A parallel Self Mesh-Adaptive N-body method based on approximate inverses

A new parallel Self Mesh-Adaptive N-body method based on approximate inverses is proposed. The scheme is a three-dimensional Cartesian-based method that solves the Poisson equation directly in physical space, using modified multipole expansion formulas for the boundary conditions. Moreover, adaptive-mesh techniques are utilized to form a class of separate smaller n-body problems that can be solved in parallel and increase the total resolution of the system. The solution method is based on multigrid method in conjunction with the symmetric factored approximate sparse inverse matrix as smoother. The design of the parallel Self Mesh-Adaptive method along with discussion on implementation issues for shared memory computer systems is presented. The new parallel method is evaluated through a series of benchmark simulations using N-body models of isolated galaxies or galaxies interacting with dwarf companions. Furthermore, numerical results on the performance and the speedups of the scheme are presented.

[1]  S. McCormick,et al.  A multigrid tutorial (2nd ed.) , 2000 .

[2]  Barbara Chapman,et al.  Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation) , 2007 .

[3]  Peter J. Teuben,et al.  The Stellar Dynamics Toolbox NEMO , 1995 .

[4]  L. Verlet Computer "Experiments" on Classical Fluids. I. Thermodynamical Properties of Lennard-Jones Molecules , 1967 .

[5]  William L. Briggs,et al.  A multigrid tutorial, Second Edition , 2000 .

[6]  Piet Hut,et al.  A hierarchical O(N log N) force-calculation algorithm , 1986, Nature.

[7]  P. Wesseling Theoretical and Practical Aspects of a Multigrid Method , 1982 .

[8]  Leslie Greengard,et al.  A fast algorithm for particle simulations , 1987 .

[9]  William L. Briggs,et al.  A multigrid tutorial , 1987 .

[10]  Hugh Merz,et al.  High Performance P3M N-body code: CUBEP3M , 2012, 1208.5098.

[11]  Jan Vierendeels,et al.  Non-stationary two-stage relaxation based on the principle of aggregation multi-grid , 2009 .

[12]  V. Springel The Cosmological simulation code GADGET-2 , 2005, astro-ph/0505010.

[13]  Devin W. Silvia,et al.  ENZO: AN ADAPTIVE MESH REFINEMENT CODE FOR ASTROPHYSICS , 2013, J. Open Source Softw..

[14]  Dehnen A Very Fast and Momentum-conserving Tree Code. , 2000, The Astrophysical journal.

[15]  R W Hockney,et al.  Computer Simulation Using Particles , 1966 .

[16]  Jens Verner Villumsen Simulations of galaxy mergers , 1982 .

[17]  W. Press,et al.  Numerical Recipes: The Art of Scientific Computing , 1987 .

[18]  Sverre J. Aarseth Gravitational N-Body Simulations: Tools and Algorithms , 2003 .

[19]  Tucson,et al.  The AGORA High-resolution Galaxy Simulations Comparison Project. III. Cosmological Zoom-in Simulation of a Milky Way–mass Halo , 2013, The Astrophysical Journal.

[20]  James Binney,et al.  Galactic Dynamics: Second Edition , 2008 .

[21]  C. Efthymiopoulos,et al.  Structures induced by companions in galactic discs , 2016, 1611.04891.

[22]  R. Teyssier Cosmological hydrodynamics with adaptive mesh refinement - A new high resolution code called RAMSES , 2001, astro-ph/0111367.

[23]  J. A. Sellwood,et al.  GALAXY package for N-body simulation , 2014, 1406.6606.

[24]  A. Klypin,et al.  Adaptive Refinement Tree: A New High-Resolution N-Body Code for Cosmological Simulations , 1997, astro-ph/9701195.