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Energy Efficient Prefetching with Buffer Disks for Cluster File Systems 6/19/2015 1 Adam Manzanares and Xiao Qin Department of Computer Science and Software.

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Presentation on theme: "Energy Efficient Prefetching with Buffer Disks for Cluster File Systems 6/19/2015 1 Adam Manzanares and Xiao Qin Department of Computer Science and Software."— Presentation transcript:

1 Energy Efficient Prefetching with Buffer Disks for Cluster File Systems 6/19/2015 1 Adam Manzanares and Xiao Qin Department of Computer Science and Software Engineering Auburn University http://www.eng.auburn.edu/~xqin xqin@auburn.edu

2 Motivation  Using 2010 Historical 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 6/19/2015 2

3 Buffer Disk Architecture RAM Buffer m buffer disks n data disks Buffer Disk Controller Data Partitioning Security Model Load Balancing Power Management Prefetching Disk Requests Energy-Related Reliability Model 6/19/2015 3

4 Energy Saving Principles  Energy Saving Principle One ◦ Increase the length and number of idle periods larger than the disk break-even time T BE  Energy Saving Principle Two ◦ Reduce the number of power-state transitions 6/19/2015 4

5 Paramaters Tested ParameterValues Data Size1, 5, 10, 25 MB # of Data Disks4, 8, 12 Inter-arrival Delay0, 0.1, 0.5, 1 S Hit Rate85, 90, 95, 100% 6/19/2015 5

6 Energy Savings Hit Rate 85% 6/19/2015 6

7 State Transitions 6/19/2015 7

8 Why a Cluster File System Block level prefetching difficult Natural place to track file accesses Control placement of data among storage nodes, and data disks Tiered approach simplifies management of files and disk states Eliminates some shortcomings of modeling and simulation 6/19/2015 8

9 Energy Efficient Virtual File System 6/19/2015 9

10 EEVFS Process Flow 6/19/2015 10

11 EEVFS Testbed ParameterStorage ServerStorage Node Type 1 Storage Node Type 2 CPUP4 2.0 GHzP4 3.2 GHzP4 2.4 GHz Memory (MB)20001000512 Network Interconnect 1000 100 Disk TypeSATAATA/133 Disk Capacity120 GB80 GB Disk Bandwidth100 MB/s58 MB/s34 MB/s 6/19/2015 11

12 Energy Savings 6/19/2015 12

13 State Transitions 6/19/2015 13

14 Response Times 6/19/2015 14

15 Berkeley Web Trace 6/19/2015 15

16 EEVFS Summary Knowledge of requests assumed and may be hard to come by Performance tied to one of the buffer disks 6/19/2015 16

17 Parallel Striping Groups Disk 1 Disk 2 Group 1 Buffer Disk Storage Node 1 Disk 3 Disk 4 Buffer Disk Storage Node 2 Disk 5 Disk 6 Group 2 Buffer Disk Storage Node 3 Disk 7 Disk 8 Buffer Disk Storage Node 4 File 1File 2File 3File 4 6/19/2015 17

18 Striping Within a Group Disk 1 Disk 2 Group 1 Buffer Disk Storage Node 1 Disk 3 Disk 4 Buffer Disk Storage Node 2 13579468 46813579 10 1 2 1 2 File 1 File 2 2 2 6/19/2015 18

19 Striping Within a Group Number of disks in a group can be matched to nearest bottleneck Striping within the group maintains relatively high performance Allows us to use a buffer disk for each storage node, while still maintaining file striping level 6/19/2015 19

20 Testbed ParameterStorage ServerStorage Node CPUCeleron 2.2 GHz Memory (MB)2000 Network Interconnect 1000 Disk TypeSATA Disk Capacity160 GB480 GB Disk Bandwidth126 MB/s 6/19/2015 20

21 Measured Results 6/19/2015 21

22 Measured Results 6/19/2015 22

23 Berkeley Web Trace 6/19/2015 23

24 Response Time Comparison Energy efficiency is slightly improved Response time gain is significant ParameterStripingNo Striping Energy Consumption (J)2,088,1132,100,243 Response Time (S)2.7813.87 6/19/2015 24

25 Summary Improves the energy efficiency and performance of a storage system Designed to scale –Needs to be tested on large scale storage system 6/19/2015 25

26 Future Work Improve the EEVFS prototype for production use Run EEVFS on large scale storage system –Investigate scaling effects 6/19/2015 26

27 Questions http://www.eng.auburn.edu/~xqin/presentations


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