Chapter 1 Introduction
1.1 General introduction of P systems implementation
1.2 Challenging problems of P systems implementation
1.3 Review of software implementations
1.4 Review of hardware implementations
1.5 Other implementation platforms
Chapter 2 P systems Implementation on P-Lingua framework
2.1 Overview
2.2 P-Lingua language for P systems variants
2.3 Simulation algorithms
2.4 MeCoSim
Chapter 3 Software implementation for P systems
3.1 Automatic design of cell-like P systems with P-Lingua
3.2 Automatic design of spiking neural P systems with P-Lingua
3.3 Modelling real ecosystems with MeCoSim
3.4 Robot motion planning
Chapter 4 Infobiotics Workbench - In Silico Software Suite for Computational Biology
4.1 Introduction
4.2 Stochastic P Systems
4.3 Software Description
4.3.1 Modelling
4.3.2 Simulation
4.3.3 Verification
4.3.4 Parameter Optimization
4.4 Case Studies
4.5 Next Generation Infobiotics
4.5.1 Prediction-based stochastic simulations
4.5.2 High-performance simulation and verification
4.5.3 Biocompilation
4.6 Conclusions and discussions
Chapter 5 Molecular Physics and Chemistry in Membranes: The Java Environment for Nature-inspired Approaches (JENA)
5.1 Motivation and Introduction
5.2 JENA at a Glance
5.3 JENA Descriptive Capacity
5.4 JENA Source Code Design
5.5 Selection of JENA Case Studies
Chapter 6 P systems Implementation on CUDA
6.1 Overview
6.2 Specific simulations
6.3 Generic simulations
6.4 Adaptative simulations
Chapter 7 P systems Implementation on FPGA
7.1 Introduction
7.2 FPGA Hardware
7.3 Generalized Numerical P systems (GNPS)
7.4 Implementing GNPS on FPGA
7.5 FPGA implementations of other models of P systems
7.6 Discussion
Chapter 8 Hardware implementations and applications
8.1 Knapsack problems with CUDA implementation
8.2 Robot membrane controllers with FPGA implementation
8.3 Robot path planning with FPGA implementation
8.4 Image processing with FPGA implementation
