1. Energy Efficient Prefetching – from models to Implementation 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. Adam Manzanares Ph.D. May 2010.

3. About me Ph.D.’04, U. of Nebraska-Lincoln 04-07, New Mexico Tech 07-10, Auburn University

4. About My Research Group

5. Presentation Outline Motivation Modeling Work DiskSim Modifications Energy Efficient Virtual File System (EEVFS) Parallel Striping Groups in EEVFS Conclusion 6/19/2015 5

6. Motivation EPA Report to Congress on Server and Data Center Energy Efficiency, 2007 6/19/2015 6

7. 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 7

8. 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 8

9. IBM Ultrastar 36Z15 6/19/2015 9 Transfer Rate55 MB/sSpin Down Time: T D 1.5 s Active Power: P A 13.5 WSpin Up Time: T U 10.9 s Idle Power: P I 10.2 WSpin Down Energy: E D 13 J Standby Power: P A 2.5 WSpin Up Energy: E U 135 J Break-Even Time: T BE 15.2 S

10. Prefetching Disk 1 Disk 2 Disk 3 Buffer Disk 6/19/2015 10

11. Why Modeling & Simulation Allows us to determine the potential of our research ideas Can quickly evaluate many simulation parameters Allows us to test architectures and hardware without having the physical resources 6/19/2015 11

12. Modeling & Simulation Work  Developed Mathematical Model ◦ Disk Energy Consumption ◦ Conditions to prefetch  Developed Energy Saving Principles ◦ Investigated cases that exploit the energy saving principles  Implemented model in JAVA based simulator 6/19/2015 12

13. 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 13

14. 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 14

15. Energy Savings Hit Rate 85% 6/19/2015 15

16. State Transitions 6/19/2015 16

17. Parameter Generalizations Larger data sizes produce greater energy savings and less state transitions Increasing the inter-arrival delay increases energy savings More data disks per buffer disks increases energy efficiency High hit rates produce the greatest energy efficiency 6/19/2015 17

18. Modeling & Sim. Summary  Hit Rate, Inter-arrival Delay, & Data Size combine to produce Idle Windows  Transitions important to reduce energy consumption ◦ May increase/decrease to reduce energy consumption  Disk parameters have large impact on energy savings  Model and simulator developed in-house 6/19/2015 18

19. DiskSim Event driven simulator developed at CMU Simulates disks at the block level The simulator has been validated Discrete event based simulator Provides a large amount of statistics Lacks Disk Power Models Ability to simulate large storage systems 6/19/2015 19

20. File System Simulator Large files important to energy savings Popularity of data is also useful Developed a block to file translator Interacts with DiskSim 6/19/2015 20

21. DiskSim with File System Simulator 6/19/2015 21

22. Modified DiskSim Results 6/19/2015 22

23. Modified DiskSim Summary Provides us with accurate disk statistics Only the changes to DiskSim need to be validated Heavily dependent upon disk parameters May miss details that can only be found in implementation 6/19/2015 23

24. 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 24

25. Energy Efficient Virtual File System 6/19/2015 25

26. EEVFS Process Flow 6/19/2015 26

27. 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 27

28. Energy Savings 6/19/2015 28

29. State Transitions 6/19/2015 29

30. Response Times 6/19/2015 30

31. Berkeley Web Trace 6/19/2015 31

32. EEVFS Summary Knowledge of requests assumed and may be hard to come by Performance tied to one of the buffer disks 6/19/2015 32

33. 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 33

34. 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 34

35. 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 35

36. 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 36

37. Measured Results 6/19/2015 37

38. Measured Results 6/19/2015 38

39. Berkeley Web Trace 6/19/2015 39

40. 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 40

41. Parallel Striping Groups 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 41

42. Conclusions Modeling and simulation used to test our ideas –System, Disk, Trace Parameters varied to study their impacts DiskSim Modifications –Added disk power models to DiskSim –Implemented block to file translator Energy Aware Virtual Cluster File System (EEVFS) –Implemented a prototype –Added parallel striping groups to improve the energy efficiency 6/19/2015 42

43. Future Work Improve the EEVFS prototype for production use Run EEVFS on large scale storage system –Investigate scaling effects 6/19/2015 43

44. http://www.auburn.edu/~xzq0001

45. Download the presentation slides

48. http://www.slideshare.net/xqin74

49. Questions