Parallel and distributed simulation systems have evolved from research in the 1970s and 1980s, now widely used in applications like military training, communication network analysis, and air traffic control. This tutorial discusses technologies for distributing simulation execution across multiple computers, focusing on synchronization and data distribution. Parallel simulations run on multiprocessor systems with frequent interactions, while distributed simulations operate on loosely coupled systems with slower interactions. Both involve distributing a single simulation model across multiple computers. Two main simulation types are discussed: analytic simulations for evaluating system designs and virtual environments for training and entertainment. Parallel and distributed simulations offer benefits like reduced execution times, real-time performance, and geographically distributed environments. They also simplify integrating simulators from different manufacturers. Synchronization algorithms are crucial for ensuring correct event processing order and repeatable results. Conservative synchronization ensures events are processed in timestamp order, while optimistic synchronization allows violations but can recover. Time Warp is a key optimistic algorithm that rolls back events to maintain correctness. Time-parallel simulation divides the time axis into intervals, allowing parallel execution. However, state-matching between intervals is challenging. Techniques like guessing initial states and fix-up computations help resolve this. Distributed virtual environments (DVEs) use standards like DIS and HLA for interoperability, with data distribution mechanisms ensuring efficient communication. Data distribution in DVEs involves managing communication bandwidth and ensuring relevant messages are sent. The HLA provides declaration and data distribution management services, using routing spaces and regions for efficient data sharing. Interest and description expressions define regions for data distribution, enabling precise message routing. In summary, parallel and distributed simulation technologies address execution issues on multiprocessor and distributed systems, with applications in high-performance computing and virtual environments. Synchronization and data distribution remain central challenges, with ongoing research improving performance and efficiency.Parallel and distributed simulation systems have evolved from research in the 1970s and 1980s, now widely used in applications like military training, communication network analysis, and air traffic control. This tutorial discusses technologies for distributing simulation execution across multiple computers, focusing on synchronization and data distribution. Parallel simulations run on multiprocessor systems with frequent interactions, while distributed simulations operate on loosely coupled systems with slower interactions. Both involve distributing a single simulation model across multiple computers. Two main simulation types are discussed: analytic simulations for evaluating system designs and virtual environments for training and entertainment. Parallel and distributed simulations offer benefits like reduced execution times, real-time performance, and geographically distributed environments. They also simplify integrating simulators from different manufacturers. Synchronization algorithms are crucial for ensuring correct event processing order and repeatable results. Conservative synchronization ensures events are processed in timestamp order, while optimistic synchronization allows violations but can recover. Time Warp is a key optimistic algorithm that rolls back events to maintain correctness. Time-parallel simulation divides the time axis into intervals, allowing parallel execution. However, state-matching between intervals is challenging. Techniques like guessing initial states and fix-up computations help resolve this. Distributed virtual environments (DVEs) use standards like DIS and HLA for interoperability, with data distribution mechanisms ensuring efficient communication. Data distribution in DVEs involves managing communication bandwidth and ensuring relevant messages are sent. The HLA provides declaration and data distribution management services, using routing spaces and regions for efficient data sharing. Interest and description expressions define regions for data distribution, enabling precise message routing. In summary, parallel and distributed simulation technologies address execution issues on multiprocessor and distributed systems, with applications in high-performance computing and virtual environments. Synchronization and data distribution remain central challenges, with ongoing research improving performance and efficiency.