Quantifying and Improving the Performance of Garbage Collection

Researchers have devoted decades towards improving garbage collec-tion performance. A key question is: What opportunity remains for performance improvement? Because the perceived performance dis-advantage of garbage collection is often cited as a barrier to its adoption, we propose using explicit memory management as the touchstone for evaluating garbage collection performance. This work begins by asking how well garbage collection performs currently and which areas remain for it to improve. We present oracular memory management to help answer this question by en-abling us to quantify garbage collections performance. Our results show that while garbage collection can perform competitively, this good performance assumes the heap fits in available memory. Our work thus focuses onto this brittleness, and we show the design and implement of our bookmarking collector. While performing competi-tively when not paging, our new collectors paging performance helps make garbage collections performance more robust.