Abstract Type safety and garbage collection in managed languages elimi-nate memory errors such as dangling pointers, double frees, and

The growth in complexity of modern systems makes it increasingly difficult to extract high-performance. The software stacks for such systems typically consist of multiple layers and include managed runtime environments (MREs). In this paper, we investigate techniques to improve cooperation between these layers and the hardware to increase the efficacy of automatic memory management in MREs. General-purpose MREs commonly implement parallel and/or concurrent garbage collection and employ compaction to eliminate heap fragmentation. Moreover, most systems trigger collection based on the amount of heap a program uses. Our analysis shows that in many cases this strategy leads to ineffective collections that are unable to reclaim sufficient space to justify the incurred cost. To avoid such collections, we exploit the observation that dead objects tend to cluster together and form large, never-referenced, regions in the address space that correlate well with virtual pages that have not recently been referenced by the application. We leverage this correlation to design a new, simple and light-weight, yield predictor that estimates the amount of reclaimable space in the heap using hardware page reference bits. Our predictor allows MREs to avoid low-yield collections and thereby improve resource management. We integrate this predictor into three state-of-the-art parallel compactors, implemented in the HotSpot JVM, that represent distinct canonical heap layouts. Our empirical evaluation, based on standard Java benchmarks and opensource applications, indicates that inexpensive and accurate yield prediction can improve performance significantly.

Abstract not found

I am deeply grateful to Kathryn McKinley for supporting and mentor-ing me in many ways. Kathryn has provided invaluable technical expertise and feedback even as we worked in new areas. She has been unwaveringly enthusiastic and positive about students and ideas and projects, and she has been a strong advocate, putting my and other students ’ interests first. I en-tered graduate school uncertain about getting a Ph.D., and I leave inspired to pursue an academic career because of Kathryn. Steve Blackburn has been an enthusiastic supporter and has devoted a lot of his time to solving problems and giving advice, both solicited and unso-licited. Steve, Keshav Pingali, Peter Stone, and Emmett Witchel have given helpful feedback and spent a lot of time reading long documents and attending long talks. Vitaly Shmatikov and Steve Keckler have provided valuable advice and mentoring. David Padua and Craig Zilles were supportive advisors when I was a master’s student at the University of Ilinois. The graduate student community at UT has been incredibly support-ive. I am thankful to have Ben Wiedermann, Xianglong Huang, and Milind Kulkarni as friends and colleagues. I am indebted to them and to the fol-lowing friends and colleagues for their technical and personal support: Kar-

Committee: Copyright by

Abstract not found

Copyright © 2011 by

Copyright © 2011 by