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15
Evaluating Performance and Energy in File System Server Workloads
"... Recently, power has emerged as a critical factor in designing components of storage systems, especially for power-hungry data centers. While there is some research into power-aware storage stack components, there are no systematic studies evaluating each component’s impact separately. This paper eva ..."
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Recently, power has emerged as a critical factor in designing components of storage systems, especially for power-hungry data centers. While there is some research into power-aware storage stack components, there are no systematic studies evaluating each component’s impact separately. This paper evaluates the file system’s impact on energy consumption and performance. We studied several popular Linux file systems, with various mount and format options, using the FileBench workload generator to emulate four server workloads: Web, database, mail, and file server. In case of a server node consisting of a single disk, CPU power generally exceeds diskpower consumption. However, file system design, implementation, and available features have a significant effect on CPU/disk utilization, and hence on performance and power. We discovered that default file system options are often suboptimal, and even poor. We show that a careful matching of expected workloads to file system types and options can improve power-performance efficiency by a factor ranging from 1.05 to 9.4 times. 1
Energy Proportionality for Storage: Impact and Feasibility
"... (in alphabetical order) This paper highlights the growing importance of storage energy consumption in a typical data center, and asserts that storage energy research should drive towards a vision of energy proportionality for achieving significant energy savings. Our analysis of real-world enterpris ..."
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(in alphabetical order) This paper highlights the growing importance of storage energy consumption in a typical data center, and asserts that storage energy research should drive towards a vision of energy proportionality for achieving significant energy savings. Our analysis of real-world enterprise workloads shows a potential energy reduction of 40-75% using an ideally proportional system. We then present a preliminary analysis of appropriate techniques to achieve proportionality, chosen to match both application requirements and workload characteristics. Based on the techniques we have identified, we believe that energy proportionality is achievable in storage systems at a time scale that will make sense in real world environments. 1
A Survey on Techniques for Improving the Energy Efficiency of Large Scale Distributed Systems
"... The great amounts of energy consumed by large-scale computing and network systems, such as data centers and supercomputers, have been a major source of concern in a society increasingly reliant on information technology. Trying to tackle this issue, the research community and industry have proposed ..."
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Cited by 10 (1 self)
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The great amounts of energy consumed by large-scale computing and network systems, such as data centers and supercomputers, have been a major source of concern in a society increasingly reliant on information technology. Trying to tackle this issue, the research community and industry have proposed a myriad of techniques to curb the energy consumed by IT systems. This article surveys techniques and solutions that aim to improve the energy efficiency of computing and network resources. It discusses methods to evaluate and model the energy consumed by these resources, and describes techniques that operate at a distributed system level, trying to improve aspects such as resource allocation, scheduling and network traffic management. This work aims to review the state of the art on energy efficiency and to foster research on schemes to make network and computing resources more efficient.
Green Cloud computing and Environmental Sustainability
"... Abstract: Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. High energy cons ..."
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Abstract: Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high operational cost, which reduces the profit margin of Cloud providers, but also leads to high carbon emissions which is not environmentally friendly. Hence, energy-efficient solutions are required to minimize the impact of Cloud computing on the environment. In order to design such solutions, deep analysis of Cloud is required with respect to their power efficiency. Thus, in this chapter, we discuss various elements of Clouds which contribute to the total energy consumption and how it is addressed in the literature. We also discuss the implication of these solutions for future research directions to enable green Cloud computing. The chapter also explains the role of Cloud users in achieving this goal. 1.
Modeling the performance and energy of storage arrays
- in Proceedings of the International Conference on Green Computing, ser. GREENCOMP ’10
"... Abstract—We propose a novel framework for evaluating techniques for power optimization in storage. Given an arbitrary trace of disk requests, we split it into short time intervals, extract a set of simple statistics for each interval, and apply an analytical model to those statistics to obtain accur ..."
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Abstract—We propose a novel framework for evaluating techniques for power optimization in storage. Given an arbitrary trace of disk requests, we split it into short time intervals, extract a set of simple statistics for each interval, and apply an analytical model to those statistics to obtain accurate information regarding the performance and energy characteristics of the system for that workload. The key abstraction used in our analytical model is the run-length-a single sequential run of requests at the disk level. Using this abstraction, the model is able to account for arbitrary interactions of random and sequential I/Os in the context of a RAID array, and obtain accurate results with less effort than a detailed individual request-level simulation. Various layout and migration policies aimed at power conservation can be easily expressed as transformations on this set of statistics for each time interval. We demonstrate the efficacy of our framework by using it to evaluate PARAID, a recently proposed technique for power optimization in storage arrays. We show that the performance and power predicted by the model under the migration and layout policies of PARAID accurately match the results of a detailed simulation of the system. The analytic model allows us to identify key parameters that affect PARAID performance, and propose an enhancement to the layout of data in PARAID which we show to perform superior to the original technique. We use both the analytic model and detailed simulations to illustrate the benefit of our new layout. This also demonstrates the significant simplicity of evaluating a new technique by applying a high-level model to the extracted trace statistics, compared to the current alternative of either implementing the new technique or simulating it at the level of individual requests. I.
Thermal modeling of hybrid storage clusters
- Journal of Signal Processing Systems
"... Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript ve ..."
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Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”.
MIND: A Black-Box Energy Consumption Model for Disk Arrays
"... Abstract—Energy consumption is becoming a growing concern in data centers. Many energy-conservation techniques have been proposed to address this problem. However, an integrated method is still needed to evaluate energy efficiency of storage systems and various power conservation techniques. Extensi ..."
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Abstract—Energy consumption is becoming a growing concern in data centers. Many energy-conservation techniques have been proposed to address this problem. However, an integrated method is still needed to evaluate energy efficiency of storage systems and various power conservation techniques. Extensive measurements of different workloads on storage systems are often very timeconsuming and require expensive equipments. We have analyzed changing characteristics such as power and performance of stand-alone disks and RAID arrays, and then defined MIND as a black box power model for RAID arrays. MIND is devised to quantitatively measure the power consumption of redundant disk arrays running different workloads in a variety of execution modes. In MIND, we define five modes (idle, standby, and several types of access) and four actions, to precisely characterize power states and changes of RAID arrays. In addition, we develop corresponding metrics for each mode and action, and then integrate the model and a measurement algorithm into a popular trace tool – blktrace. With these features, we are able to run different IO traces on large-scale storage systems with power conservation techniques. Accurate energy consumption and performance statistics are then collected to evaluate energy efficiency of storage system designs and power conservation techniques. Our experiments running both synthetic and realworld workloads on enterprise RAID arrays show that MIND can estimate power consumptions of disk arrays with an error rate less than 2%. Index Terms—Energy Consumption, Disk Arrays, Black-Box I.
Leveraging Disk Drive Acoustic Modes for Power Management
, 2010
"... Reduction of disk drive power consumption is a challenging task, particularly since the most prevalent way of achieving it, powering down idle disks, has many undesirable side-effects. Some hard disk drives support acoustic modes, meaning they can be configured to reduce the acceleration and velocit ..."
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Reduction of disk drive power consumption is a challenging task, particularly since the most prevalent way of achieving it, powering down idle disks, has many undesirable side-effects. Some hard disk drives support acoustic modes, meaning they can be configured to reduce the acceleration and velocity of the disk head. This reduces instantaneous power consumption but sacrifices performance. As a result, input/output (I/O) operations run longer at reduced power. This is useful for power capping since it causes significant reduction in peak power consumption of the disks. We conducted experiments on several disk drives that support acoustic management. Most of these disk drives support only two modes- quiet and normal. We ran different I/O workloads, including SPC-1 to simulate a real-world online transaction processing workload. We found that the reduction in peak power can reach up to 23 % when using quiet mode. We show that for some workloads this translates into a reduction of 12.5 % in overall energy consumption. In other workloads we encountered the opposite phenomenon-an increase of more than 6 % in the overall energy consumption.
Energy Efficiency for Ultrascale Systems: Challenges and Trends from Nesus Project
"... c © The Authors 2015. This paper is published with open access at SuperFri.org Energy consumption is one of the main limiting factors for designing and deploying ultrascale systems. Therefore, this paper presents challenges and trends associated with energy efficiency for ultrascale systems based on ..."
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c © The Authors 2015. This paper is published with open access at SuperFri.org Energy consumption is one of the main limiting factors for designing and deploying ultrascale systems. Therefore, this paper presents challenges and trends associated with energy efficiency for ultrascale systems based on current activities of the working group on ”Energy Efficiency ” in the European COST Action Nesus IC1305. The analysis contains major areas that are related to studies of energy efficiency in ultrascale systems: heterogeneous and low power hardware architec-tures, power monitoring at large scale, modeling and simulation of ultrascale systems, energy-aware scheduling and resource management, and energy-efficient application design.
