Rolf Brink Founder/CEO
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1 Rolf Brink Founder/CEO
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 to: FOR MORE INFORMATION, FEEDBACK OR TO SUGGEST IMPROVEMENTS FOR THIS DOCUMENT, PLEASE SEND YOUR SUGGESTIONS OR INQUIRIES TO:
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
4 THE CHALLENGES INCREASE IN INFORMATION FOOTPRINT DEMAND FOR HIGH DENSITY CLOUD CONSOLIDATION OF POWER DEMAND OVERLOADING OF OUTDATED POWER GRID GLOBAL NETWORK LOAD CREATING EXERGY
5 ENERGY FOOTPRINT OF INFORMATION FACILITIES Datacentres, Server rooms, Network hubs etc. Estimated 4% Global Electricity Production (25 PWh) 4% = 1 PWh Wh (10 15 )
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. 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)
7 GLOBAL PUE: APPROX. 1.7 UPS/Nobreak 2% Other 2% Global estimated PUE breakdown Cooling 37% ICT 59% Fans (20%) 10% Information (65%) 40% Power supply (15%) 9%
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.
9 ACTUAL INFORMATION EFFICIENCY Actual 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 Information 40% Cooling + IT fans 47% 1000 TWh/400TWh PUE equivalent: 2.5 Other 2% UPS+IT Power supply 11%
10 ENERGY TRANSFORMATION Global thermal energy production by Information J or 1.9 EJ (10 18 ) (529 TJ/s*3600): Energy for heat rejection EXERGY DESTRUCTION: Wh
11 WHAT IF INFORMATION FACILITIES COULD... EXCLUDE COOLING INSTALLATIONS REDUCE IT OVERHEAD BALANCE THE POWER GRID REDUCE THE DATA NETWORK LOAD BECOME ENERGY PRODUCERS
12 COOLING THE CLOUD 1 MW critical load, ΔT of 10 C Thermal production: 1MJ/s 1 C rise with air: 1005 J/kg C * kg/l = J/L/s 1MJ/s requires: J/(10 C *1.2 J) 83333L/s AIR
13 83333 L/s AIR VS WATER 1 MJ/s 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 Liquid can travel 200 TIMES THE DISTANCE with same thermal losses THE DATACENTER OF THE FUTURE: 6 L/s AND IS AN ENERGY PRODUCER...
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.
15 THE WRONG QUESTION DON T ASK WHICH TECHNOLOGY TO USE CHOOSE BETWEEN AIR OR LIQUID THEN COMBINE LIQUID TECHNOLOGIES
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: C / 55 C Extreme / max ΔT 10 C
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: C / max ΔT 15 C
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: C / 28 C Extreme / max ΔT 12 C
19 OPTIMISING LIQUID INFRASTRUCTURES TECHNOLOGY NORMAL INLET OUTLET CRAC (generic) 6-18 C C ILC (U-Systems) C C DLC (Asetek) C C TLC (Asperitas) C 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
20 INCREASING ΔT WITH TEMPERATURE CHAINING Serial implementation of the infrastructure 17 C CRAC Parallel ILC Parallel TLC & DLC paired TLC & DLC paired Facility output +5 C Output 22 C +6 C Output 28 C +16 C Output 44 C +16 C Output 60 C 60 C CREATE HIGH T 3-stage cooling for low water volume Down to 35 C, free-air Between C, adiabatic Below 28 C, chiller USABLE HEAT
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 120 kw ILC +6 C Facility input 20 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 Stage 1 ILC 26 C +8 C +5 C +7 C +6 C +2 C +7 C +9 C +5 C +3 C +2 C +6 C +7 C 400 kw TLC 40 kw DLC +19 C Stage 2 DLC & TLC +5 C +6 C +6 C +7 C +6 C +6 C +6 C +6 C +7 C +4 C +3 C +6 C 45 C 160 kw TLC 60 kw DLC +15 C +7 C +10 C +7 C +9 C +17 C +12 C +14 C +16 C +7 C +8 C +6 C +7 C Stage 3 Optimised DLC&TLC Facility output 60 C
22 REUSE MICRO INFRASTRUCTURE Micro datacentre or server room Open water circuit Reusable requirement: 65 C Variable volume Feedback loop for constant temperature 51 C +7 C +7 C Variable temp Facility input 5-40 C Constant temp Facility output 65 C
23 TEMPERATURE CHAINING IMPACT L/s AIR VS WATER 1 MJ/s 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
24 DATACENTRE DESIGN DESIGNED FOR AIR 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/m 2 Concrete floor + Raised floors Power UPS (IT only): 100% Gensets (facility): 100% DESIGNED FOR MIXED LIQUID 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/m 2 Bare concrete floor Power (compared to air) UPS (IT only): 90% Gensets: 60%
25 SITE PLANNING AND QUALIFICATION Minimised energy footprint Minimised installations requirements Flexibility by minimal environmental impact FOCUS ON 24/7 HEAT CONSUMERS
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
27 DISTRIBUTED MICRO EDGE NODES kw 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) 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
28 CORE DATACENTRES Industrial scale reuse infrastructures 100% 24/7 heat reuse Agriculture Spas Cooking, pressurising, sterilisation, bleaching Distillation, concentrating, drying or Kilning Chemical Large facilities No-break systems Limited cooling infrastructure 24/7 information availability Edge management Replicated Edge back-end Communication hub Exergy destruction Rivers/ocean Liquid-to-air rejection
29 EDGE MANAGEMENT Emerging platforms for decentralised cluster management Integration with energy and heat management CLOUD CUSTOMERS CLOUD DEMAND.ware HARDWARE INSTALLATION Q.RADS, O.MAR, AIC24 HEAT DEMAND CUSTOMERS COMPUTING JOBS COMPUTING RESULTS CLOUD DEMAND DISTRIBUTION MANAGEMENT FOR HEATING INFORMATION HARDWARE JOB SCHEDULING HEAT DEMAND COMPUTING JOBS COMPUTING RESULTS Free and green heat.rads
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 m 2 Reduced operational cost Reduced maintenance on installations High IT density Higher specs IT hardware, also for cloud Reduced software cost
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
32 WHAT NEEDS TO BE DONE? Focus on heat consumption without dependency Not with an invoice Free cooling guarantee UPS/Nobreak 2% Other 2% PUE inefficiency Government involvement Incentives Intermediate for (industrial) heat reuse Information footprint as part of district planning More (low grade) heating networks Cooling 37% ICT 59% Fans (20%) 10% Information (65%) 40% Power supply (15%) 9% 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 FEAR OF WATER
33 THE DATACENTRE OF THE FUTURE? THE FUTURE IS NOW!
+31 88 96 000 00 www.asperitas.com ASPERITAS COMPANY Privately owned and funded Rolf Brink/Markus Mandemaker History Aecorsis BV founded in 2014 Modernising the marine industry Micro datacentre for marine
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