Scalable and Near-Optimal Design Space Exploration for Embedded Systems [electronic resource] / by Angeliki Kritikakou, Francky Catthoor, Costas Goutis.
By: Kritikakou, Angeliki [author.].
Contributor(s): Catthoor, Francky [author.] | Goutis, Costas [author.] | SpringerLink (Online service).
Material type: BookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: XVII, 277 p. 80 illus., 2 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319049427.Subject(s): Engineering | Energy | Microprocessors | Electronics | Microelectronics | Electronic circuits | Engineering | Circuits and Systems | Processor Architectures | Electronics and Microelectronics, Instrumentation | Energy, generalAdditional physical formats: Printed edition:: No titleDDC classification: 621.3815 Online resources: Click here to access onlineIntroduction & Motivation -- Reusable DSE methodology for scalable & near-optimal frameworks -- Part I Background memory management methodologies -- Development of intra-signal in-place methodology -- Pattern representation -- Intra-signal in-place methodology for non-overlapping scenario -- Intra-signal in-place methodology for overlapping scenario -- Part II Processing related mapping methodologies -- Design-time scheduling techniques DSE framework -- Methodology to develop design-time scheduling techniques under constraints -- Design Exploration Methodology for Microprocessor & HW accelerators -- Conclusions & Future Directions.
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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