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Energy Efficient Prefetching – from models to Implementation 05/25/10 Adam Manzanares and Xiao Qin Department of Computer Science and Software Engineering Auburn University http://www.eng.auburn.edu/~xqin [email_address]
Adam Manzanares Ph.D. May 2010.
About me Ph.D.’04,  U. of Nebraska-Lincoln 04-07,  New Mexico Tech 07-10,  Auburn University
About My Research Group
Presentation Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],05/25/10
Motivation EPA Report to Congress on Server and Data Center Energy Efficiency,  2007   05/25/10
Motivation ,[object Object],[object Object],[object Object],[object Object],05/25/10
Buffer Disk Architecture 05/25/10 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
IBM Ultrastar 36Z15 05/25/10 Transfer Rate 55 MB/s Spin Down Time: T D 1.5 s Active Power: P A 13.5 W Spin Up Time: T U 10.9 s Idle Power: P I 10.2 W Spin Down Energy: E D 13 J Standby Power: P A 2.5 W Spin Up Energy: E U 135 J Break-Even Time: T BE 15.2 S
Prefetching Disk 1 Disk 2 Disk 3 Buffer Disk 05/25/10
Why Modeling & Simulation ,[object Object],[object Object],[object Object],05/25/10
Modeling & Simulation Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],05/25/10
Energy Saving Principles ,[object Object],[object Object],[object Object],[object Object],05/25/10
Paramaters Tested 05/25/10 Parameter Values Data Size 1, 5, 10, 25 MB  # of Data Disks 4, 8, 12 Inter-arrival Delay  0, 0.1, 0.5, 1 S Hit Rate 85, 90, 95, 100%
Energy Savings Hit Rate 85% 05/25/10
State Transitions 05/25/10
Parameter Generalizations ,[object Object],[object Object],[object Object],[object Object],05/25/10
Modeling & Sim. Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],05/25/10
DiskSim ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],05/25/10
File System Simulator ,[object Object],[object Object],[object Object],[object Object],05/25/10
DiskSim with File System Simulator 05/25/10
Modified DiskSim Results 05/25/10
Modified DiskSim Summary ,[object Object],[object Object],[object Object],[object Object],05/25/10
Why a Cluster File System ,[object Object],[object Object],[object Object],[object Object],[object Object],05/25/10
Energy Efficient Virtual File System 05/25/10
EEVFS Process Flow 05/25/10
EEVFS Testbed 05/25/10 Parameter Storage Server Storage Node Type 1 Storage Node  Type 2 CPU P4 2.0 GHz P4 3.2 GHz P4 2.4 GHz Memory (MB) 2000 1000 512 Network Interconnect 1000 1000 100 Disk Type SATA ATA/133 ATA/133 Disk Capacity 120 GB 80 GB 80 GB Disk Bandwidth 100 MB/s 58 MB/s 34 MB/s
Energy Savings 05/25/10
State Transitions 05/25/10
Response Times 05/25/10
Berkeley Web Trace 05/25/10
EEVFS Summary ,[object Object],[object Object],05/25/10
Parallel Striping Groups Group 1 Storage Node 1 Storage Node 2 Group 2 Storage Node 3 Storage Node 4 File 1 File 2 File 3 File 4 05/25/10 Disk 1 Disk 2 Buffer Disk Disk 3 Disk 4 Buffer Disk Disk 5  Disk 6 Buffer Disk Disk 7 Disk 8 Buffer Disk
Striping Within a Group Group 1 Storage Node 1 Storage Node 2 1 3 5 7 9 4 6 8 4 6 8 1 3 5 7 9 10 10 1 2 1 2 File 1 File 2 2 2 05/25/10 Disk 1 Disk 2 Buffer Disk Disk 3 Disk 4 Buffer Disk
Striping Within a Group ,[object Object],[object Object],[object Object],05/25/10
Testbed 05/25/10 Parameter Storage Server Storage Node CPU Celeron 2.2 GHz Celeron 2.2 GHz Memory (MB)  2000 2000 Network Interconnect 1000 1000 Disk Type SATA SATA Disk Capacity 160 GB 480 GB Disk Bandwidth 126 MB/s 126 MB/s
Measured Results 05/25/10
Measured Results 05/25/10
Berkeley Web Trace 05/25/10
Response Time Comparison ,[object Object],[object Object],05/25/10 Parameter Striping No Striping Energy Consumption (J) 2,088,113 2,100,243 Response Time (S) 2.78 13.87
Parallel Striping Groups Summary ,[object Object],[object Object],[object Object],05/25/10
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],05/25/10
Future Work ,[object Object],[object Object],[object Object],05/25/10
http://www.auburn.edu/~xzq0001
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Energy Efficient Prefetching – from Models to Implementation

Editor's Notes

  1. Web Servers they account for 24% of the energy, 77% proxy server, 27% in data center
  2. 12 disk