Scalable and Near-Optimal Design Space Exploration for Embedded Systems
This book describes scalable and near-optimal, processor-level design space exploration (DSE) methodologies. The authors present design methodologies for data storage and processing in real-time, cost-sensitive data-dominated embedded systems. Readers will be enabled to reduce time-to-market, whil...
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| Κύριοι συγγραφείς: | , , |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
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| Έκδοση: | 1st ed. 2014. |
| Θέματα: | |
| Διαθέσιμο Online: | https://doi.org/10.1007/978-3-319-04942-7 |
| Ετικέτες: |
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| Περίληψη: | This book describes scalable and near-optimal, processor-level design space exploration (DSE) methodologies. The authors present design methodologies for data storage and processing in real-time, cost-sensitive data-dominated embedded systems. Readers will be enabled to reduce time-to-market, while satisfying system requirements for performance, area, and energy consumption, thereby minimizing the overall cost of the final design. • Describes design space exploration (DSE) methodologies for data storage and processing in embedded systems, which achieve near-optimal solutions with scalable exploration time; • Presents a set of principles and the processes which support the development of the proposed scalable and near-optimal methodologies; • Enables readers to apply scalable and near-optimal methodologies to the intra-signal in-place optimization step for both regular and irregular memory accesses. |
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| Φυσική περιγραφή: | XVII, 277 p. 80 illus., 2 illus. in color. online resource. |
| ISBN: | 9783319049427 |