Modeling and Simulation in computer science

Chapters

1Foundations of Modeling in Computer Science

2Mathematical Foundations for Simulation

3Discrete-Event Simulation Fundamentals

4Agent-Based Modeling and Complex Systems

5System Dynamics and Continuous Modeling

6Numerical Methods and Scientific Computing for Simulation

7Stochastic Processes and Uncertainty Quantification

8Data Structures, Algorithms, and Simulation Efficiency

Data Structures for Simulation State Event Queues and Priority Queues Hashing and Caching for Speed Memory Management and Profiling Parallelism and Concurrency Cache Locality and Performance Algorithmic Complexity and Optimization Data Access Patterns and Cache-Aware Design Random Number Streams Management Domain Decomposition Load Balancing in Simulations Profiling Tools and Techniques Vectorization and SIMD GPU Acceleration Concepts Testing and Debugging Simulations

9Simulation Programming Languages and Frameworks

10Verification, Validation, and Experiment Design

11Performance Analysis and Optimization of Simulations

12High-Performance Computing and Parallel Simulation

13Data Management, Reproducibility, and Experiment Tracking

14Visualization and Communication of Simulation Results

15Applications and Case Studies in Modeling and Simulation

Courses/Modeling and Simulation in computer science/Data Structures, Algorithms, and Simulation Efficiency

Data Structures, Algorithms, and Simulation Efficiency

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Optimize the internal machinery of simulations through efficient data handling and computation.

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Vectorization and SIMD

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