• DocumentCode
    572405
  • Title

    Power management of online data-intensive services

  • Author

    Meisner, David ; Sadler, Christopher M. ; Barroso, Luiz André ; Weber, Wolf-Dietrich ; Wenisch, Thomas F.

  • Author_Institution
    Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2011
  • fDate
    4-8 June 2011
  • Firstpage
    319
  • Lastpage
    330
  • Abstract
    Much of the success of the Internet services model can be attributed to the popularity of a class of workloads that we call Online Data-Intensive (OLDI) services. These work-loads perform significant computing over massive data sets per user request but, unlike their offline counterparts (such as MapReduce computations), they require responsiveness in the sub-second time scale at high request rates. Large search products, online advertising, and machine translation are examples of workloads in this class. Although the load in OLDI services can vary widely during the day, their energy consumption sees little variance due to the lack of energy proportionality of the underlying machinery. The scale and latency sensitivity of OLDI workloads also make them a challenging target for power management techniques. We investigate what, if anything, can be done to make OLDI systems more energy-proportional. Specifically, we evaluate the applicability of active and idle low-power modes to reduce the power consumed by the primary server components (processor, memory, and disk), while maintaining tight response time constraints, particularly on 95th-percentile latency. Using Web search as a representative example of this workload class, we first characterize a production Web search workload at cluster-wide scale. We provide a fine-grain characterization and expose the opportunity for power savings using low-power modes of each primary server component. Second, we develop and validate a performance model to evaluate the impact of processor- and memory-based low-power modes on the search latency distribution and consider the benefit of current and foreseeable low-power modes. Our results highlight the challenges of power management for this class of workloads. In contrast to other server workloads, for which idle low-power modes have shown great promise, for OLDI workloads we find that energy-proportionality with acceptable query latency can only be achieved using coordinated, full- system active low-power modes.
  • Keywords
    Internet; pattern clustering; power aware computing; Internet service model; OLDI workloads; coordinated-full-system active low-power modes; energy consumption; energy-proportional OLDI systems; fine-grain characterization; idle low-power modes; latency sensitivity; memory-based low-power mode impact evaluation; online data-intensive services; power consumption reduction; power management techniques; power savings; primary server components; processor-based low-power mode impact evaluation; production Web search workload; query latency; request rates; response time constraints; scale sensitivity; search latency distribution; Abstracts; Servers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Architecture (ISCA), 2011 38th Annual International Symposium on
  • Conference_Location
    San Jose, CA
  • ISSN
    1063-6897
  • Print_ISBN
    978-1-4503-0472-6
  • Type

    conf

  • Filename
    6307768