Logo Logo
Switch Language to German
Li, Lin; Fussenegger, Markus; Cichon, Gordon (2016): A Data Locality and Memory Contention Analysis Method in Embedded NUMA Multi-core Systems. 2016 IEEE 10th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSOC), 21-23 September 2016, Lyon, France.
Full text not available from 'Open Access LMU'.


Data locality in distributed memories has a significant performance impact on NUMA multi-core systems owing to non-uniform memory accesses. In addition, memory contention also influences the performance of multi-core systems. The performance degradation caused by both effects should be analyzed before performance optimization because data locality and memory contention are mutually dependent. A reduction of one effect could cancel performance gains due to another effect. A novel post-processing method based on non-intrusive tracing is proposed in this paper to analyze the performance impact incurred by both data locality and memory contention in a quantitative, comparable way. It makes use of non-intrusive tracing, which has no impact on normal execution and timing. The analysis provides results including data locality and memory contention penalties, which can be used as a reference to improve performance.