A modified parallel tree code for N-body simulation of the Large Scale Structure of the Universe

Details A modified parallel tree code for N-body simulation of the Large Scale Structure of the Universe A modified parallel tree code for N-body simulation of the Large Scale Structure of the Universe

2000-04-18

arxiv.org/abs/astro-ph/0004249v2

J. Comput. Phys. Vol. 163, 118-132 (2000)

Astronomy and Astrophysics

Astrophysics

13 pages and 7 Figures

Scientific paper

10.1006/jcph.2000.6557

N-body codes to perform simulations of the origin and evolution of the Large Scale Structure of the Universe have improved significantly over the past decade both in terms of the resolution achieved and of reduction of the CPU time. However, state-of-the-art N-body codes hardly allow one to deal with particle numbers larger than a few 10^7, even on the largest parallel systems. In order to allow simulations with larger resolution, we have first re-considered the grouping strategy as described in Barnes (1990) (hereafter B90) and applied it with some modifications to our WDSH-PT (Work and Data SHaring - Parallel Tree) code. In the first part of this paper we will give a short description of the code adopting the Barnes and Hut algorithm \cite{barh86} (hereafter BH), and in particular of the memory and work distribution strategy applied to describe the {\it data distribution} on a CC-NUMA machine like the CRAY-T3E system. In the second part of the paper we describe the modification to the Barnes grouping strategy we have devised to improve the performance of the WDSH-PT code. We will use the property that nearby particles have similar interaction list. This idea has been checked in B90, where an interaction list is builded which applies everywhere within a cell C_{group} containing a little number of particles N_{crit}. B90 reuses this interaction list for each particle $ p \in C_{group}$ in the cell in turn. We will assume each particle p to have the same interaction list. Thus it has been possible to reduce the CPU time increasing the performances. This leads us to run simulations with a large number of particles (N ~ 10^7/10^9) in non-prohibitive times.

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