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Scalable and Near-Optimal Design Space Exploration for Embedded Systems de Angeliki Kritikakou

Scalable and Near-Optimal Design Space Exploration for Embedded Systems

Autor Angeliki Kritikakou, Francky Catthoor, Costas Goutis
en Limba Engleză Hardback – 3 apr 2014
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.
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Specificații

ISBN-13: 9783319049410
ISBN-10: 3319049410
Pagini: 296
Ilustrații: XVII, 277 p. 80 illus., 2 illus. in color.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.7 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Introduction & 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.

Textul de pe ultima copertă

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.


Caracteristici

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 Includes supplementary material: sn.pub/extras