The document discusses the need for optimizing data centers in a holistic, systems approach. It describes how a data center functions similarly to a computer chip with multiple optimized components. It proposes the development of a research data center facility that would contain the best current capabilities across cooling, power, networking, and software optimization. This facility would have extensive monitoring sensors to directly control and optimize operations based on real-time data.

1. The DataCenter is the Computer
Ron Hutchins, PhD
Associate Vice Provost for Research and
Technology, and Chief Technology Officer
Georgia Tech

2. Motivation and
Articulation of the Problem
• Simulation and modeling, as well as analytics, as
motivation today
• Growth of computing need for simulation is linear at
worst (best?)
• Hosting costs are growing, sustainability must be
considered
• A complex adaptive systems problem, not a simple one
dimensional issue: power/smart grid, cooling, outside
air, local water consumption/gray water, data center
network, monitoring, world-wide distribution of
partnered systems, chip clocking, black box vs manned,
software characteristics

3. The meta computer
• Large scale CPU consolidation into high density racking with in-row
cooling.
• Large storage arrays with multiple speeds/sizes separate from
Compute section including high speed scratch storage (like main
memory?)
• High performance networking switching can be compared to
backplane
• High speed connections with outside world
• Interactions across multiple data centers.
• Data center provides “heat sync” capabilities at large scale.
So… like we optimized the CPU chip by making it multi-core, L2 cache,
variable clock speed, etc., we need to work the same way with the
data center optimization – small pieces that can add up to a lot

4. power/smart grid
• Today’s power varies in price around the US
and the World and is growing rapidly

5. cooling, outside air, local water
consumption/gray water
• Cold isle temperature recommendations are
changing. Air side economizing is becoming
more viable for more areas – requires careful
monitoring?
• Water is a big issue in the future. Gray water
capture/use is complex.
http://www.internap.com/colocation-
provider-facility-overview/green-data-centers/

6. Gray Water (cont)

7. chip clocking
“Designers now face a difficult choice between
increasing clock frequency to improve
performance and paying a large penalty in power
consumption, or reducing power with little gain
in the performance per gate of the design and
using more gates (silicon) for performance gains.”
http://www.eetimes.com/design/eda-
design/4018851/Greening-processor-design

8. data center network, monitoring
• Data center networks appear like WAN
networks due to the number of devices
attached – and the complexity of
interconnection.
• MPLS and VLANs rule the networks and create
complex architectures. Complexity is king.
• Collected data is basically for billing, not
operational/optimization purposes.

9. software characteristics
• Long running codes – sensitive to failures
• Highly parallel codes – sensitive to
interconnect
• Decoupled serial jobs – highly mobile
• Web services – stateless
• Database – hard to distribute and hard to
replicate in real time.

10. A Research Instrument –
A Systems Approach
• A production capable facility containing the best current capabilities
across multiple disciplines, a capability of being easily adaptable for
future innovations – including waste heat reuse in adjoining office
tower.
• Careful placement of sensors (air pressure, temperature, humidity,
power use) throughout the data center and in high performance
computer racks and chassis.
• Direct coupling of output of sensors to:
– Outside air controls
– Chip clocking controls
– Software schedulers
– Geographic prioritization
– Smart Grid/spot market for power
– Data center networking managed for optimization not billing

11. GT Advance Planning:
“Georgia Tech High Performance
Innovation Ecosystem”?
• http://www.realestate.gatech.edu/hpc/index.
php