05579nam 2200757 a 450 991082830810332120240313134124.097811185775851118577582978129914630312991463099781118577769111857776097811185776601118577663(CKB)2670000000327411(EBL)1117268(OCoLC)827208496(SSID)ssj0000904833(PQKBManifestationID)11494231(PQKBTitleCode)TC0000904833(PQKBWorkID)10924298(PQKB)10774565(OCoLC)828100066(MiAaPQ)EBC1117268(Au-PeEL)EBL1117268(CaPaEBR)ebr10653848(CaONFJC)MIL445880(OCoLC)812570943(FINmELB)ELB178707(Perlego)1001169(EXLCZ)99267000000032741120121017d2013 uy 0engur|n|---|||||txtccrMemory allocation problems in embedded systems optimization methods /María Soto ... [et al.]1st ed.London ISTE ;Hoboken, N.J. Wiley20131 online resource (198 p.)Computer engineering seriesDescription based upon print version of record.9781848214286 1848214286 Includes bibliographical references and index.Title Page; Contents; Introduction; Chapter 1. Context; 1.1. Embedded systems; 1.1.1. Main components of embedded systems; 1.2. Memory management for decreasing power consumption; 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 electronics1.4.1. Main challenges in applying operations research to electronicsChapter 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 Banks3.1. Introduction3.2. 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 metaheuristics4.4.1. Generating initial solutions4.4.1.1. 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 problem5.3. An illustrative example5.4. 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: Cases 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 147; 7.1. Summary of the memory allocation problem versions7.2. Intensification and diversification 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, pISTEEmbedded computer systemsEmbedded computer systems.006.22Soto María920609MiAaPQMiAaPQMiAaPQBOOK9910828308103321Memory allocation problems in embedded systems4100746UNINA