Emerging mobile platforms integrate heterogeneous, multicore processors to efficiently deal with the heterogeneity of data (in magnitude, type, and quality). The main goal is to achieve a high degree of energy-proportionality which corresponds with the nature and fluctuation of mobile workloads. Most existing power and energy consumption analyses of these architectures rely on simulation or static benchmarks neither of which truly reflects the type of workload the processors handle in reality. By contrast, we generate two types of stochastic workloads and employ four types of dynamic voltage and frequency scaling (DVFS) policies to investigate the energy proportionality and the dynamic power consumption characteristics of a heterogeneous processor architecture when operating in different configurations. The analysis illustrates, both qualitatively and quantitatively, that knowledge of the statistics of the incoming workload is critical to determine the appropriate processor configuration.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:85463 |
| Date | 15 May 2023 |
| Creators | Arega, Frehiwot Melak, Hähnel, Markus, Dargie, Waltenegus |
| Publisher | Springer |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 978-3-319-54999-6, 10.1007/978-3-319-54999-6_19 |
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