NumaPerf

Abstract

It is extremely challenging to achieve optimal performance of parallel applications on a NUMA architecture, which necessitates the assistance of profiling tools. However, existing NUMA-profiling tools share some similar shortcomings, such as portability, effectiveness, and helpfulness issues. This paper proposes a novel profiling tool–NumaPerf–that overcomes these issues. NumaPerf aims to identify potential performance issues for any NUMA architecture, instead of only on the current hardware. To achieve this, NumaPerf focuses on memory sharing patterns between threads, instead of real remote accesses. NumaPerf further detects potential thread migrations and load imbalance issues that could significantly affect the performance but are omitted by existing profilers. NumaPerf also identifies cache coherence issues separately that may require different fix strategies. Based on our extensive evaluation, NumaPerf can identify more performance issues than any existing tool, while fixing them leads to significant performance speedup.