Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Datacentre of the Future

465 views

Published on

Asperitas CEO Rolf Brink presented a vision on the datacentre of the future including innovative datacentre design concepts during the Datacentre Transformation event in Manchester on the 11th of July 2017

Published in: Technology
  • Be the first to comment

Datacentre of the Future

  1. 1. Rolf Brink Founder/CEO +31 88 96 000 00 www.asperitas.com
  2. 2. COPYRIGHT © 2017 BY ASPERITAS Asperitas, Robertus Nurksweg 5, 2033AA Haarlem, The Netherlands Information in this document can be freely used and distributed for internal use only. Copying or re-distribution for commercial use is strictly prohibited without written permission from Asperitas. If you would like to use the original powerpoint version of this document, you can send an email to: Marketing@Asperitas.com FOR MORE INFORMATION, FEEDBACK OR TO SUGGEST IMPROVEMENTS FOR THIS DOCUMENT, PLEASE SEND YOUR SUGGESTIONS OR INQUIRIES TO: WHITEPAPERS@ASPERITAS.COM Copyright © 2017 by Asperitas
  3. 3. THE DATACENTRE OF THE FUTURE A DATACENTRE IS NOT ABOUT ICT, POWER, COOLING OR SECURITY. IT IS NOT EVEN ABOUT SCALE OR AVAILABILITY OF THESE SYSTEMS. IT IS ABOUT THE AVAILABILITY OF INFORMATION… Copyright © 2017 by Asperitas
  4. 4. INCREASE IN INFORMATION FOOTPRINT DEMAND FOR HIGH DENSITY CLOUD CONSOLIDATION OF POWER DEMAND OVERLOADING OF OUTDATED POWER GRID GLOBAL NETWORK LOAD CREATING EXERGY THE CHALLENGES Copyright © 2017 by Asperitas
  5. 5. Datacentres, Server rooms, Network hubs etc. Estimated 4% Global Electricity Production (25 PWh) 4% = 1 PWh 1000000000000000 Wh (1015) ENERGY FOOTPRINT OF INFORMATION FACILITIES Copyright © 2017 by Asperitas
  6. 6. EXPLANATION PREVIOUS SLIDE (ENERGY FOOTPRINT) ▪ There is no real data available which can substantiate any sort of claim to the percentage mentioned. It is a very rough estimate for a global scale. ▪ The fact that the information is unavailable, is part of the problem. You cannot solve the problem which cannot be identified. ▪ https://yearbook.enerdata.net/electricity/world-electricity-production-statistics.html ▪ The only available source for a global figure is the European Commission where Neelie Kroes mentioned datacentres being responsible for 2% of the global electrical energy production and ICT in general being responsible for 8-10%. (2012) Copyright © 2017 by Asperitas
  7. 7. GLOBAL PUE: APPROX. 1.7 Cooling 37% UPS/Nobreak 2% Other 2% Power supply (15%) 9% Fans (20%) 10% Information (65%) 40% ICT 59% Global estimated PUE breakdown Copyright © 2017 by Asperitas
  8. 8. EXPLANATION PREVIOUS SLIDE (GLOBAL PUE ESTIMATE) ▪ There is no real data available which can substantiate any sort of claim to the percentages mentioned. Everything is a very rough estimate for a global scale. ▪ For both the Power supply and Fans percentages, the estimates are based on the following factors: ▪ Most datacentres (colo) have no control over the internal temperature management of the IT. ▪ Environmental temperatures in datacentres are usually too high for optimal power efficiency of IT. ▪ IT is in general greatly under-utilised (30% is already high in many cloud environments, corporate IT in colo is often worse) which creates a very high overhead for both the PSU and fans. ▪ Most cloud and corporate backoffice platforms are running on inefficient, cheap IT hardware which is driven by CAPEX as opposed to OPEX. Reason for this is that power consumption is not part of the IT budget. ▪ Virtually all high density cloud environments (5-10 kW/rack) are based on 1U servers. These are the least efficient when it comes to fan overhead. Copyright © 2017 by Asperitas
  9. 9. ACTUAL INFORMATION EFFICIENCY ▪ 1000 TWh total energy ▪ Actual cooling: 471 TWh ▪ Actual power loss: 112 TWh 112 TJ/s ▪ Other overhead: 17 TWh 17 TJ/s ▪ Energy for information: 400 TWh 400TJ/s ▪ 1000 TWh/400TWh ▪ PUE equivalent: 2.5 Cooling + IT fans 47% UPS+IT Power supply 11%Other 2% Information 40% Actual efficiency Copyright © 2017 by Asperitas
  10. 10. Global thermal energy production by Information 1904400000000000000 J or 1.9 EJ (1018) (529 TJ/s*3600): Energy for heat rejection EXERGY DESTRUCTION: 471000000000000 Wh ENERGY TRANSFORMATION Copyright © 2017 by Asperitas
  11. 11. EXCLUDE COOLING INSTALLATIONS REDUCE IT OVERHEAD BALANCE THE POWER GRID REDUCE THE DATA NETWORK LOAD BECOME ENERGY PRODUCERS WHAT IF INFORMATION FACILITIES COULD... Copyright © 2017 by Asperitas
  12. 12. 1 MW critical load, ΔT of 10°C Thermal production: 1MJ/s 1°C rise with air: 1005 J/kg°C * 0.001205 kg/L = 1.211025 J/L/s 1MJ/s requires: 1000000 J/(10°C *1.2 J) 83333L/s AIR COOLING THE CLOUD Copyright © 2017 by Asperitas
  13. 13. Water required for ΔT of 10 °C 4187 J/kg°C * 1 kg/L = 4187 J/L/s per 1°C 10°C with 1 MJ/s: 24 L/s 83333 L/s AIR VS WATER 1 MJ/s THE DATACENTER OF THE FUTURE: 6 L/s AND IS AN ENERGY PRODUCER...… Liquid can travel 200 TIMES THE DISTANCE with same thermal losses Copyright © 2017 by Asperitas
  14. 14. EXPLANATION PREVIOUS SLIDES (WATER VS AIR) ▪ For simplicity, the identical ΔT is maintained for both approaches. ▪ After feedback from reviewers and the audience of Datacentre Transformation Manchester, the comparison was raised to 10 °C ▪ Air will usually allow the ΔT to become higher than 10 °C, although due to poor utilization, this is not always achieved. ▪ In CRAC water circuits, the ΔT is usually below 10 °C. Copyright © 2017 by Asperitas
  15. 15. DON’T ASK WHICH TECHNOLOGY TO USE CHOOSE BETWEEN AIR OR LIQUID THEN COMBINE LIQUID TECHNOLOGIES THE WRONG QUESTION Copyright © 2017 by Asperitas
  16. 16. TLC - IMMERSED COMPUTING® ▪ 100% Removal of heat from the IT ▪ Highest IT efficiency by eliminated fans ▪ No air required ▪ Level of intelligence ▪ Management control and insight ▪ Automatic optimisation of the water circuit ▪ Optimised for high density cloud/HPC nodes ▪ Varying servers ▪ Flexible IT hardware ▪ Feed: 18-40°C / 55°C Extreme / max ΔT 10°C Copyright © 2017 by Asperitas
  17. 17. DLC - DIRECT-TO-CHIP LIQUID COOLING ▪ Removes heat from hottest parts of the IT ▪ Increased IT efficiency by reduced fan power ▪ Requires additional cooling (ILC) ▪ Level of intelligence ▪ Management control and insight ▪ Automatic optimisation of the water circuit ▪ Optimised for HPC racks with identical nodes ▪ Very high temperature chips ▪ High density computing ▪ Feed: 18-45°C / max ΔT 15°C Copyright © 2017 by Asperitas
  18. 18. ILC - (ACTIVE) REAR DOOR COOLING ▪ 100% Removal of heat from the IT ▪ Small IT efficiency by assisted circulation ▪ Acts as air handler in the room ▪ Level of intelligence ▪ Management control and insight ▪ Automatic optimisation of the water circuit ▪ Optimised for IT with limited liquid compatibility ▪ Storage ▪ Network ▪ Legacy systems and high maintenance servers ▪ Feed: 18-23°C / 28°C Extreme / max ΔT 12°C Copyright © 2017 by Asperitas
  19. 19. TECHNOLOGY NORMAL INLET OUTLET CRAC (generic) 6-18°C 12-25°C ILC (U-Systems) 18-23°C 23-28°C DLC (Asetek) 18-45°C 24-55°C TLC (Asperitas) 18-40°C 22-48°C TECHNOLOGY EXTREME INLET OUTLET CRAC (generic) 21°C 30°C ILC (U-Systems) 28°C 32°C DLC (Asetek) 45°C 65°C TLC (Asperitas) 55°C 65°C OPTIMISING LIQUID INFRASTRUCTURES Copyright © 2017 by Asperitas
  20. 20. 17°C CRAC Parallel • +5°C • Output 22°C ILC Parallel • +6°C • Output 28°C TLC & DLC paired • +16°C • Output 44°C TLC & DLC paired • +16°C • Output 60°C Facility output 60°C INCREASING ΔT WITH TEMPERATURE CHAINING ▪ Serial implementation of the infrastructure CREATE HIGH ∆T 3-stage cooling for low water volume Down to 35 °C, free-air Between 35-28 °C, adiabatic Below 28 °C, chiller USABLE HEAT Copyright © 2017 by Asperitas
  21. 21. TEMPERATURE CHAINING EXAMPLE ▪ Closed room 3-stage configuration ▪ ILC setup maintains air temperature ▪ Water volume decreased by 85% ▪ ΔT 6°C : 29.9 L/s ▪ ΔT 40°C : 4.5 L/s ▪ Cooling options ▪ Closed cooling circuit with pumps and coolers ▪ Closed cooling circuit with pumps and reuse behind Heat Exchanger ▪ Open cooling circuit with external water source supplied for reuse +8°C +5°C+6°C+6°C+7°C+6°C +6°C+7°C+4°C+3°C+6°C +7°C +9°C +6°C +6°C +7°C+10°C+7°C +7°C+8°C+6°C +14°C +16°C +17°C +12°C Stage 1 ILC Stage 2 DLC & TLC Stage 3 Optimised DLC&TLC Facility input 20°C 26°C +6°C +5°C +8°C +7°C +2°C +5°C +7°C +5°C +9°C +8°C +4°C +6°C +5°C+7°C+6°C+2°C +7°C+6°C+2°C+3°C+5°C +9°C +7°C Facility output 60°C 400 kW TLC 40 kW DLC +19°C 160 kW TLC 60 kW DLC +15°C 120 kW ILC +6°C 45°C Copyright © 2017 by Asperitas
  22. 22. REUSE MICRO INFRASTRUCTURE ▪ Micro datacentre or server room ▪ Open water circuit ▪ Reusable requirement: 65°C ▪ Variable volume ▪ Feedback loop for constant temperature +7°C +7°C Constant temp Facility output 65°C 51°C Variable temp Facility input 5-40°C Copyright © 2017 by Asperitas
  23. 23. Water required for ΔT of 40 °C 4187 J/kg°C * 1 kg/L = 4187 J/L per 1°C 40°C with 1 MJ/s: 6 L/s 83333 L/s AIR VS WATER 1 MJ/s TEMPERATURE CHAINING IMPACT Copyright © 2017 by Asperitas
  24. 24. DATACENTRE DESIGN ▪ Cooling options: ▪ 100% Chillers ▪ 100% Free air/adiabatic + 100% Chillers (off) ▪ High volume, low ∆T (5-20 °C) ▪ Fluid handling ▪ Spacious high capacity air ducting ▪ Air filtration ▪ Hot/Cold aisle separation ▪ Information density (avg) 1,5 kW/m2 ▪ Concrete floor + Raised floors ▪ Power ▪ UPS (IT only): 100% ▪ Gensets (facility): 100% ▪ Cooling options: ▪ External cold water supply by reuser ▪ 100% Free air/adiabatic + 5% chillers ▪ Low volume, high ∆T (20+°C) ▪ Fluid handling ▪ Normal capacity water circuit ▪ Water quality management ▪ Minimal “fresh-air” ventilation ▪ Information density (mixed) 12 kW/m2 ▪ Bare concrete floor ▪ Power (compared to air) ▪ UPS (IT only): 90% ▪ Gensets: 60% DESIGNED FOR AIR DESIGNED FOR MIXED LIQUID Copyright © 2017 by Asperitas
  25. 25. Minimised energy footprint Minimised installations requirements Flexibility by minimal environmental impact FOCUS ON 24/7 HEAT CONSUMERS SITE PLANNING AND QUALIFICATION Copyright © 2017 by Asperitas
  26. 26. REDEFINING THE LANDSCAPE ▪ Large facilities ▪ Core Datacentres ▪ On the edge of urban areas ▪ Distributed micro facilities ▪ Edge nodes ▪ Inside the urban area ▪ Energy balancing ▪ Distributed minimised power load ▪ Focus on heat reuse Copyright © 2017 by Asperitas
  27. 27. DISTRIBUTED MICRO EDGE NODES ▪ 10-100 kW ▪ Edge of network, within urban areas ▪ IoT capture and processing ▪ Data caching (Netflix, Youtube, etc.) ▪ Localised cloud services (SaaS, Paas, IaaS) ▪ Minimised facilities ▪ External cooling input ▪ 24/7 energy rejection for reuse ▪ Geo redundant ▪ Tesla Powerpack for controlled failover ▪ District data hub EDGE ENERGY REUSE Spas, swimming pools (100% reuse) Hospitals, hotels with hot water loops (100% reuse) Urban fish/vegetable farms with aquaponics (100% reuse) District heating (100% reuse) Aquifers for heat storage (75% reuse) Water mains (29% reuse) Canals, lakes and sewage (exergy destruction) Copyright © 2017 by Asperitas
  28. 28. CORE DATACENTRES ▪ Large facilities ▪ No-break systems ▪ Limited cooling infrastructure ▪ 24/7 information availability ▪ Edge management ▪ Replicated Edge back-end ▪ Communication hub ▪ Industrial scale reuse infrastructures ▪ 100% 24/7 heat reuse ▪ Agriculture ▪ Spas ▪ Cooking, pressurising, sterilisation, bleaching ▪ Distillation, concentrating, drying or Kilning ▪ Chemical ▪ Exergy destruction ▪ Rivers/ocean ▪ Liquid-to-air rejection Copyright © 2017 by Asperitas
  29. 29. EDGE MANAGEMENT Emerging platforms for decentralised cluster management Integration with energy and heat management CLOUD CUSTOMERS COMPUTING JOBS COMPUTING RESULTS CLOUD DEMAND COMPUTING JOBS COMPUTING RESULTS JOB SCHEDULING HEAT DEMAND CLOUD DEMAND DISTRIBUTION MANAGEMENT FOR HEATING .ware INFORMATION HARDWARE Q.RADS, O.MAR, AIC24 HARDWARE INSTALLATION HEAT DEMAND CUSTOMERS .rads Free and green heat Copyright © 2017 by Asperitas
  30. 30. LIQUID INFORMATION FACILITIES ▪ Reduced or eliminated technical installations ▪ Cooling ▪ No-break ▪ Reduced build cost ▪ No raised floors ▪ Reduced space for fluid handling ▪ Increased, distributed power density ▪ Reduced m2 ▪ Reduced operational cost ▪ Reduced maintenance on installations ▪ High IT density ▪ Higher specs IT hardware, also for cloud ▪ Reduced software cost Copyright © 2017 by Asperitas
  31. 31. LIQUID IS COMING HOW TO PREPARE? Design for water (redundant) to IT Sufficient ability to distribute piping to whitespace Plan for reusable heat Plan for liquid way of work IT maintenance rooms for wet equipment Staff training for liquid management Proper supplies and tooling Copyright © 2017 by Asperitas
  32. 32. WHAT NEEDS TO BE DONE? ▪ Focus on heat consumption without dependency ▪ Not with an invoice ▪ Free cooling guarantee ▪ Government involvement ▪ Incentives ▪ Intermediate for (industrial) heat reuse ▪ Information footprint as part of district planning ▪ More (low grade) heating networks ▪ Focus on TCO, not CAPEX ▪ PUE – need for a new “easy” metric ▪ PUE figures are widely manipulated ▪ PUE discourages IT efficiency ▪ It needs to give insight in actual inefficiency Cooling 37% UPS/Nobreak 2% Other 2% Power supply (15%) 9% Fans (20%) 10% Information (65%) 40% ICT 59% PUE inefficiency FEAR OF WATER Copyright © 2017 by Asperitas
  33. 33. THE DATACENTRE OF THE FUTURE? THE FUTURE IS NOW! Copyright © 2017 by Asperitas

×