Marina Shimchenko: Optimizing Energy Efficiency of Concurrent Garbage Collection

Abstract

The increasing energy consumption of the Information and Communication Technology sector amid climate change concerns underscores the urgency for energy efficiency improvements in computing. This thesis focuses on optimizing the energy efficiency of Java, a widely used programming language, and its implementation in OpenJDK. Specifically, our focus is on enhancing the energy efficiency of concurrent garbage collection.

As a starting point for our work, we assessed the energy consumption of various garbage collection algorithms within OpenJDK, establishing concurrent garbage collectors as the least energy-efficient. This prompted further investigation into methods to enhance their energy consumption. We investigated methods like dynamically adjusting the memory size required by an application based on how much of the computer's processors one wants to use for garbage collection. We also looked into scheduling garbage collection tasks to run on specific types of computer cores that use less energy and running these tasks when the computer is not being actively used. 

We implemented all the abovementioned strategies in one of Java’s concurrent garbage collectors, ZGC. Through our experiments, we showed that these techniques can significantly reduce the amount of energy used by garbage collection without slowing down the performance of the programs running on the computer. Overall, our research contributes to making computing more environmentally friendly by finding ways to use less energy while still getting the same results.