Distributed simulation is an effective method to improve simulation speed for computer architecture. In this paper, a general performance model for distributed simulation is established and then some typical distributed simulation systems are analyzed based on the model. The analysis results in some important conclusions about parallel speedup and parallel efficiency for distributed simulation. Next, a scalable and evenly distributed simulation (SEDSim) approach is presented. SEDSim adopts a cost model guided even partition and allocation (CoMEPA) policy for benchmark program instructions to enhance load-balance among parallel simulation nodes. An allocation policy based on minimum equivalent cost (MinEC) is also designed to efficiently integrate arbitrary number of discrete sampling intervals in SEDSim. The study implementes SEDSim based on sim-outorder and evaluates its speed and accuracy using Benchmark programs from SPEC CPU2000. Both theoretical analysis and testing results validate some advantages of SEDSim approach. Compared with existing methods, CoMEPA and MinEC can achieve a speedup of about 1.6 and 1.4 respectively.