We introduce, in this paper, Clustered Time Warp (CTW), an algorithm for the parallel
simulation of discrete event models on a general purpose distributed memory
architecture. CTW has its roots in the problem of distributed logic simulation. It is a
hybrid algorithm which makes use of Time Warp between clusters of LPs and a
sequential algorithm within the clusters whereas Time Warp is traditionally
implemented between individual LPs.We also develop a family of three checkpointing algorithms for use with CTW, each of
which occupies a different point in the spectrum of possible trade-offs between memory
usage and execution time. The algorithms were implemented and tested on several digital
logic circuits and their speed, number of states saved and maximal memory consumption
were compared to Time Warp. Our results showed that one of the algorithms saved an
average of 40% of the maximal memory consumed by Time Warp while the other two
decreased the maximal usage by 15 and 22%, respectively. The latter two algorithms
exhibited a speed comparable to Time Warp, while the first algorithm was 60% slower.We investigated the scalability of CTW using 3 different queuing models and different
service-time distributions and showed that the algorithm acts to limit the explosion of
rollbacks exhibited by Time Warp. Furthermore, we showed that the memory
requirements for CTW are three times smaller than that of Time Warp for one model
and half as large for the two other models.