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, while satisfying system requirements for performance, area, and energy consumption, thereby minimizing the overall cost of the final design.

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.