1. Parallel and Distributed Simulation Introduction and Motivation By Syed S. Rizvi

2. Modeling & Simulation Model: is a representation –Entity –Process –System Simulation: The process of exercising a model –Characterize the behavior of the modeled entity process, or system over time Computer simulation: is a computer program –Simulate an abstract model of a particular system

3. Why & Where Use Simulations Why do we need Simulations Observe a Real Operational System –Difficult –Hazardous –expensive Parts of the system may not be observable/viewable –e.g., internals of a silicon chip or biological system Where we can use Simulations Analyze system before it is built –Reduce number of design mistakes –Optimize design Analyze operational systems –Optimize the performance –Operational mistakes Create virtual environments for training, entertainment

4. Applications: System Analysis Classical Application of Simulation Telecommunication networks –Example  Sim-Link tool Battlefield simulations –Example  JOFT & JFAST for JFCOM Transportation systems Electronic systems (e.g., computer systems, microelectronics) Manufacturing systems Ecological systems Etc..

5. Simulation tool is used for fast analysis of alternate courses of action in time critical situations –Initialize simulation from situation database –Faster-than-real-time execution to evaluate effect of decisions Applications: air traffic control, battle management Simulation results may be needed in only seconds Applications: On-Line Decision Aids live data feeds analysts and decision makers forecasting tool (fast simulation) situation database interactive simulation environment

6. Applications: Virtual Environments Uses: VE uses for training –Education Haptar (http://vmasce.vmasc.odu.edu/fig_06/exercise.html)http://vmasce.vmasc.odu.edu/fig_06/exercise.html –Military Example is America’s Army (http://www.americasarmy.com/)http://www.americasarmy.com/ –Medicine –Emergency planning –Entertainment, – Etc.. Simulations are often used in virtual environments to create dynamic computer generated entities Defense: Computer generated forces (CGF) –Automated forces –Semi-automated forces

7. Simulation Fundamentals A computer simulation is a: –computer program that models the behavior of a physical system over time. Computer Simulation has: –Program variables (state variables) –Represents the current state of the physical system State Variables can be modified: –Model the development of the physical system over time.

8. Simulation Taxonomy Continuous time simulation –State changes occur continuously across time –Typically, behavior of CM described by differential equations Discrete time simulation –State changes only occur at discrete time instants –Simulation Time: Time stepped: time advances by fixed time increments Event stepped: time advances occur with irregular increments Computer Simulation Discrete Models Continuous Models Event driven Time- stepped

9. Time Stepped vs. Event Stepped Goal: compute state of system over simulation time state variables simulation time event driven execution time advances occur with irregular increments

10. Parallel / Distributed Simulation –Parallel Simulation: Tightly coupled architecture  shared memory multiprocessor systems Goal: reduce execution time –Distributed Simulation: Loosely coupled architecture  set of computers Goal: linking distributed resources, reusability, interoperability –Parallel (Distributed) Simulation Refers to the technology concerned with executing computer simulations over computing systems containing multiple processors

11. Distributed Simulation Simulation Sequential ExecutionParallel Execution Divide a single-large-simulation in a series of discrete events Discrete events can then be distributed on geographically distributed computers Time Management Algorithm is running there that ensures that the execution of the parallel distributed simulation is properly synchronized. Parallel/Distributed Simulation

12. Why Execute Over Multiple CPUs? Reduced model execution time –Up to N-fold reduction using N CPUs May not have enough memory on a single machine –Large physical system  large model  large simulation  enough memory & processors are required Scalable performance –Maintaining the same execution speed for bigger models/virtual environments by using more CPUs Geographically distributed users and/or resources –(e.g., simultaneous update of databases) Is there any Disadvantage ??

13. Chandy/Misra/Bryant algorithm Time Warp algorithm High Performance Computing Community 197519801985199019952000 Historical Perspective SIMulator NETworking (SIMNET) (1983-1990) Distributed Interactive Simulation (DIS) Aggregate Level Simulation Protocol (ALSP) (1990 - 1997ish) High Level Architecture (1996 - today) Defense Community Adventure (Xerox PARC) Dungeons and Dragons Board Games Multi-User Dungeon (MUD) Games Internet & Gaming Community Multi-User Video Games Conservative synchronization Optimistic synchronization

14. Summary Simulation is seeing widespread use in: –system design and management, as decision aids, and in creating virtual worlds for training or entertainment Fundamental concepts: State, changing state across simulation time –Continuous vs. discrete time simulations –Here, focus on discrete event simulation Reasons for distributing the execution of simulations over multiple computers include –Performance –Geographical distribution –Easier integration of systems (interoperability), reuse Parallel/Distributed simulation technologies developed largely independently in different R&D communities –High performance computing –Defense –Internet and gaming