Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Much prior work has shown that the performance enabled by garbage collection (GC) systems is highly dependent upon the behavior of the application as ll as on the available resources. That is, no single GC enables the best performance for all programs and all heap sizes. To address this limitation,  present the design, implementation, and empirical evaluation of a novel Java Virtual Machine (JVM) extension that facilitates dynamic switching beten a number of very different and popular garbage collectors.  also show how to exploit this functionality using annotation-guided GC selection and evaluate the system using a large number of benchmarks. In addition,  implement and evaluate a simple heuristic to investigate the efficacy of switching automatically. Our results show that, on average, our annotation-guided system introduces less than 4% overhead and improves performance by 24% over the worst-performing GC (across heap sizes) and by 7% over always using the popular Generational/Mark-Sep hybrid.
['Sunil Soman', 'Chandra Krintz', 'David F. Bacon']
I am writing a research paper on a idea Dynamic selection of application-specific garbage collectors
[{"from": "human", "value": "I am writing a research paper on a idea Dynamic selection of application-specific garbage collectors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Much prior work has shown that the performance enabled by garbage collection (GC) systems is highly dependent upon the behavior of the application as ll as on the available resources. That is, no single GC enables the best performance for all programs and all heap sizes. To address this limitation,  present the design, implementation, and empirical evaluation of a novel Java Virtual Machine (JVM) extension that facilitates dynamic switching beten a number of very different and popular garbage collectors.  also show how to exploit this functionality using annotation-guided GC selection and evaluate the system using a large number of benchmarks. In addition,  implement and evaluate a simple heuristic to investigate the efficacy of switching automatically. Our results show that, on average, our annotation-guided system introduces less than 4% overhead and improves performance by 24% over the worst-performing GC (across heap sizes) and by 7% over always using the popular Generational/Mark-Sep hybrid."}]