Power management of online data-intensive services
- 4 June 2011
- journal article
- conference paper
- Published by Association for Computing Machinery (ACM) in ACM SIGARCH Computer Architecture News
- Vol. 39 (3), 319-330
- https://doi.org/10.1145/2024723.2000103
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 workloads 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
This publication has 18 references indexed in Scilit:
- MemScalePublished by Association for Computing Machinery (ACM) ,2011
- The Case for Energy-Proportional ComputingComputer, 2007
- Limiting the power consumption of main memoryPublished by Association for Computing Machinery (ACM) ,2007
- Power provisioning for a warehouse-sized computerPublished by Association for Computing Machinery (ACM) ,2007
- The Synergy Between Power-Aware Memory Systems and Processor Voltage ScalingLecture Notes in Computer Science, 2005
- Conserving disk energy in network serversPublished by Association for Computing Machinery (ACM) ,2003
- Web search for a planet: the google cluster architectureIEEE Micro, 2003
- DRPMPublished by Association for Computing Machinery (ACM) ,2003
- Managing energy and server resources in hosting centersPublished by Association for Computing Machinery (ACM) ,2001
- Hardware and software techniques for controlling DRAM power modesIEEE Transactions on Computers, 2001