Kritikakou, Angeliki.
Scalable and Near-Optimal Design Space Exploration for Embedded Systems [electronic resource] / by Angeliki Kritikakou, Francky Catthoor, Costas Goutis. - XVII, 277 p. 80 illus., 2 illus. in color. online resource.
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.
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.
9783319049427
10.1007/978-3-319-04942-7 doi
Engineering.
Energy.
Microprocessors.
Electronics.
Microelectronics.
Electronic circuits.
Engineering.
Circuits and Systems.
Processor Architectures.
Electronics and Microelectronics, Instrumentation.
Energy, general.
TK7888.4
621.3815
Scalable and Near-Optimal Design Space Exploration for Embedded Systems [electronic resource] / by Angeliki Kritikakou, Francky Catthoor, Costas Goutis. - XVII, 277 p. 80 illus., 2 illus. in color. online resource.
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.
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.
9783319049427
10.1007/978-3-319-04942-7 doi
Engineering.
Energy.
Microprocessors.
Electronics.
Microelectronics.
Electronic circuits.
Engineering.
Circuits and Systems.
Processor Architectures.
Electronics and Microelectronics, Instrumentation.
Energy, general.
TK7888.4
621.3815