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

    • 1. 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
    • 2. My Research Group: 2011
    • 3. 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. 4
      6/10/2011
      Electricity Usage in Data Centers
      Annual Data Center Electricity Usage and Electricity Price increase Every year
    • 5. 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
    • 6. Electrical Cost of Data Centers
      • Using 2010 Trends Scenario
      • 7. Server and Data Centers Consume 110 Billion kWh per year
      • 8. Assume average commercial end user is charged 9.46 kWh
      • 9. 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.
    • 10. 7
      6/10/2011
      Energy Consumption of Disks
    • 11. Power States of Disks
      Active State: high energy consumption
      Active
      Standby
      State transition penalty
      Standby State: low energy consumption
      8
    • 12. A Hard Disk Drive
      A10000RPM Hard Drive may take 10.9 seconds to wake up!
      9
    • 13. Parallel Disks
      Performance
      Energy Efficiency
    • 14. Challanges
      Performance Oriented:
      • Best Performance
      • 15. Huge Electricity Bills
      Energy Efficiency Oriented:
      • Worst Performance?
      • 16. Small Electricity Bills
    • Basic Idea of BUD
      • Keep Disks in Standby mode as long as possible
      • 17. Reduce Status Transitions as many as possible
      12
    • 18. IBM Ultrastar 36Z15
      6/10/2011
      13
    • 19. A Parallel Disk System with a Write Buffer Disk
    • 20. The BUD Architecture
      Data Disks can serve requests without buffer disks when workload is high
      15
    • 21. Auburn University
      16
      Sum of Requests in Buffer (SRB)
      • SRB is Number of the buffered requests targetingat the same data disk.
      • 22. SRB is set by administrators
      • 23. 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
    • 24. Example
      Buffer Disk
      Requests Queue
      18
    • 25. Auburn University
      Xiaojun Ruan
      19
      From Design to Simulation
    • 26. Simulation Environment
      20
    • 27. Auburn University
      21
      Workloads
    • 28. Impact of SRB—Low Workload, UltraStar
      22
    • 29. Auburn University
      Xiaojun Ruan
      23
      Non-Buffer Experiments
    • 30. Auburn University
      24
      BUD with IBM 40GNX TravalStar
    • 31. Buffer Disk Number and Workload-- UltraStar
      25
    • 32. Auburn University
      26
      Energy Consumption
      E = Active Energy Consumption + Standby Energy Consumption + Transition Penalty
    • 33. Auburn University
      Xiaojun Ruan
      27
      From Simulation to
      Real Implementation
    • 34. An Energy-Efficient Cluster Storage System
      28
    • 35. Implementation (no buffer disks)
      29
    • 36. Implementation (with buffer-disks)
      30
    • 37. Experimental Design
      • Disk Category I/O Node 1
      • 38. Data Disk 1: WesternDigital 400, 20GB
      • 39. Data Disk 2: WesternDigital 400, 20GB
      • 40. Disk Category I/O Node 2
      • 41. Data Disk 1: WesternDigital 400, 20GB
      • 42. Data Disk 2: Maxtor D740X-6L, 20GB
      31
    • 43. Experimental Design
      • Disk Category I/O Node 1
      • 44. Buffer Disk: Maxtor DiamondMax Plus 9
      • 45. Data Disk 1: WesternDigital 400, 20GB
      • 46. Data Disk 2: WesternDigital 400, 20GB
      • 47. Disk Category I/O Node 2
      • 48. Buffer Disk: Seagate Barracuda 7200
      • 49. Data Disk 1: WesternDigital 400, 20GB
      • 50. Data Disk 2: Maxtor D740X-6L, 20GB
      32
    • 51. 33
    • 52. 34
      idle time gap is 200s
      idle time gap is 100s
    • 53. Previous Research
      GreenFS
      [ACM EuroSys 2008]
      Massive Arrays of Idle Disks
      [SC 2002]
      Popular Data Concentration
      [ACM ICS 2004]
      35
      6/10/2011
    • 54. Download the presentation slideshttp://www.slideshare.net/xqin74
      Google: slideshare Xiao Qin
      ‹#›
    • 55. http://www.eng.auburn.edu/~xqin
    • 56. My webpagehttp://www.eng.auburn.edu/~xqin
    • 57. Download Slides at slidesharehttp://www.slideshare.net/xqin74
    • 58. Auburn University
      40
      Questions?

    ×