Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Information on a particular behavioral aspect of a program can be useful to know about the performance bottlenecks and can be utilized further to improve the performance of the system. It is observed that contention for shared L2 cache beten programs running on a Multi-Core Processor (MCP) is one of the performance bottlenecks. The utilization of the L2 cache by a program, while sharing it with others on a MCP is a metric of interest to frame policies that reduce contention. In this work  investigate the ability of some of the machine learning algorithms to predict the solo run L2 cache stress of a running program on Intel quad-core Xeon X5482 processor. Data collected from hardware performance counters of Intel quad-core Xeon X5482 processor re utilized to derive the attributes to train the machine learning algorithms.  observed that the best performing machine learning algorithm in this context is Model tree (M5’), follod by Artificial Neural Networks (ANN).
['Jitendra Kumar Rai', 'Atul Negi', 'Rajeev Wankar', 'K.D. Nayak']
I am writing a research paper on a idea On Prediction Accuracy of Machine Learning Algorithms for Characterizing Shared L2 Cache Behavior of Programs on Multicore Processors
[{"from": "human", "value": "I am writing a research paper on a idea On Prediction Accuracy of Machine Learning Algorithms for Characterizing Shared L2 Cache Behavior of Programs on Multicore Processors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Information on a particular behavioral aspect of a program can be useful to know about the performance bottlenecks and can be utilized further to improve the performance of the system. It is observed that contention for shared L2 cache beten programs running on a Multi-Core Processor (MCP) is one of the performance bottlenecks. The utilization of the L2 cache by a program, while sharing it with others on a MCP is a metric of interest to frame policies that reduce contention. In this work  investigate the ability of some of the machine learning algorithms to predict the solo run L2 cache stress of a running program on Intel quad-core Xeon X5482 processor. Data collected from hardware performance counters of Intel quad-core Xeon X5482 processor re utilized to derive the attributes to train the machine learning algorithms.  observed that the best performing machine learning algorithm in this context is Model tree (M5\u2019), follod by Artificial Neural Networks (ANN)."}]