Thursday, 14 December 2017

Session 3: Performance and Energy Reduction - Part 1

Adaptive Workload Shaping for Power Savings on Disk Drives

Authors:

Xenia Mountrouidou (College of William and Mary)
Alma Riska (College of William and Mary)
Evgenia Smirni (College of William and Mary)

Abstract:

In order to reduce the amount of power consumption in data centers, it is becoming necessary to shut off or slow down disks that are not actively serving user requests. In addition to exploiting disk drive idleness, system features are in place that shape a disk's workload by redirecting portions of it elsewhere, with the goal to expand the periods of idleness and the potential for power savings. In this paper, we propose several workload shaping techniques that determine which part of the working set to copy elsewhere using temporal and spatial access frequencies in the workload. These workload shaping techniques, used within an analytic estimation methodology, enable a fully automated framework that determines on-line for the current workload which, if any, shaping technique to activate such that the power saving benefits are maximized without violating performance targets. Extensive trace-driven evaluation shows that the proposed workload shaping techniques complement each-other with regard to their abilities to enhance idleness in disk drives for a wide range of workload characteristics. This results to added power savings in a data center even when performance targets are stringent and workloads intensive.

DOI: 10.1145/1958746.1958766

Full text: PDF

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Fluid Analysis of Energy Consumption Using Rewards in Massively Parallel Markov Models

Authors:

Anton Stefanek (Imperial College London)
Richard A. Hayden (Imperial College London)
Jeremy T. Bradley (Imperial College London)

Abstract:

Capturing energy consumption directly from a stochastic behavioural model is a computationally expensive process. Using a so-called fluid analysis technique we are able to access accumulated reward measures in much larger scale stochastic systems than has been previously possible.These accumulated rewards are ideal for deriving energy and power consumption from stochastic process models. In previous work, it has been shown how to derive a set of ordinary differential equations (ODEs) whose solutions approximate the moments of component counts in a continuous-time Markov chain(CTMC) described in a stochastic process algebra. In this paper, we show how to extend the method to provide rapid access to moments of accumulated rewards in CTMCs. In addition to measuring the amount of energy used by a system, we are also interested in the time taken to reach a particular level of energy consumption. In reward terms, this is a so-called completion time. In this paper, we are able to use higher moments of rewards to give us access to completion time distributions.

We demonstrate the technique on a model of energy consumption in a client-server system with server failure and hibernation. Moreover, we are able to use these new and rapid techniques to capture the trade-off between energy consumption and service level agreement (SLA) compliance. We use a standard optimisation approach to find the precise configuration of the system which minimises the energy consumption while satisfying an operational response-time quantile.

DOI: 10.1145/1958746.1958767

Full text: PDF

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Assessment of High-Performance Smart Metering for the Web Service Enabled Smart Grid

Authors:

Stamatis Karnouskos (SAP Research)
Per Goncalves da Silva (SAP Research)
Dejan Ilic (SAP Research)

Abstract:

The electricity network is undergoing a significant change towards a more adaptive, intelligent, self-managing, collaborative and information-driven grid. According to the smart grid vision, any electronic device connected to it will be able to communicate its consumed or produced energy almost in real time. Based on the analysis of this newly acquired information, a new generation of services and decision support systems can be realized, enabling more intelligent decisions, and ultimately a more efficient energy system. Therefore, high-performance acquisition of smart metering information from large scale distributed infrastructures is of key importance for the upcoming Internet-based enterprise services and mash-up applications. We have used open source software to build a web service-based advanced metering infrastructure of simulated smart meters, concentrators, and a smart metering platform, all interconnected via web services. We measure in a methodological fashion the performance of the various components of the architecture and evaluate their limitations. Finally we identify key performance indicators that need to be considered when deploying large-scale smart metering systems, and discuss on challenges and directions that arise.

DOI: 10.1145/1958746.1958768

Full text: PDF

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The Design and Development of the Server Efficiency Rating Tool (SERT)

Authors:

Klaus-Dieter Lange (Hewlett-Packard Company)
Michael G. Tricker (Microsoft Corporation)

Abstract:

According to the United States Environmental Protection Agency (US EPA) almost 3% of all electricity consumed within the US in 2010 goes to running datacenters, with the majority of that powering servers and the associated air conditioning systems dedicated to eliminating the heat they produce. The EPA launched the ENERGY STAR® Computer Server program in May 2009, intended to deliver information to better enable server purchasing decisions based on projected power consumption.

The Server Efficiency Rating Tool (SERT) has been developed by the Standard Performance Evaluation Corporation (SPEC) SPECpower committee to address the EPA requirements for Version 2 of the ENERGY STAR server program. Unlike many tools sourced from the SPEC organization the SERT is not intended to be a benchmark, and for Version 2 does not offer a single score model. Instead it produces detailed information regarding the influence of CPU, memory, network and storage I/O configurations on overall server power consumption.

This paper describes the design and development of the SERT, including discussion of the collaborative nature of working with the EPA and the various industry stakeholders involved in the design, review and development process. Many of the core ideas behind SERT were derived from the SPECpower_ssj2008 and other SPEC-developed benchmarks, and this paper illustrates where ideas and code were shared, as well as where new thinking resulted in entirely new solutions. It also includes thoughts for the future, as the ENERGY STAR server program continues to evolve and the SERT will evolve with it.

DOI: 10.1145/1958746.1958769

Full text: PDF

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Metric-Based Selection of Timer Methods for Accurate Measurements

Authors:

Michael Kuperberg (Karlsruhe Institute of Technology)
Martin Krogmann (Karlsruhe Institute of Technology)
Ralf Reussner (Karlsruhe Institute of Technology)

Abstract:

Performance measurements are often concerned with accurate recording of timing values, which requires timer methods of high quality. Evaluating the quality of a given timer method or performance counter involves analysing several properties, such as accuracy, invocation cost and timer stability. These properties are metrics with platform-dependent values, and ranking and selecting timer methods requires comparisons using multidimensional metric sets, which make the comparisons ambiguous and unnecessary complex. To solve this problem, this paper proposes a new unified metric that allows for a simpler comparison. The one-dimensional metric is designed to capture fine-granular differences between timer methods, and normalises accuracy and other quality attributes by using CPU cycles instead of time units. The proposed metric is evaluated on all timer methods provided by Java and .NET platform APIs.

DOI: 10.1145/1958746.1958823

Full text: PDF

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