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BUDW: Energy-Efficient Parallel Storage Systems with Write-Buffer Disks
 

BUDW: Energy-Efficient Parallel Storage Systems with Write-Buffer Disks

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A critical challenge with modern parallel I/O systems is that parallel disks consume a significant amount of energy in servers and high-performance computers. To conserve energy consumption in ...

A critical challenge with modern parallel I/O systems is that parallel disks consume a significant amount of energy in servers and high-performance computers. To conserve energy consumption in parallel I/O systems, one can immediately spin down disks when disk are idle; however, spinning down disks might not be able to produce energy savings due to penalties of spinning operations. Unlike powering up CPUs, spinning down and up disks need physical movements. Therefore, energy savings provided by spinning down operations must offset energy penalties of the disk spinning operations. To reduce the penalties incurred by disk spinning operations, we describe in this talk an approach to conserving energy of parallel I/O systems with write buffer disks, which are used to accumulate small writes using a log file system. Data sets buffered in the log file system can be transferred to target data disks in a batch way. Thus, buffer disks aim to serve a majority of incoming write requests, attempting to reduce the large number of disk spinning operations by keeping data disks in standby for long period times. Interestingly, the write buffer disks not only can achieve high energy efficiency in parallel I/O systems, but also can shorten response times of write requests. To evaluate the performance and energy efficiency of our parallel I/O systems with buffer disks, we implemented a prototype using a cluster storage system as a testbed. Experimental results show that under light and moderate I/O load, buffer disks can be employed to significantly reduce energy dissipation in parallel I/O systems without adverse impacts on I/O performance.

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  • Web Servers they account for 24% of the energy, 77% proxy server, 27% in data center
  • , then spin the data disk on, otherwise we always keep data disks in standby mode.
  • SRB is small, transfer data from buffer disk to data disk for too many times. Small SRB, more spin up and spin down times.
  • Trend is similar, but ultrastar penalty is higher
  • MAID:GreenFS:Benefits: low energy cost, Flaws: low capacity, low reliability

BUDW: Energy-Efficient Parallel Storage Systems with Write-Buffer Disks BUDW: Energy-Efficient Parallel Storage Systems with Write-Buffer Disks Presentation Transcript

  • Energy-Efficient Parallel Storage Systems with Write-Buffer Disks
    XiaojunRuan and Xiao Qin
    Computer Science and Software Engineering
    Samuel Ginn College of Engineering
    Auburn University
  • My Research Group: 2011
  • Overview of the Project
    Energy Efficiency
    Security
    Solid State Drives
    Performance of
    Secure Disk Systems
    [IEEE NAS09]
    Design, Model,
    Simulate, And Evaluate
    Disk Systems with
    Buffer Disks
    [ACM SAC09][ICPP09]
    Enhancing Internal
    Parallelism of SSDs
    [To Be Submitted11]
    Message Passing
    Interface with
    Enhanced Security
    [IPCCC 2010]
    Energy-Efficient
    Distributed Storage
    Systems [IPCCC10]
    Energy-Efficient
    Dynamic Voltage
    Scaling[ICCCN07]
    Xiaojun Ruan
    3
    BUD
  • 4
    6/10/2011
    Electricity Usage in Data Centers
    Annual Data Center Electricity Usage and Electricity Price increase Every year
  • The average power consumption of TOP10 supercomputing systems is 1.32 Mwatt.
    Dell’s Texas Data Center
    5
    6/10/2011
    Energy Efficiency of Supercomputers
  • Electrical Cost of Data Centers
    • Using 2010 Trends Scenario
    • Server and Data Centers Consume 110 Billion kWh per year
    • Assume average commercial end user is charged 9.46 kWh
    • Disk systems can account for 27% of the energy cost of data centers
    6/10/2011
    6
    Server and data centers may have an electrical cost of 10.4 billion dollars.
  • 7
    6/10/2011
    Energy Consumption of Disks
  • Power States of Disks
    Active State: high energy consumption
    Active
    Standby
    State transition penalty
    Standby State: low energy consumption
    8
  • A Hard Disk Drive
    A10000RPM Hard Drive may take 10.9 seconds to wake up!
    9
  • Parallel Disks
    Performance
    Energy Efficiency
  • Challanges
    Performance Oriented:
    • Best Performance
    • Huge Electricity Bills
    Energy Efficiency Oriented:
    • Worst Performance?
    • Small Electricity Bills
  • Basic Idea of BUD
    • Keep Disks in Standby mode as long as possible
    • Reduce Status Transitions as many as possible
    12
  • IBM Ultrastar 36Z15
    6/10/2011
    13
  • A Parallel Disk System with a Write Buffer Disk
  • The BUD Architecture
    Data Disks can serve requests without buffer disks when workload is high
    15
  • Auburn University
    16
    Sum of Requests in Buffer (SRB)
    • SRB is Number of the buffered requests targetingat the same data disk.
    • SRB is set by administrators
    • Once SRB is satisfied, spin up the targeted data disk, dump all those data, then spin the disk down.
  • Scheduling Strategy
    To buffer enough requests targeting at the same data disk
    DynAmic Request Allocation algorithm for Writes
    17
  • Example
    Buffer Disk
    Requests Queue
    18
  • Auburn University
    Xiaojun Ruan
    19
    From Design to Simulation
  • Simulation Environment
    20
  • Auburn University
    21
    Workloads
  • Impact of SRB—Low Workload, UltraStar
    22
  • Auburn University
    Xiaojun Ruan
    23
    Non-Buffer Experiments
  • Auburn University
    24
    BUD with IBM 40GNX TravalStar
  • Buffer Disk Number and Workload-- UltraStar
    25
  • Auburn University
    26
    Energy Consumption
    E = Active Energy Consumption + Standby Energy Consumption + Transition Penalty
  • Auburn University
    Xiaojun Ruan
    27
    From Simulation to
    Real Implementation
  • An Energy-Efficient Cluster Storage System
    28
  • Implementation (no buffer disks)
    29
  • Implementation (with buffer-disks)
    30
  • Experimental Design
    • Disk Category I/O Node 1
    • Data Disk 1: WesternDigital 400, 20GB
    • Data Disk 2: WesternDigital 400, 20GB
    • Disk Category I/O Node 2
    • Data Disk 1: WesternDigital 400, 20GB
    • Data Disk 2: Maxtor D740X-6L, 20GB
    31
  • Experimental Design
    • Disk Category I/O Node 1
    • Buffer Disk: Maxtor DiamondMax Plus 9
    • Data Disk 1: WesternDigital 400, 20GB
    • Data Disk 2: WesternDigital 400, 20GB
    • Disk Category I/O Node 2
    • Buffer Disk: Seagate Barracuda 7200
    • Data Disk 1: WesternDigital 400, 20GB
    • Data Disk 2: Maxtor D740X-6L, 20GB
    32
  • 33
  • 34
    idle time gap is 200s
    idle time gap is 100s
  • Previous Research
    GreenFS
    [ACM EuroSys 2008]
    Massive Arrays of Idle Disks
    [SC 2002]
    Popular Data Concentration
    [ACM ICS 2004]
    35
    6/10/2011
  • Download the presentation slideshttp://www.slideshare.net/xqin74
    Google: slideshare Xiao Qin
    ‹#›
  • http://www.eng.auburn.edu/~xqin
  • My webpagehttp://www.eng.auburn.edu/~xqin
  • Download Slides at slidesharehttp://www.slideshare.net/xqin74
  • Auburn University
    40
    Questions?