Ron hutchins ga_tech

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  • 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