Abstract
Energy consumption becomes more and more a critical design factor, whereby performance is still an important requirement. Thus, a balance between performance and energy has to be established. To tackle that issue for database systems, we proposed the concept of work-energy profiles. However, generating such profiles requires extensive benchmarking. To overcome that, we propose to approximate work-energy-profiles for complex operations based on the profiles of low-level operations in this paper. To show the feasibility of our approach, we use lightweight data compression algorithms as complex operations, since compression as well as decompression are heavily used in in-memory database systems, where data is always managed in a compressed representation. Furthermore, we evaluate our approach on a concrete hardware system.
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Acknowledgments
This work is partly funded within the DFG-CRC 912 (HAEC) and by the DFG-project LE-1416/26.
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Ungethüm, A., Damme, P., Pietrzyk, J., Krause, A., Habich, D., Lehner, W. (2017). Balancing Performance and Energy for Lightweight Data Compression Algorithms. In: Kirikova, M., et al. New Trends in Databases and Information Systems. ADBIS 2017. Communications in Computer and Information Science, vol 767. Springer, Cham. https://doi.org/10.1007/978-3-319-67162-8_5
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DOI: https://doi.org/10.1007/978-3-319-67162-8_5
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