov, I. M.; Chernykh, I. G.; Tutukov, A. V.: A new parallel Intel Xeon Phi hydrodynamics code for massively parallel supercomputers (2018)
  13. Kidder, Lawrence E.; Field, Scott E.; Foucart, Francois; Schnetter, Erik; Teukolsky, Saul A.; Bohn, Andy; Deppe, Nils; Diener, Peter; Hébert, François; Lippuner, Jonas; Miller, Jonah; Ott, Christian D.; Scheel, Mark A.; Vincent, Trevor: SpECTRE: A task-based discontinuous Galerkin code for relativistic astrophysics (2017)
  14. Lee, Dongwook; Faller, Hugues; Reyes, Adam: The piecewise cubic method (PCM) for computational fluid dynamics (2017)
  15. Mocz, Philip: Correspondence between constrained transport and vector potential methods for magnetohydrodynamics (2017)
  16. Anshu Dubey, Ann Almgren, John Bell, Martin Berzins, Steve Brandt, Greg Bryan, Phillip Colella, Daniel Graves, Michael Lijewski, Frank Loffler, Brian O’Shea, Erik Schnetter, Brian Van Straalen, Klaus Weide: A Survey of High Level Frameworks in Block-Structured Adaptive Mesh Refinement Packages (2016) arXiv
  17. Chen, Yuxi; Tóth, Gábor; Gombosi, Tamas I.: A fifth-order finite difference scheme for hyperbolic equations on block-adaptive curvilinear grids (2016)
  18. Wołoszkiewicz, Piotr; Murawski, Krzysztof; Musielak, Zdzisław E.; Mignone, Andrea: Numerical simulations of Alfvén waves in the solar atmosphere with the PLUTO code (2014)
  19. Tordella, D.; Iovieno, M.; Massaglia, S.; Mignone, A.: Large-eddy simulation of hypersonic flows. Selective procedure to activate the sub-grid model wherever small scale turbulence is present (2013)
  20. He, Peng; Tang, Huazhong: An adaptive moving mesh method for two-dimensional relativistic magnetohydrodynamics (2012)

1 2 next