Memory Allocation Problems in Embedded Systems Optimization Methods 1st Edition by Maria Soto, Marc Sevaux, Andre Rossi, Johann Laurent – Ebook PDF Instant Download/Delivery: 1848214286, 9781848214286
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ISBN 10: 1848214286
ISBN 13: 9781848214286
Author: Maria Soto, Marc Sevaux, Andre Rossi, Johann Laurent
Embedded systems are everywhere in contemporary life and are supposed to make our lives more comfortable. In industry, embedded systems are used to manage and control complex systems (e.g. nuclear power plants, telecommunications and flight control) and they are also taking an important place in our daily activities (e.g. smartphones, security alarms and traffic lights).
In the design of embedded systems, memory allocation and data assignment are among the main challenges that electronic designers have to face. In fact, they impact heavily on the main cost metrics (power consumption, performance and area) in electronic devices. Thus designers of embedded systems have to pay careful attention in order to minimize memory requirements, thus improving memory throughput and limiting the power consumption by the system’s memory. Electronic designers attempt to minimize memory requirements with the aim of lowering the overall system costs.
A state of the art of optimization techniques for memory management and data assignment is presented in this book.
Memory Allocation Problems in Embedded Systems Optimization Methods 1st Table of contents:
Chapter 1. Context
1.1. Embedded systems
1.1.1. Main components of embedded systems
1.2. Memory management for decreasing power consumption, performance, and area in embedded systems
1.3. State of the art in optimization techniques for memory management and data assignment
1.3.1. Software optimization
1.3.2. Hardware optimization
1.3.3. Data binding
1.3.3.1. Memory partitioning problem for low energy
1.3.3.2. Constraints on memory bank capacities and number of accesses to variables
1.3.3.3. Using external memory
1.4. Operations research and electronics
1.4.1. Main challenges in applying operations research to electronics
Chapter 2. Unconstrained Memory Allocation Problem
2.1. Introduction
2.2. An ILP formulation for the unconstrained memory allocation problem
2.3. Memory allocation and the chromatic number
2.3.1. Bounds on the chromatic number
2.4. An illustrative example
2.5. Three new upper bounds on the chromatic number
2.6. Theoretical assessment of three upper bounds
2.7. Computational assessment of three upper bounds
2.8. Conclusion
Chapter 3. Memory Allocation Problem With Constraint on the Number of Memory Banks
3.1. Introduction
3.2. An ILP formulation for the memory allocation problem with constraint on the number of memory banks
3.3. An illustrative example
3.4. Proposed metaheuristics
3.4.1. A tabu search procedure
3.4.2. A memetic algorithm
3.5. Computational results and discussion
3.5.1. Instances
3.5.2. Implementation
3.5.3. Results
3.5.4. Discussion
3.6. Conclusion
Chapter 4. General Memory Allocation Problem
4.1. Introduction
4.2. ILP formulation for the general memory allocation problem
4.3. An illustrative example
4.4. Proposed metaheuristics
4.4.1. Generating initial solutions
4.4.1.1. Random initial solutions
4.4.1.2. Greedy initial solutions
4.4.2. A tabu search procedure
4.4.3. Exploration of neighborhoods
4.4.4. A variable neighborhood search hybridized with a tabu search
4.5. Computational results and discussion
4.5.1. Instances used
4.5.2. Implementation
4.5.3. Results
4.5.4. Discussion
4.5.5. Assessing TabuMemex
4.6. Statistical analysis
4.6.1. Post hoc paired comparisons
4.7. Conclusion
Chapter 5. Dynamic Memory Allocation Problem
5.1. Introduction
5.2. ILP formulation for dynamic memory allocation problem
5.3. An illustrative example
5.4. Iterative metaheuristic approaches
5.4.1. Long-term approach
5.4.2. Short-term approach
5.5. Computational results and discussion
5.5.1. Results
5.5.2. Discussion
5.6. Statistical analysis
5.6.1. Post hoc paired comparisons
5.7. Conclusion
Chapter 6. MemExplorer: Case Studies
6.1. The design flow
6.1.1. Architecture used
6.1.2. MemExplorer design flow
6.1.3. Memory conflict graph
6.2. Example of MemExplorer utilization
Chapter 7. General Conclusions and Future Work
7.1. Summary of the memory allocation problem versions
7.2. Intensification and diversification
7.2.1. Metaheuristics for memory allocation problem with constraint on the number of memory banks
7.2.1.1. Tabu-Allocation
7.2.1.2. Evo-Allocation
7.2.2. Metaheuristic for general memory allocation problem
7.2.3. Approaches for dynamic memory allocation problem
7.3. Conclusions
7.4. Future work
7.4.1. Theoretical perspectives
7.4.2. Practical perspectives
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Tags: Maria Soto, Marc Sevaux, Andre Rossi, Johann Laurent, Memory Allocation, Optimization Methods


