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Liam Newcombe BCS Data Centre Specialist Group Secretary Modelling Data Centre Energy Efficiency and Cost.

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Presentation on theme: "Liam Newcombe BCS Data Centre Specialist Group Secretary Modelling Data Centre Energy Efficiency and Cost."— Presentation transcript:

1 Liam Newcombe BCS Data Centre Specialist Group Secretary Modelling Data Centre Energy Efficiency and Cost

2 BCS Data Centre Simulator Background Overview of Tools Structure of the BCS Simulator Input Data Sample Output Development Path

3 Background

4 Power Loss Chain – Fossil Fuel – CPU Used

5 “For each £ or Watt my Data Centre consumes what output do I get?” vs. “For each Service I deliver what is the financial and energy cost?” Data Centre Cost and Energy

6 Overview of Tools

7 Tool Coverage Existing tools –Computational Fluid Dynamics –Server benchmarking –Chiller technology comparisons –Carbon ‘calculators’ –Device specific comparators

8 Tool Problem When the only tool you have is a hammer everything looks like a nail 1 1) Abraham Maslow

9 Tool Problem The data centre is not a set of independent components that can be individually tuned The data centre is a complex and interdependent system Only a holistic tool can give useful answers

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15 Framework Tool One tool to cover the entire system, allowing the simulation of components in a realistic context. No need to develop more partial tools, you can now contribute to the open, trusted tool instead.

16 Framework Tool Designed to facilitate the incorporation of new or enhanced component models and data Publish performance data in standard formats that we can use to compare devices

17 Structure of the BCS Simulator

18 BCS Data Centre Model IT Workload IT Device Load to Power Function Data Centre Power Transfer Function

19 IT Device

20 IT Device Costs

21 IT Device in a Data Centre

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23 Energy Costs

24 Per Device Costs

25 Input Data

26 Fully Representative Data

27 Open XML Formats

28 Sample Output

29 Example Scenario Simulator Output Same Computing Workload 100 One App Per Server Servers 15 Virtualised Servers 10 HPC Grid Servers Old N+1 Data Centre, Nameplate Provisioning

30 Simulator Output Old N+1 Data Centre, Nameplate

31 Simulator Output

32 Example Scenario Same Computing Workload 100 One App Per Server Servers 15 Virtualised Servers 10 HPC Grid Servers New N+1 Data Centre, Free Cooling Simulator Output

33 New N+1 Data Centre, Free Cooling 19°C Simulator Output

34 New N+1 Data Centre, Free Cooling 25°C Simulator Output

35 New N+1 Data Centre, Free Cooling 25°C Simulator Output

36 New N+1 Data Centre, Free Cooling 25°C Simulator Output

37 Development Path

38 Data Centre energy use and cost is a complex problem that we are only starting to understand Deliver marginal and fair share, per business service energy and financial costs to enable holistic carbon management

39 Development Path Individual component ‘calculators’ are ineffective without the context of a holistic model Device level A-G style simple labelling is not effective in a data centre environment

40 Development Path As our understanding of the data centre grows we will be able to use the more complex capabilities of the simulator

41 Development Path Opportunities for Further Research and Development IT Device Performance –Configuration –Workload –Generalised Metrics ( Performance / Energy ) –Networking –Storage

42 Development Path Opportunities for Further Research and Development Application Performance –Hardware interaction –Impact of the working data set –Optimisation

43 Development Path Opportunities for Further Research and Development Economics ( Cost and Energy ) –Intelligent task deployment –Per task accounting –Automated in-source / out-source decisions –Real time cost management and reporting –Policy based management

44 Development Path Opportunities for Further Research and Development Physics –Integrated Computational Fluid Dynamics –Chiller plant behaviour and management –Workload assignment

45 Development Path Opportunities for Further Research and Development Electrical / Electronic Engineering –Power infrastructure performance and loss characteristics –Dynamic self provisioning electrical infrastructure


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