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CELLULAR AUTOMATA AS AN EFFICIENT AND FLEXIBLE COMPUTATIONAL FRAMEWORK FOR MODELING AND SIMULATION OF REAL-WORLD, MULTISCALE COMPLEX SYSTEMS

Autor
Kategoria produktu
Nauki techniczne » Informatyka
ISBN
978-83-66016-63-7
ISSN
0867-6631
Typ publikacji
monografia
Format
B5
Oprawa
miękka
Liczba stron
148
Rok wydania
2019
Wydanie
1
Opis

Computer simulation is now a fully-fledged scientific method. It is especially useful for systems or phenomena that have the property of complexity. It means that it is impossible to deduct the behavior of the whole system from the analysis of its individual parts. It is a result of interactions and feedbacks (positive and negative) that occur between components. Such systems are called Complex Systems and the only reliable method to simulate them is tracking their evolution step-bystep by using models that directly represents all components. Intensive investigations into modeling methods were motivated by the need for new methods that are able to efficiently model a Complex System. The Cellular Automata is a modeling and simulation method often used to simulate Complex Systems. It allows to decompose the system into set of interacting entities. In this monograph, three issues related to the usage of this approach are considered. First, the possibilities of implementing parallel Cellular Automata models, especially for massively parallel architecture, such as a GPU, are investigated. Two Cellular Automata models are used as a case study: water flow and pedestrian dynamics. The researches include various strategies for constructing parallel models and their algorithms. Another issue, investigated by the Author, is multiscality which is difficult to represent using the original Cellular Automata approach. Thus, a new extension is proposed which is capable of encompassing processes occurring in different spatio-temporal scales. Efficiency and universality of this new modeling tool is demonstrated and discussed using natural phenomena like a vascular system and a mycelium. The last issue is the ability to use the Cellular Automata not only as a specific modeling tool but also as a flexible and efficient modeling framework. This approach was tested using a model of evolution and population dynamics. The model uses agent-based methodology to represent individuals, their behavior and life strategy and the Cellular Automata represents the agents’ habitat. Additionally, the Cellular Automata is used as a framework to organize the processing of agents. In particular, it allows to employ tested and efficient architectures of parallel computations. The monograph ends with an outline of the most important contributions and concluding remarks summarizing the results. 


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Abstract  7

Streszczenie  9

Preface  11

1. Introduction  19

1.1. Modeling Complex Systems  20

1.2. Simulation as scientific method  22

1.3. Cellular Automata  22

1.4. Cellular Automata: extensible modeling and simulation tool  25

1.5. Cellular Automata as flexible and efficient modeling framework  38

2. Cellular Automota for natural phenomena  39

2.1. Anastomosing river systems  40

2.2. Cellular Automata model of anastomosing river  42

2.3. Multi-scale phenomenon of anastomosing river  45

3. High performance simulations with Cellular Automata approach  47

3.1. Cellular Automata models on cluster platforms  48

3.2. Accelerating Cellular Automata models with GPU  50

3.3. Large-scale simulations with Cellular Automata models on GPU  62

3.4. Summary on applying GPU computations for Cellular Automata models  68

4. Cellular Automata applied for multiscale phenomena  69

4.1. Model of Anastomosing river with Graph of Cellular Automata  71

4.2. Model of tumor-induced angiogenesis  76

4.3. Model of Fusarium graminearum  88

4.4. Summary of using Graph of Cellular Automata models  96

5. Cellular Automata as an environment for agents  97

5.1. Agents and agent-based systems  97

5.2. Evolving agents in Cellular Automata environment  104

5.3. On efficiency of Cellular Automata with Agents and Agents with Cellular Automata  117

6. Summary  119

Bibliography  121

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