Low Cost Working Set Size Tracking

نویسندگان

  • Weiming Zhao
  • Xinxin Jin
  • Zhenlin Wang
  • Xiaolin Wang
  • Yingwei Luo
  • Xiaoming Li
چکیده

Efficient memory resource management requires knowledge of the memory demands of applications or systems at runtime. A widely proposed approach is to construct an LRU-based miss ratio curve (MRC), which provides not only the current working set size (WSS) but also the relationship between performance and target memory allocation size. Unfortunately, the cost of LRUMRC monitoring is nontrivial. Although optimized with AVLtree based LRU structure and dynamic hot set sizing, the overhead is still as high as 16% on average. Based on a key insight that for most programs the WSSs are stable most of the time, we design an intermittent tracking scheme, which can temporarily turn off memory tracking when memory demands are predicted to be stable. With the assistance of hardware performance counters, memory tracking can be turned on again if a significant change in memory demands is expected. Experimental results show that, by using this intermittent tracking design, memory tracking can be turned off for 82% of the execution time while the accuracy loss is no more than 4%. More importantly, this design is orthogonal to existing optimizing techniques, such as AVL-tree based LRU structure and dynamic hot set sizing. By combining the three approaches, the mean overhead is lowered to only 2%. We show that when applied to memory balancing for virtual machines, our scheme brings a speedup of 1.85.

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تاریخ انتشار 2011