Impact of Developer Choices on Energy Consumption of Software on Servers

The power cost of running a data center is a significant portion of its total annual operating budget. With the aim of reducing power bills of data centers, “Green Computing” has emerged with the primary goal of making software more energy efficient without compromising the performance. Developers play an important role in controlling the energy cost of data center software while writing code. In this paper, we show how software developers can contribute to energy efficiency of servers by choosing energy efficient APIs (Application Programming Interface) with the optimal choice of parameters while implementing file reading, file copy, file compression and file decompression operations in Java; that are performed extensively on large scale servers in data centers. We performed extensive measurements of energy cost of those operations on a Dell Power Edge 2950 machine running Linux and Windows servers. Measurement results show that energy costs of various APIs for those operations are sensitive to the buffer size selection. The choice of a particular Java API for file reading with different buffer sizes has significant impact on the energy cost, giving an opportunity to save up to 76%. To save energy while copying files, it is important to use APIs with tunable buffer sizes, rather than APIs using fixed size buffers. In addition, there is a trade off between compression ratio and energy cost: because of more compression ratio, xz compression API consumes more energy than zip and gzip compression APIs. Finally, we model the energy costs of APIs by polynomial regression to avoid repeated measurements