Quantitatively Measuring the Memory Locality Leakage on NUMA Systems Based on Instruction-Based-Sampling

Qiuming Luo, Chengjian Liu, Chang Kong, Ye Cai

Abstract: Sustaining the memory locality is critical for obtaining high performance in NUMA system. But how to identify a locality leakage problem and how to measure the leakage is still open issue. This paper provides an algorithm to quantitatively measure the locality leakage based on the memory trace produced by IBS (Instruction-Based-Sampling). A """"perfect matrix"""" PM is generated from virtual memory address trace, which represents the highest locality pattern. A """"communication matrix"""" CM is obtained from physical memory address trace to describe the actual memory access pattern. The penalty factors are calculated from PM or CM with considering of the hardware NUMA factor. The leakage is measured by the difference between the penalty factors of PM and the penalty factors of CM, which can be used to estimate the performance decrease and guide the optimization. Some experiment results are show to testify the effectiveness and accuracy of our quantitative measurement.