Haskell in Green Land: Analyzing the Energy Behavior of a Purely Functional Language

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Lima, LG (Author) Other; Soares Neto, F (Author) Other; Lieuthier, P (Author) Other; Castor, F (Author) Other; Melfe, G (Author) Other; Joao Paulo Fernandes (Author) Other

Conference proceedings International

Title: 2016 IEEE 23RD INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION, AND REENGINEERING (SANER), VOL 1

Pages: 517-528

23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER)

Osaka, JAPAN, MAR 14-18, 2016

Indexing

ISI Web of Knowledge - 24 Citations

Scopus - 40 Citations

Other information

Authenticus ID: P-00K-WW1

DOI: 10.1109/saner.2016.85

Abstract (EN): Recent work has studied the effect that factors such as code obfuscation, refactorings and data types have on energy efficiency. In this paper, we attempt to shed light on the energy behavior of programs written in a lazy purely functional language, Haskell. We have conducted two empirical studies to analyze the energy efficiency of Haskell programs from two different perspectives: strictness and concurrency. Our experimental space exploration comprises more than 2000 configurations and 20000 executions. We found out that small changes can make a big difference in terms of energy consumption. For example, in one of our benchmarks, under a specific configuration, choosing one data sharing primitive (MVar) over another (TMVar) can yield 60% energy savings. In another benchmark, the latter primitive can yield up to 30% energy savings over the former. Thus, tools that support developers in quickly refactoring a program to switch between different primitives can be of great help if energy is a concern. In addition, the relationship between energy consumption and performance is not always clear. In sequential benchmarks, high performance is an accurate proxy for low energy consumption. However, for one of our concurrent benchmarks, the variants with the best performance also exhibited the worst energy consumption. To support developers in better understanding this complex relationship, we have extended two existing performance analysis tools to also collect and present data about energy consumption.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12