Presentation by Mike Kelly CEO DataCentred at 2014 Data Centre World, asking does PUE miss the point? Traditionally in data centres there has been no end to end view of energy efficiency. Chip designers have used techniques to make on-chip and on-board calculations efficient; rack builders have devised techniques which are efficient in cooling servers within racks and within containment systems for pods of racks; data centre operators have ensured that bulk efficiency of supposed compute energy demand versus total energy demand are as low as possible. The reality, however, is that since no part of this chain has sight of the others, what is described as total efficiency, PUE, may bear no relation to compute efficiency at all. In large single user data centres, an end to end view is increasingly possible, and is a better measure of energy efficiency. This presentation explores whether some of these end to end measures and some the efficiency techniques they lead to, could be used in a multi-tenancy data centre.

1. Energy Efficiency in Multi-
Tenanted Data Centres
Dr Mike Kelly
CEO

2. Data Centre Evolution
1990-2005
Colocation
2005-2007
Density
2007-2011
Containment
2011+
Modular
2.0 PUE
1.4 – 1.6 PUE 1.2 – 1.5 PUE
1.05 –1.15 PUE
Rack
Density & deployment
Free air cooling
Raise temperatures
Server
Capacity
20 year technology
Containers, PODs
Scalability
Sustainability
Hot & cold aisle
containment
Modular
CHP/ renewable energy
Free air

3. Scale of the challenge
1%?
10%?

4. Does PUE miss the point?
• PUE measures energy consumption
• PUE concentration allows some energy saving
from historic baseline, ~30%, but real
compute efficiency could be very low
• Greater deficiency
– Assumes (in a sense) that all IT power
consumption is productive
– In reality actual use of silicon estate could be very
low, <10%

5. Efficiency and Utilisation
Source: Blackburn, 2008

6. PUE+
Compute efficiency as well as PUE

7. Single user data centre
• Single user will manage
data centre and compute
resource
• ‘Knows’ what’s happening
– can measure actual
compute efficiency
• Can measure compute
cycles per watt
• Can maximise efficiency
because can use shared
compute resource across
range of applications

8. How can we do this in multi-tenant

9. Colo plus
Traditional Colocation Facility New Facility

10. Many types of Cloud

11. Future Data Centres Internal
Environment – Radical OCP
• Form factors matched at
all scales
• Boards sit in racks as
moveable chassis
– Self supporting and
stackable
• Wireless networks
• Pluggable bulk connectors
for rack scale form factor
• ‘Racks’ stackable and
constructable for
reconfiguration and
convection friendly
shapes
• Robotic movement of
‘racks’ in high bay
warehouse like
environment
• Performance measures
IIOPs per watt, IPS or
FLOPS per watt
• Complete integration of
compute and internal
network with physical
operation of data centre
• Data centres as
neighbourhood hot spots
of pervasive compute

12. Future Data Centres in their
Environment
• Factories of continuous production
– Never idle
– Continuous renewal of equipment
– On site generation
• Neighbourhood resource like urban power
stations
• Integrated into CHP schemes
• Use of heat to create urban vegetation
production in biodomes in temperate zones
– Can achieve high radiative forcing levels

13. Compute Efficiency in Future Data
Centres
• Compute efficiency in data centres can’t be
achieved without use of local cloud
• Can’t be achieved without shared monitoring
• Can’t be achieved without shared resources
• Sharing of data centres is relatively novel
• Sharing compute systems is something IT
service providers ask their users to do all the
time
• Sauce for the goose