AS-GC: An Efficient Generational Garbage Collector for Java Application Servers

Xian, Feng; Srisa-an, Witawas; Jia, ChengHuan; Jiang, Hong

doi:10.1007/978-3-540-73589-2_7

Cited by 6 publications

(8 citation statements)

References 28 publications

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“…From the object lifespan perspective, inefficient GC due to scheduling can make the lifespans of objects appear to be longer. In fact, we have observed the increasing lifespan phenomenon in our previous study of a SPECjAppServer2004 [32,31].…”

Section: Motivationmentioning

confidence: 83%

“…We also configured the size of the mature space to be twice as large as that of the nursery space. Our previous study showed that this value yields the best performance for multithreaded server applications [32,31]. We also evaluated the sensitivities of our algorithms to heap sizes and garbage collection policies.…”

Section: Discussionmentioning

confidence: 98%

“…We discovered that lifespans become much longer as the number of active threads becomes larger [31]. To better understand the reason for such behavior, we revisit an observation made by Wilson and Moher [28,30].…”

Section: Motivationmentioning

confidence: 92%

“…Further investigation reveals that thread scheduling policies play a major role in causing the object lifespans to increase [31]. Currently, most modern operating systems employ some forms of preemptive round robin scheduling policies based on time-quantum.…”

Section: Introductionmentioning

confidence: 99%

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Allocation-phase aware thread scheduling policies to improve garbage collection performance

Xian

Srisa-an

Jiang

2007

Proceedings of the 6th International Symposium on Memory Management

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Past studies have shown that objects are created and then die in phases. Thus, one way to sustain good garbage collection efficiency is to have a large enough heap to allow many allocation phases to complete and most of the objects to die before invoking garbage collection. However, such an operating environment is hard to maintain in large multithreaded applications because most typical time-sharing schedulers are not allocation-phase cognizant; i.e., they often schedule threads in a way that prevents them from completing their allocation phases quickly. Thus, when garbage collection is invoked, most allocation phases have yet to be completed, resulting in poor collection efficiency.We introduce two new scheduling strategies, LARF (lower allocation rate first) and MQRR (memory-quantum round robin) designed to be allocation-phase aware by assigning higher execution priority to threads in computationoriented phases. The simulation results show that the reductions of the garbage collection time in a generational collector can range from 0%-27% when compare to a round robin scheduler. The reductions of the overall execution time and the average thread turnaround time range from -0.1%-3% and -0.1%-13%, respectively.

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Section: Motivationmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 98%

Section: Motivationmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Allocation-phase aware thread scheduling policies to improve garbage collection performance

Xian

Srisa-an

Jiang

2007

Proceedings of the 6th International Symposium on Memory Management

Self Cite

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“…Xian et. al [24][25][26][27] design several types of schedulers for Java applications, including object allocation phase aware and contention aware schedulers. The allocation phase aware scheduler schedules the threads according to their allocation rate or preempt threads with the memory consumption instead of the running time which is used in the CFS.…”

Section: Related Workmentioning

confidence: 99%

Exploiting FIFO Scheduler to Improve Parallel Garbage Collection Performance

Qian

Srisa-an

Seth

et al. 2016

Proceedings of The12th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments

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Recent studies have found that parallel garbage collection performs worse with more CPUs and more collector threads. As part of this work, we further investigate this phenomenon and find that poor scalability is worst in highly scalable Java applications. Our investigation to find the causes clearly reveals that efficient multi-threading in an application can prolong the average object lifespan, which results in less effective garbage collection. We also find that prolonging lifespan is the direct result of Linux's Completely Fair Scheduler due to its round-robin like behavior that can increase the heap contention between the application threads. Instead, if we use pseudo first-in-first-out to schedule application threads in large multicore systems, the garbage collection scalability is significantly improved while the time spent in garbage collection is reduced by as much as 21%. The average execution time of the 24 Java applications used in our study is also reduced by 11%. Based on this observation, we propose two approaches to optimally select scheduling policies based on application scalability profile. Our first approach uses the profile information from one execution to tune the subsequent executions. Our second approach dynamically collects profile information and performs policy selection during execution.

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TRINI: an adaptive load balancing strategy based on garbage collection for clustered Java systems

et al. 2016

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Summary Nowadays, clustered environments are commonly used in high‐performance computing and enterprise‐level applications to achieve faster response time and higher throughput than single machine environments. Nevertheless, how to effectively manage the workloads in these clusters has become a new challenge. As a load balancer is typically used to distribute the workload among the cluster's nodes, multiple research efforts have concentrated on enhancing the capabilities of load balancers. Our previous work presented a novel adaptive load balancing strategy (TRINI) that improves the performance of a clustered Java system by avoiding the performance impacts of major garbage collection, which is an important cause of performance degradation in Java. The aim of this paper is to strengthen the validation of TRINI by extending its experimental evaluation in terms of generality, scalability and reliability. Our results have shown that TRINI can achieve significant performance improvements, as well as a consistent behaviour, when it is applied to a set of commonly used load balancing algorithms, demonstrating its generality. TRINI also proved to be scalable across different cluster sizes, as its performance improvements did not noticeably degrade when increasing the cluster size. Finally, TRINI exhibited reliable behaviour over extended time periods, introducing only a small overhead to the cluster in such conditions. These results offer practitioners a valuable reference regarding the benefits that a load balancing strategy, based on garbage collection, can bring to a clustered Java system. Copyright © 2016 John Wiley & Sons, Ltd.

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AS-GC: An Efficient Generational Garbage Collector for Java Application Servers

Cited by 6 publications

References 28 publications

Allocation-phase aware thread scheduling policies to improve garbage collection performance

Allocation-phase aware thread scheduling policies to improve garbage collection performance

Exploiting FIFO Scheduler to Improve Parallel Garbage Collection Performance

TRINI: an adaptive load balancing strategy based on garbage collection for clustered Java systems

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