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.