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Project GreenLight: DC Modular Datacenter for Improved Energy Efficiency,[object Object],Dr. Greg Hidley,[object Object],California Institute for Telecommunications and Information Technology, UCSD,[object Object],http://greenlight.calit2.net,[object Object]
The NSF-Funded GreenLight ProjectGiving Users Greener Compute and Storage Options,[object Object],PI is Dr. Tom DeFanti,[object Object],$2.6M over 3 Years to construct GreenLight Instrument,[object Object],Start with Sun Modular Data Center,[object Object],Sun Has Shown up to 40% Reduction in Energy,[object Object],Measures Temperature at 5 Levels in 8 Racks,[object Object],Measures power Utilization in Each of the 8 Racks,[object Object],Chilled Water Cooling input and output temperatures,[object Object],Add additional monitoring at every receptacle,[object Object],Add web and VR interfaces to access measurement data,[object Object],Populate with a variety of computing clusters and architectures,[object Object],Traditional compute and storage servers,[object Object],GP GPU arrays and specialized FPGA based coprocessors,[object Object],DC powered servers,[object Object],Turn over to investigators in various disciplines ,[object Object],Measure, Monitor and Collect Energy Usage data,[object Object]
The GreenLight Project: Instrumenting the Energy Cost of Computational Science,[object Object],Focus on 5 Communities with At-Scale Computing Needs:,[object Object],Metagenomics,[object Object],Ocean Observing,[object Object],Microscopy ,[object Object],Bioinformatics,[object Object],Digital Media,[object Object],Measure, Monitor, & Web Publish Real-Time Sensor Outputs,[object Object],Via Service-oriented Architectures,[object Object],Allow Researchers Anywhere To Study Computing Energy Cost,[object Object],Enable Scientists To Explore Tactics For Maximizing Work/Watt,[object Object],Develop Middleware that Automates Optimal Choice of Compute/RAM Power Strategies for Desired Greenness,[object Object]
UCSD is Installing Zero Carbon EmissionSolar and Fuel Cell DC Electricity Generators,[object Object],UCSD 2.8 Megawatt Fuel Cell Power Plant Uses Methane,[object Object],Available Late 2011,[object Object],San Diego’s Point Loma Wastewater Treatment Plant Produces Waste Methane,[object Object],2 Megawatt of Solar Power Cells Installed,[object Object]
Zero Carbon GreenLight Experiment:Direct DC-Powered Modular Data Center ,[object Object],Concept—Avoid DC to AC to DC Conversion Losses,[object Object],Computers Use DC Power Internally,[object Object],Solar and Fuel Cells Produce DC,[object Object],Both Plug into the AC Power Grid,[object Object],Can We Use DC Directly (With or Without the AC Grid)?,[object Object],DC Generation from Renewable Can Be Intermittent ,[object Object],Depends on Source ,[object Object],Solar, Wind, Fuel Cell, Hydro,[object Object],Can Use Sensors to Shut Down or Sleep Computers,[object Object],Can Use Virtualization to Halt/Shift Jobs,[object Object],Experiment Planning Just Starting,[object Object],Collaboration with Oracle, LBNL, EPRI, Direct Power, Intel, Delta, Emerson ,[object Object],NSF GreenLight Year 2 and Year 3 Funds,[object Object],CEC  and PIER support ,[object Object],DC Fuel Cell 2800kWatts,[object Object],Sun Box <200kWatt,[object Object]
Two Rack DC Experiment now Operational,[object Object],Proof of concept experiment within context of Project GreenLight,[object Object],Uses Emerson rectifier as source of DC power => 400VDC,[object Object],Uses Emerson DC PDUs,[object Object],Drives 400VDC custom server power supplies (from Delta and Emerson),[object Object],Drives 13 servers ,[object Object],6 SunFire X4270 (Nehalem) servers,[object Object],6 Intel 2600 (Nehalem) servers,[object Object],1 SunFire x4540 storage servers  ,[object Object],Transformer,[object Object],Rectifier,[object Object],PDU,[object Object],Servers,[object Object],480VAC,[object Object],400VDC,[object Object],400VDC,[object Object]
Potential Energy Efficiency Improvements using DC Power,[object Object],Anticipate reductions in all levels of energy chain from FC to servers using 400VDC ,[object Object],Fuel Cell Inverter (DC to AC),[object Object],DC-DC conversion losses (adjust to grid voltage),[object Object],480VAC distribution line losses,[object Object],480VAC to 208VAC or 120VAC step down losses,[object Object],UPS (AC to DC to charge batteries and back to AC) conversion losses,[object Object],PDU’s (AC voltage stepped down to server requirements),[object Object],Inside Power Supplies (rectification and transformation losses),[object Object],Anticipate reduction in cooling loads given heat dissipation of conversions,[object Object],Anticipate reduction of power utilization by 25% or better (power and cooling),[object Object],Anticipate cooling efficiencies of 33% or better,[object Object]
END,[object Object]
Capabilities  sneak  peak…,[object Object],GLIMPSE,[object Object],Decision Support System,[object Object],D E M O,[object Object],2010.08.20,[object Object]
Situational Awareness,[object Object],Dashboard interface,[object Object],“Tap”,[object Object],for details,[object Object],Power utilization,[object Object],Enterprise reach,[object Object],Multiple perspectives,[object Object]
Datacenter vitals,[object Object],Input/Output,[object Object],temperature sampling,[object Object],Live/average Fan speeds,[object Object],Live/Average,[object Object],data,[object Object],Live Temperature,[object Object],Heat Exchangers,[object Object],Environmentals,[object Object]
Domain specific views,[object Object],Control elements,[object Object],Real-time heatmap,[object Object],Realistic models,[object Object]
Airflow dynamics,[object Object],Live ,[object Object],fan speeds,[object Object],Airflow dynamics,[object Object],13,[object Object]
Heat distribution,[object Object],Combined heat + fans,[object Object],Realistic correlation,[object Object]
Heat Trends,[object Object],Heat exchangers,[object Object],Hotspot identification,[object Object],Trends over past 24h,[object Object]
Past changes in airflow,[object Object],Fan slices,[object Object],rpm,[object Object],Heat distribution changes,[object Object],Potential for failures,[object Object],Trends over past 24h,[object Object]
Power spikes,[object Object],IT assets,[object Object],Computation zone,[object Object],Unused asset,[object Object],Average load,[object Object],Peak computation,[object Object],1 minute,[object Object],resolution,[object Object]
Zoom-in Analysis,[object Object],2010.08.20,[object Object],History over several days.,[object Object],Zoom on desired time range.,[object Object],Hint on each sample point.,[object Object],Automatic average area.,[object Object],Multiple sensors per asset with up to 1 min samplingresolution.,[object Object],Calit2/UCSD [http://greenlight.calit2.net],[object Object]
Summary,[object Object],GLIMPSE – decision support system,[object Object],just a sliver of entire GreenLight Enterprise capabilities,[object Object],critical to understand the massive amounts of data,[object Object],provide real-time situational awareness,[object Object],monitor & control datacenter assets,[object Object],GreenLightEnterprise Solution:,[object Object],federates datacenters,[object Object],improves performance/watt by selecting most appropriate architectures,[object Object],improves energy utilization by scheduling computation based on heat, energy usage, and load,[object Object],reduces cooling needs and improves equipment lifetime,[object Object]

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Notas del editor

  1. Data Center Infrastructure Efficiency (DCiE)DCiE = IT (useful work) power / total facility powerPower Usage Effectiveness (PUE, the inverse of DCiE)PUE = total facility power / IT (useful work) power DCiE of 80% is the same as PUE of 1.25 … implies 200kw Sun MD would use 160kw for computers and 40kw for cooling and power distribution losses