We consider massively parallel discrete event simulations where the communication topology among the processing elements is a complex graph. In the case of regular topologies we review recent results on virtual time horizon management. First we analyze the computational scalability of the conservative massively parallel update scheme for discrete event simulations by using the analogy with a well-known surface growth model, then we show that a simple modification of the regular PE communication topology to a small-world topology will also ensure measurement scalability. This leads to a fully scalable parallel simulation for systems with asynchronous dynamics and short-range interactions. Finally, we present numerical results for the evolution of the virtual time horizon on scale-free Barabasi-Albert networks serving as communication topology among the processing elements.
[1]
R. Evershed,et al.
Mat Res Soc Symp Proc
,
1995
.
[2]
A. Schoneveld,et al.
Parallel complex systems simulation
,
1999
.
[3]
Leonard Kleinrock,et al.
Bounds and approximations for self-initiating distributed simulation without lookahead
,
1991,
TOMC.
[4]
M. A. Novotny,et al.
Algorithmic scalability in globally constrained conservative parallel discrete event simulations of asynchronous systems
,
2002,
Physical review. E, Statistical, nonlinear, and soft matter physics.
[5]
Ericka Stricklin-Parker,et al.
Ann
,
2005
.
[6]
A. Barabasi,et al.
Fractal concepts in surface growth
,
1995
.