Energy Efficient Prefetching

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Energy Efficient Prefetching from models to
Implementation
Adam Manzanares and Xiao Qin Department of
Computer Science and Software Engineering Auburn
Universityhttp//www.eng.auburn.edu/xqin xqin_at_au
burn.edu
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Adam Manzanares
Ph.D. May 2010.
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About me
Ph.D.04, U. of Nebraska-Lincoln
04-07, New Mexico Tech
07-10, Auburn University
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About My Research Group
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Presentation Outline

• Motivation
• Modeling Work
• DiskSim Modifications
• Energy Efficient Virtual File System (EEVFS)
• Parallel Striping Groups in EEVFS
• Conclusion

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Motivation
EPA Report to Congress on Server and Data Center
Energy Efficiency, 2007
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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

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Buffer Disk Architecture
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IBM Ultrastar 36Z15
Transfer Rate 55 MB/s Spin Down Time TD 1.5 s
Active Power PA 13.5 W Spin Up Time TU 10.9 s
Idle Power PI 10.2 W Spin Down Energy ED 13 J
Standby Power PA 2.5 W Spin Up Energy EU 135 J
Break-Even Time TBE Break-Even Time TBE 15.2 S 15.2 S
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Prefetching
Buffer Disk
Disk 1
Disk 2
Disk 3
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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

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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

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Energy Saving Principles

• Energy Saving Principle One
• Increase the length and number of idle periods
  larger than the disk break-even time TBE
• Energy Saving Principle Two
• Reduce the number of power-state transitions

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Paramaters Tested
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
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Energy Savings Hit Rate 85
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State Transitions
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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

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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

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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

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File System Simulator

• Large files important to energy savings
• Popularity of data is also useful
• Developed a block to file translator
• Interacts with DiskSim

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DiskSim with File System Simulator
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Modified DiskSim Results
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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

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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

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Energy Efficient Virtual File System
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EEVFS Process Flow
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EEVFS Testbed
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
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Energy Savings
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State Transitions
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Response Times
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Berkeley Web Trace
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EEVFS Summary

• Knowledge of requests assumed and may be hard to
  come by
• Performance tied to one of the buffer disks

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Parallel Striping Groups
File 1
File 2
File 3
File 4
Group 1
Group 2
Disk 1
Disk 2
Buffer Disk
Disk 5
Disk 6
Buffer Disk
Storage Node 1
Storage Node 3
Disk 3
Disk 4
Buffer Disk
Disk 7
Disk 8
Buffer Disk
Storage Node 2
Storage Node 4
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Striping Within a Group
Disk 1
Disk 2
Buffer Disk
1
3
5
7
9
4
6
8
10
2
Storage Node 1
Disk 3
Disk 4
Buffer Disk
4
6
8
1
3
5
7
9
10
2
Storage Node 2
Group 1
File 2
2
2
1
1
File 1
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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

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Testbed
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
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Measured Results
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Measured Results
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Berkeley Web Trace
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Response Time Comparison
Parameter Striping No Striping
Energy Consumption (J) 2,088,113 2,100,243
Response Time (S) 2.78 13.87

• Energy efficiency is slightly improved
• Response time gain is significant

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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

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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

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Future Work

• Improve the EEVFS prototype for production use
• Run EEVFS on large scale storage system
• Investigate scaling effects

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http//www.auburn.edu/xzq0001
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Download the presentation slides
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Download the presentation slides
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Download the presentation slides
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http//www.slideshare.net/xqin74
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Questions