TaPT: Temperature-Aware Dynamic Cache Optimization for Embedded Systems
AffiliationUniv Arizona, Dept Elect & Comp Engn
Keywordsdynamic thermal management
low-power embedded systems
dynamic voltage and frequency scaling
MetadataShow full item record
CitationAdegbija T, Gordon-Ross A. TaPT: Temperature-Aware Dynamic Cache Optimization for Embedded Systems. Computers. 2018; 7(1):3.
Rights© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
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AbstractEmbedded systems have stringent design constraints, which has necessitated much prior research focus on optimizing energy consumption and/or performance. Since embedded systems typically have fewer cooling options, rising temperature, and thus temperature optimization, is an emergent concern. Most embedded systems only dissipate heat by passive convection, due to the absence of dedicated thermal management hardware mechanisms. The embedded system's temperature not only affects the system's reliability, but can also affect the performance, power, and cost. Thus, embedded systems require efficient thermal management techniques. However, thermal management can conflict with other optimization objectives, such as execution time and energy consumption. In this paper, we focus on managing the temperature using a synergy of cache optimization and dynamic frequency scaling, while also optimizing the execution time and energy consumption. This paper provides new insights on the impact of cache parameters on efficient temperature-aware cache tuning heuristics. In addition, we present temperature-aware phase-based tuning, TaPT, which determines Pareto optimal clock frequency and cache configurations for fine-grained execution time, energy, and temperature tradeoffs. TaPT enables autonomous system optimization and also allows designers to specify temperature constraints and optimization priorities. Experiments show that TaPT can effectively reduce execution time, energy, and temperature, while imposing minimal hardware overhead.
NoteOpen access journal.
VersionFinal published version
SponsorsNational Science Foundation [CNS-0953447]