INSIDE THE PROTOTYPE BODENTYPE DATA CENTER: OPENSOURCE MONITORING OF OPENSOURCE HARDWARE
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1 INSIDE THE PROTOTYPE BODENTYPE DATA CENTER: OPENSOURCE MONITORING OF OPENSOURCE HARDWARE Dr Jon Summers Scientific Leader in Data Centers, RISE Adjunct Professor of Fluid Mechanics, Lulea University of Technology, SWEDEN Senior Lecturer in Thermofluids, University of Leeds, UK ICT DIVISION, Research Institutes of Sweden
2 BodenType Data Center H2020 Project The BodenType Data Center (BTDC) project is funded by the EU To pilot a cost and energy efficient sub 1MW prototype data center. Three Data Center PODs Designed for 500kW of Information Technology. Test POD 1 has legacy Open Compute Project IT windmill. POD 2 and 3 are designed for HPC/GPU test partners for a target 350kW. This project has received funding from the European Union s Horizon 2020 Research and Innovation programme under grant agreement No Visit
3 BodenType DC H2020 Project Rapid growth in data center energy consumption in Europe from 86TWh in 2013 to an anticipated 104TWh in 2020 (reference P.Bertoldi from the EU JRC). Aim of BodenType DC project to create a pilot data center that is cost and energy efficient with minimal environmental impact to demonstrate this requires a comprehensive monitoring and measurement tool. Efficiency is focussed on reducing power losses no UPS, reducing cooling power consumption using direct air (measured comparison with other methods) and better utilization of the IT systems workload deployment and management. Project partners are: Visit P. Bertoldi, The European Programme for Energy Efficiency in Data Centres: The Code of Conduct, EU DG JRC, Institute for Energy and Transport, 2016.
4 Construction of Boden Type Data Center One Visit
5 The complete BTDC One Building Visit
6 The BodenType Data Center design POD 1 Visit
7 Open source monitoring of BTDC One Monitoring Software
8 T fixed for all IT units Innovation around thermal management POD 1 Cooling Units set T supply and T return Traditional Set supply Temperature and expected delta T Cooling Units Hot aisle IT Equipment Cold aisle IT Equipment T return T supply Exhausted Hot aisle T return Exhausted Wind tunnel to determine T IT equipment sets T return
9 Server wind tunnel HEX RADIAL FAN Set temperature with the HEX chilled water flowrate and wind tunnel FAN speed. Air flowrate with the wind tunnel FAN can pressurize the cold aisle as would happen in the contained cold aisle in the DC. Upstream and downstream temperature measurements. Can support between 1U and 4U of Information Technology. Currently limited control over the air relative humidity. TEMP and FLOW sensors
10 Results with the OCP Windmill Server Wind tunnel results are captured using the same data center monitoring tools. Uses the same opensource monitoring system as the data center. The project uses many different workload generation approaches. Note the variation of power consumption with server supply temperature combination of increased fan power and current leakages. Temperatures are in o C Pressure drop was not kept constant for the different inlet temperatures.
11 ΔT Relationship between the delta T and power consumption of the IT. The cooling strategy is to set a delta T on the cooling systems to match idle power OCP Server Power vs. ΔT (ΔP=0, Ti=20 ) y = 0.039x R² = When IT power increases the coolers will speed up the supply and extract fans to maintain the supply temperature and to try and maintain the return temperature based on the idle delta T This will result in pressurisation of the contained cold aisle. A more efficient strategy is to allow the return temperature to match the exhaust temperature from the servers Power/blade [W] Wind tunnel HEX kept inlet temperature constant and the FAN kept the server pressure drop to 0.
12 Types of workloads operated in the BTDC One POD1 Workload Classification Based on Processing Model Based on Resource Based on Computer Environment Based on Generation Based on Application Batch Memory Physical Synthetic Web Interactive CPU Virtual Real Social Network IO Database Cloud Hybrid Application based Load Patterns A controlled test campaign has started to run for one year and large datasets from POD1 will form part of an Open Research Data Pilot. Video Service Smart Cities Industrial Internet of Things etc
13 Varying CPU utilisation on servers using synthetic workloads.
14 Results in the following profile of power consumption.
15 With the following supply and return temperatures.
16 And a resulting increased pressure in the cold aisle.
17 Monitoring outside environment with a weather station Sub-zero temperatures 4 th March 8am to midnight 6 th March
18 Humidity control Low outside temps gives a challenge for humidity control. Wetting the air is done by wetted pads not a spray system, but with sub-zero temps need to account for the potential of freezing water. All axes are in percentages 25% average = 1 out 4 coolers in recirculation. Power Factor to the Data Centre (blue) and Pod 1 (red)
19 Heat sinks in OCP Servers Aim to achieve lower flow rates and higher delta temperature across the Windmill servers. Flowrate control is also achieved by the use of some locally developed fan controller cards. Run to a fixed delta temperature across all servers or calculate flowrate through each server and provide this information to the fresh air cooling system. Replaced aluminium heat sinks containing embedded heat pipes with copper heat sinks. LOCALLY DEVELOPED FAN CONTROLLER
20 Effect of taking control of all server fans for 30 minutes.
21 SUMMARY The project operates and monitors an experimental, but realistic test data center. Deployed a chain of opensource software to monitor the data center, IT utilisation and deterministic control of workload. Created a 150kW IT footprint using legacy OCP Windmill servers, with power, network and environmental and workload control. Piloting a data center cooled by direct air with a low cost humidification and an ambitious linking of facility and server fans. RISE can characterise thermal and power envelopes of servers using a uniquely developed server wind tunnel. The EU funded project has developed a strategy for deploying synthetic and near to real Industrial IOT workloads. Open Research Data Pilot will be available from the end of March Visit Thanks to RISE colleagues: Jonas Gustafsson Daniel Olsson Jeffrey Sarkinen Magnus Nilsson-Mäki Filip Blylod Sebastian Fredriksson This project has received funding from the European Union s Horizon 2020 Research and Innovation programme under grant agreement No Thanks to the other BodenType DC Project partners H1 Systems Fraunhofer Institute of Optronics EcoCooling Boden Business Agency
22 ANY QUESTIONS? Visit PODS available for test partners. Project Highlights Design characteristics Environmental values Cost and Energy Efficiency Please visit us in Boden. This project has received funding from the European Union s Horizon 2020 Research and Innovation programme under grant agreement No Thanks to the other BodenType DC Project partners H1 Systems Fraunhofer Institute of Optronics EcoCooling Boden Business Agency
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