Data Cluster Detection for Low Power Embedded Memory Subsystems

Dae Jin Park; Jeong Hun Cho; Doo San Cho

doi:10.4028/www.scientific.net/AMM.789-790.833

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 789-790Data Cluster Detection for Low Power Embedded...

Data Cluster Detection for Low Power Embedded Memory Subsystems

Abstract:

This work proposes a technique for optimizing data placement of application-wide reused data so that it resides in scratchpad memory of processing elements in multiprocessor system on chips. The proposed technique identifies data elements with fine granularity that can profitably be placed in the scratchpad memories to maximize performance and energy gains. We present a heuristic approach that efficiently exploits the scratchpad memories using memory access footprint. Our experimental results indicate that our approach is able to reduce energy consumption by 30% over cache based memory subsystems.

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Periodical:

Applied Mechanics and Materials (Volumes 789-790)

Pages:

833-836

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.789-790.833

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Online since:

September 2015

Authors:

Dae Jin Park, Jeong Hun Cho, Doo San Cho

Keywords:

Analysis, Embedded System, Low Power, Memory, Optimization, Profiling

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