Proceedings of the 2006 Winter Simulation Conference L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, eds. ABSTRACT This paper presents the performance evaluation of a CMB (Chandy-Misra-Bryant) protocol from the perspective of execution time. The performance of each logical process in simulation is measured. Our evaluation shows that logical processes can have different behaviors and different proto- cols can be used simultaneously in simulations. While some logical processes may perform well using conserva- tive protocols, others can use optimistic protocols because otherwise most of the time these processes would be blocked unnecessarily. In order to analyze the behavior of the simulations some models were simulated using a CMB implementation called ParSMPLX. These models showed that each logical process of a simulation has a different be- havior that makes it more suitable for a specific protocol, increasing the performance. 1 INTRODUCTION The simulation technique is a powerful tool to evaluate performance of computer systems, however it can consume a lot of time and computational resources. Even with fast processors, simulations can take many hours to complete. In order to reduce this time, simulations can be executed in parallel machines or distributed systems (Dongarra et al. 2002, Kumar et al. 2004, Fujimoto 2003). One parallel simulation approach is to decompose the simulation model into logical processes and simulate each one in a different processor. This approach can reduce the simulation time for some applications, mainly those which are easy to become parallel and have large computational granularity. Research has been done in distributed simulation tech- nique and most of these studies focus on two well known protocols: conservative and optimistic (Bruschi et al. 2004, Xu and Chung 2004, Bauer et al. 2005, Bononi et al. 2005, Curry et al. 2005, Lee, Luu and Konangi 2005). Events in the conservative approach are executed only when causality errors can be avoided, i.e., when there is not an event with smaller timestamp than the first event in the event queue.The optimistic protocol, on the other hand, simulates all the events without being concerned about causality errors. If an error occurs, the simulation returns to a safe state (using rollbacks) and the simulation can con- tinue. Various papers have shown that choosing a parallel simulation protocol is a difficult task because it depends on a set of factors concerning the model and the computa- tional platform (Alonso, Frutos and Palacio 1994, Choi and Chung 1995, Xu and Chung 2004). Computational granu- larity, model partitioning, load balancing, and lookahead are a few factors that can influence the simulation per- formance. Attempting to predict the performance of a parallel simulation is a difficult task because different models have different characteristics. Some models can have good speedup, even though some logical processes of the simu- lation are slower than others. This paper describes experiments that were carried out with sequential (SMPLX) and conservative distributed simulations (ParSMPLX) to find out the factors that can affect the performance of a simulation. The results show that each logical process of a simulation model has particu- lar characteristics that make it more suitable for a specific protocol (conservative or optimistic) depending on factors such as blocked time, number of null messages exchanged, and the type of blocking that the logical process can ex- perience (necessary or unnecessary). We explain the factors that affect the simulation per- formance and use them to demonstrate how the perform- ance can be analyzed in each one of the logical processes. When these metrics are collected and analysed at run-time, an opportunity is created for adapting the simulation for increased speed. The performance we obtained with our method differs from what has been reported in the litera- ture. PERFORMANCE EVALUATION OF A CMB PROTOCOL Célia L. O. Kawabata Centro Universitário Central Paulista Rua Miguel Petroni, 5111 São Carlos, SP 13563-470, BRAZIL Regina H. C. Santana Marcos J.Santana Sarita M. Bruschi ICMC, Universidade de São Paulo Av. Trabalhador São-Carlense 400 São Carlos, SP 13560-970, BRAZIL Kalinka R. L. J. Castelo Branco Centro Universitário Eurípides de Marília Av Hygino Muzzi Filho 529 Marília, SP 17525-901, BRAZIL 1012 1-4244-0501-7/06/$20.00 ©2006 IEEE