• DocumentCode
    1902390
  • Title

    Bandwidth Bandit: Quantitative characterization of memory contention

  • Author

    Eklov, D. ; Nikoleris, N. ; Black-Schaffer, D. ; Hagersten, Erik

  • fYear
    2013
  • fDate
    23-27 Feb. 2013
  • Firstpage
    1
  • Lastpage
    10
  • Abstract
    On multicore processors, co-executing applications compete for shared resources, such as cache capacity and memory bandwidth. This leads to suboptimal resource allocation and can cause substantial performance loss, which makes it important to effectively manage these shared resources. This, however, requires insights into how the applications are impacted by such resource sharing. While there are several methods to analyze the performance impact of cache contention, less attention has been paid to general, quantitative methods for analyzing the impact of contention for memory bandwidth. To this end we introduce the Bandwidth Bandit, a general, quantitative, profiling method for analyzing the performance impact of contention for memory bandwidth on multicore machines. The profiling data captured by the Bandwidth Bandit is presented in a bandwidth graph. This graph accurately captures the measured application´s performance as a function of its available memory bandwidth, and enables us to determine how much the application suffers when its available bandwidth is reduced. To demonstrate the value of this data, we present a case study in which we use the bandwidth graph to analyze the performance impact of memory contention when co-running multiple instances of single threaded application.
  • Keywords
    cache storage; performance evaluation; shared memory systems; bandwidth bandit; bandwidth graph; cache capacity; memory bandwidth; memory contention; multicore machines; multicore processors; profiling method; quantitative characterization; resource sharing; single threaded application; suboptimal resource allocation; Bandwidth; Benchmark testing; Instruction sets; Memory management; Multicore processing; Parallel processing; Resource management; Bandwidth; Caches; Memory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Code Generation and Optimization (CGO), 2013 IEEE/ACM International Symposium on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4673-5524-7
  • Type

    conf

  • DOI
    10.1109/CGO.2013.6494987
  • Filename
    6494987