Scalable and Near-Optimal Design Space Exploration for Embedded Systems

Detalles Bibliográficos
Autor Principal:	Kritikakou, Angeliki
Otros autores o Colaboradores:	Catthoor, Francky, Goutis, Costas
Formato:	Libro
Lengua:	inglés
Datos de publicación:	Cham : Springer International Publishing : Imprint: Springer, 2014.
Temas:	Engineering. Energy. Microprocessors. Electronics. Microelectronics. Electronic circuits. Circuits and Systems. Processor Architectures. Instrumentation.
Acceso en línea:	http://dx.doi.org/10.1007/978-3-319-04942-7
Resumen:	This book describes scalable and near-optimal, processor-level design space exploration (DSE) methodologies.Â The authors present design methodologies for data storage and processing in real-time, cost-sensitive data-dominated embedded systems.Â 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. Â â_¢Â Describes design space exploration (DSE) methodologies for data storage and processing in embedded systems, which achieve near-optimal solutions with scalable exploration time; â_¢Â Presents a set of principles and the processes which support the development of the proposed scalable and near-optimal methodologies; â_¢Â Enables readers to apply scalable and near-optimal methodologies to the intra-signal in-place optimization step for both regular and irregular memory accesses.
Descripción Física:	xvii, 277 p. : il.
ISBN:	9783319049427
DOI:	10.1007/978-3-319-04942-7

Tabla de Contenidos:

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.

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Scalable and Near-Optimal Design Space Exploration for Embedded Systems

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