Comparisons of different codes for galacticN-body simulations

Abstract

Context. N-body simulations are widely used for galactic dynamics studies. Several different algorithms have been developed and a number of authors have made their codes public. Aims. We wish to help potential users of these codes, particularly less experienced ones, to select the appropriate code by giving them relevant information. Methods. We consider different implementations of three different algorithms, namely the Barnes-Hut tree-code algorithm (implemented both in GADGET-2 and as a NEMO program), the fast multipole method (implemented in the FMB code -Fast Multipole with BLAS) and W. Dehnen's algorithm (implemented in falcON -force algorithm with complexity O(N)). We compare extensively the timing and memory comparisons of these different implementations and discuss other advantages and disadvantages of these codes.Results. In terms of serial executions, falcON is clearly the fastest code, in many cases by a wide margin. In addition, it is much less sensitive to concentration than other codes, it conserves linear momentum, its computational costs depends roughly linearly on the number of particles, and it allows for manipulators. GADGET-2 is the second fastest and, being parallel, can outperform falcON if a sufficient number of processors is used, the number of which, in our tests is between three and ten. Its public version includes an SPH representation of the gas component. FMB is faster than the implementation of the Barnes-Hut algorithm in NEMO, as long as the particle distribution is not too concentrated, but remains considerably slower than falcON and GADGET-2. It has, nevertheless, the highest parallel efficiency and memory scalability. Conclusions. We recommend falcON for pure N-body simulations with a relatively restricted number of particles (up to a few million). In cases of a larger number of particles, a number of processors being available, or studies including gas and its physics, we recommend GADGET-2. FMB provides the highest parallel efficiency and memory scalability, but is considerably slower in execution time and is ill-adapted to the concentrated distributions encountered in galactic work.

Parallel Dual Tree Traversal on Multi-core and Many-core Architectures for Astrophysical N-body Simulations

“…For is run on NVIDIA GPUs (C2070 or K20c, both in SSE-server) with CUDA 5.0. We will use two distributions of 10M particles: an artificial uniform distribution inside a 3D cube, and a Plummer distribution as a classical (non-uniform) astrophysical model [9]. All codes compute both forces and potentials, for all particles, with single precision floating point arithmetic.…”

“…All codes compute both forces and potentials, for all particles, with single precision floating point arithmetic. We also use in each code appropriate softenings for the near field part of the gravity [9]. Figure 4 presents the performance of different direct computation kernels presented in Sect.…”

“…Dehnen's algorithm [6], implemented in the serial falcON code (Force ALgorithm with Complexity O(N )), is one order of magnitude faster than serial executions of Barnes-Hut treecodes [6,9], mainly thanks to its dual tree traversal (DTT). But parallel tree-codes implementations, on one or two multi-core CPUs or on one GPU, then manage to outperform falcON [9]. The parallelization of falcON is therefore crucial to exploit its algorithmic asset on current parallel architectures.…”

“…All these features have been implemented in the falcON 2 code (Force ALgorithm with Complexity O(N )) which offers O(N ) computation times one order of magnitude smaller than serial executions of Barnes-Hut tree-codes [6,9]. Moreover, these computation times are much less sensitive to the distribution of particles: this is very important for astrophysical simulations where the particle distributions representing galaxies or groups of galaxies are highly non-uniform.…”

GPU-centric resolved-particle disperse two-phase flow simulation using the Physalis method

“…It is important to draw attention to the wealth of research on the topic of n-body simulation of which the method described below is but an example. For more advanced and/or specialized methods, see, e.g., Fortin et al [9].…”