Data centerefficiency

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  • Source: . http://www.mediafire.com/file/zzqna34282frr2f/koomeydatacenterelectuse2011finalversion.pdf
  • Source: http://searchdatacenter.techtarget.com/definition/power-usage-effectiveness-PUE
  • Source: http://www.google.com/corporate/data center/efficient-computing/index.htm
  • Source:http://static.googleusercontent.com/external_content/untrusted_dlcp/services.google.com/en/us/blog_resources/PSU_white_paper.pdf 
  • Sources:http://www.google.com/about/datacenters/inside/efficiency/temperature.html,http://www.google.com/about/datacenters/inside/efficiency/index.html
  • Source: http://www.google.com/about/datacenters/inside/efficiency/servers.html
  • Source:http://www.datacenterknowledge.com/archives/2009/11/27/should-servers-come-with-batteries/
  • Source :  http://queue.acm.org/detail.cfm?id=1698225
  • Source: http://serktools.com/2010/01/20/windows-server-core-overview/
  • Source:http://queue.acm.org/detail.cfm?id=1698225
  • Source:http://queue.acm.org/detail.cfm?id=1698225
  • Source:http://queue.acm.org/detail.cfm?id=1698225
  • Source: nms.csail.mit.edu/~stavros/pubs/energy_sigmod10.pdf

Transcript

  • 1. DATA CENTER EFFICIENCY Introduction 1
  • 2. DATA CENTER POWER CONSUMPTION  In 2005 data center power usage was 1% of the worlds power consumption.  The current power usage is estimated to be as high as 1.5% world wide and up to 2.2% of US power consumption.  Why should you care?  Every year there are rolling blackouts though the summer because utilities cannot keep up with demand.  Energy costs are higher than equipment costs. 2
  • 3. EFFICIENCY BASICS  Power Usage Effectiveness (PUE) developed by the Green Grid is a widely accepted measure of data center efficiency.  PUE Calculation Total data center energy consumption/IT energy consumption=PUE  A PUE of one means that all energy consumptions is being used by the servers, storage devices and networking equipment.  Reaching one is the goal, but may not be possible currently…  However, Google has reached reach a Power Usage Effectiveness (PUE) of 1.16. 3
  • 4. THERE IS A BETTER WAY… According to Google “if all data centers operated at the same efficiency as ours, the U.S. alone would save enough electricity to power every household within the city limits of Atlanta, Los Angeles, Chicago, and Washington, D.C.” 4
  • 5. CASE STUDY: GOOGLE How did they do it?  Power Supply  The average power supply converts power from AC to DC accounting for 30 to 40% in power loss.  This process also produces heat  Google power supplies do not perform this costly conversion and have an integrated UPS.  “We’ve also cut out 2 of the AC / DC conversion stages by putting back-up batteries on the server racks themselves.” 5
  • 6. GOOGLE CASE STUDY (CONTINUED)  Google tracks its PUE  Data centers are run at 80 degree Fahrenheit or more  This “conforms with both the American Society of Heating, Refrigerating, and Air Conditioning Engineers' recommendations and most IT equipment manufacturers' specs.  Data centers can be cooled without chillers  Remaining chillers have disabled “dehumidifying and reheating functions on CRACs. Most are set to dehumidify air to 40% and reheat air if the return air is too cold, but these functions aren’t needed.”  Each data center element is designed to operate at optimal efficiency 6
  • 7. GOOGLE CASE STUDY (CONTINUED)  “Customizing servers for efficient power use  We also omit parts on servers that aren't needed for our applications. Hardware is limited to what is necessary for the applications to run, and does not include unnecessary components such as peripheral connectors or video cards. We also optimize our servers and racks to use minimal fan power, and the fans are controlled to spin only as fast as necessary to keep the server temperature below a threshold.“ 7
  • 8. FACEBOOK CASE STUDY “Facebook recently disclosed its plans to adopt a novel power distribution design pioneered by Google that removes uninterruptible power supply (UPS) and power distribution units (PDUs) from the data center. The new design shifts the UPS and battery backup functions from the data center into the cabinet by adding a 12 volt battery to each server power supply.”  Video Tour of Facebooks 1.07 PUE datacenter https://www.facebook.com/photo.php?v=10150385588936731&set=vb.193287527693&type=2&theater 8
  • 9. ROLE OF SOFTWARE  ”(T)he only way to have software consume zero resources is not to run it at all. Even running very well-behaved software at the minimum will, in practice, require some resource overhead.”  Virtualization  Power Management  Node Management  Scheduling  Lean Operating systems  Software development  De-duplication 9
  • 10. VIRTUALIZATION  Virtualization is useful for consolidation of under utilized software  DO: consolidate servers that typically have usage under 70%  DO NOT: consolidate servers that have usage higher than 90%  Unless the server resources are more than enough to cover usage patterns including the other virtualized servers consolidated into the new server  WARNING: Consolidating server high usage servers on one server may be a recipe for disaster.  Remember: Virtualization can lead to the need to rework cooling in the data center.  Fewer machines could lead to unnecessary cooling of space no longer occupied by servers. This could result in wasted cooling. 10
  • 11. LEAN OPERATING SYSTEMS  Windows server 2008 R2 Core  Uses less disk space  Standard 7.5 GB  Core 3.5 GB  What’s the big deal space is cheap?  Not really  Hard drive usage must be powered  Additional load for backups  Can be a huge deal in a virtualized environment  Memory usage is also decreased by 34%  Multiply that by 100 in a virtual environment, the resource savings is huge 11
  • 12. SOFTWARE DEVELOPMENT  CPU UTILIZATION  Write event-triggered not time-based checks  Use batch processing for processes that cannot be event based  Make sure batch jobs can be adjusted for time conflicts  MEMORY UTILIZATION  Avoid memory leaks  Release memory when it is no longer needed, don’t wait for the system to do it foru you. 12
  • 13. SOFTWARE DEVELOPMENT (CONTINUED)  I/O UTILIZATION  Buffer/batch I/O requests  EFFICIENT SYSTEM STACK  “Features to reduce power consumption of underutilized system resources have become pervasive in even the largest systems, and the software layers responsible for managing those resources must evolve in turn”  Implement policies:  Increase performance of resources in use  Reduce power consumption for resources not in use 13
  • 14. SOFTWARE DEVELOPMENT (CONTINUED)  “Resource consumers clearly have a significant opportunity either to contribute to or undermine the efficiency of the broader stack. Though getting programmers to think differently about the way they design software is more than a technical problem, tools such as PowerTOP represent a great first step by providing programmers and administrators with observability into software inefficiency, a point of reference for optimization, and awareness of the important role software plays in energy-efficient computing." 14
  • 15. HARDWARE  What is better one really powerful server of several low powered servers?  Answer: It depends.  Many low powered servers are ideal for transactional loads  Powerful servers are better for simulation and computation 15
  • 16. STORAGE  Hard Disk DriveHDD vs Solid State Drives (SDD)  HDD  Uses 80% of maximum power draw at start-up  SDD  Linear proportion usage to power relationship  This means that any HDD active, but running at under 80% utilization is wasting energy. 16
  • 17. STORAGE PROBLEM  So is the answer to use all solid state drives?  That is one possible answer, but it is currently an expensive answer.  Other possibilities:  Storage consolidation  Virtualization is one possible method of achieving this goal  Shared storage arrays are another  Increased use of technologies such as memcached for frequently accessed data  This technique uses RAM caching  Used in conjunction with compression this can be very useful for transactional loads  Hybrid SDD/HDD storage systems managed intelligently 17
  • 18. CONCLUSION  "Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius -and a lot of courage -- to move in the opposite direction.” ~Albert Einstein  In IT this kind of thinking results in huge payoffs when implemented correctly. 18