In this paper, we propose a system-level design methodology for the efficient exploration of the architectural parameters of the memory sub-systems, from the energy-delay joint perspective. The aim is to find the best configuration of the memory hierarchy without performing the exhaustive analysis of the parameters space. The target system architecture includes the processor, separated instruction and data caches, the main memory, and the system buses. To achieve a fast convergence toward the near-optimal configuration, the proposed methodology adopts an iterative local-search algorithm based on the sensitivity analysis of the cost function with respect to the tuning parameters of the memory sub-system architecture. The exploration strategy is based on the Energy-Delay Product (EDP) metric taking into consideration both performance and energy constraints. The effectiveness of the proposed methodology has been demonstrated through the design space exploration of a real-world case study: the optimization of the memory hierarchy of a MicroSPARC2-based system executing the set of Mediabench benchmarks for multimedia applications. Experimental results have shown an optimization speedup of 2 orders of magnitude with respect to the full search approach, while the near-optimal system-level configuration is characterized by a distance from the optimal full search configuration in the range of 2%.

A Sensitivity-Based Design Space Exploration Methodology for Embedded Systems

FORNACIARI, WILLIAM;SCIUTO, DONATELLA;SILVANO, CRISTINA;ZACCARIA, VITTORIO
2002

Abstract

In this paper, we propose a system-level design methodology for the efficient exploration of the architectural parameters of the memory sub-systems, from the energy-delay joint perspective. The aim is to find the best configuration of the memory hierarchy without performing the exhaustive analysis of the parameters space. The target system architecture includes the processor, separated instruction and data caches, the main memory, and the system buses. To achieve a fast convergence toward the near-optimal configuration, the proposed methodology adopts an iterative local-search algorithm based on the sensitivity analysis of the cost function with respect to the tuning parameters of the memory sub-system architecture. The exploration strategy is based on the Energy-Delay Product (EDP) metric taking into consideration both performance and energy constraints. The effectiveness of the proposed methodology has been demonstrated through the design space exploration of a real-world case study: the optimization of the memory hierarchy of a MicroSPARC2-based system executing the set of Mediabench benchmarks for multimedia applications. Experimental results have shown an optimization speedup of 2 orders of magnitude with respect to the full search approach, while the near-optimal system-level configuration is characterized by a distance from the optimal full search configuration in the range of 2%.
Computer Architectures, Design space exploration, Power and performance optimization, Embedded Systems,
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/557323
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