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Energy efficiency and research computing RUGIT Away Day, 24th Jan 2008

Energy efficiency and research computing RUGIT Away Day, 24th Jan 2008. Dave Berry Deputy Director, NeSC & Technology Lead, Grid Computing Now! daveb@nesc.ac.uk. Contents. Background and goals Desktop Grids for High Throughput Computing Data centres and HPC centres Ways forward.

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Energy efficiency and research computing RUGIT Away Day, 24th Jan 2008

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  1. Energy efficiency and research computingRUGIT Away Day, 24th Jan 2008 Dave Berry Deputy Director, NeSC & Technology Lead, Grid Computing Now! daveb@nesc.ac.uk www.gridcomputingnow.org

  2. Contents • Background and goals • Desktop Grids for High Throughput Computing • Data centres and HPC centres • Ways forward www.gridcomputingnow.org

  3. GCN! Aims • Accelerate the benefits to the UK economy of adopting modern computing technologies, i.e.: • The creation of scalable, secure, efficient ICT infrastructures, • For delivering IT services, linked to business processes through a service oriented architecture, • While achieving greater utilisation with reduced energy consumption and reduced costs www.gridcomputingnow.org

  4. Knowledge Transfer Network • Part of the Technology Strategy Board’s Innovation Programme • Run by Intellect, NeSC and CNR • Activities • Web platform; user case studies; events; webinars; active sector and regional programme • Communities of Practice • Green IT (including MBE KTN, BCS, …) • Transport Modelling, Grids in Health, Public sector IT, … www.gridcomputingnow.org

  5. Aims for this session • To expand our community of practice • Stimulate discussion • Share knowledge • Form relationships • Suggest a “best practices” document • Input to policy (Unis, RCs, government) • Want to learn as much as inform www.gridcomputingnow.org

  6. Desktop Grids • High Throughput Computing • Many experimental scientists are more interested in number of jobs/month rather than instantaneous computing power • One approach: use “Spare” Cycles • No need for air conditioning, etc. • But don’t we want to switch off machines at night? • Claim: desktop grids can give computing power for less cost and less electricity www.gridcomputingnow.org

  7. Cardiff slides from James Osborne, High-Throughput Computing Week NeSC, 27-30 November 2008 Central Manager master, collector, negotiator Execute Nodes 1600 Workstations Submit Nodes 30 Workstations master, schedd, shadow master, startd, starter

  8. Based on a P4 3GHz PC with 512MB RAM Power Consumption

  9. Based on a P4 3GHz PC with 512MB RAM Economic Viability • Makes sound financial sense • Hibernate saves £60 per year • Condor = £30 per year (max) • Dedicated = £150 per year • Condor is 5 times cheaper Saving of Hibernate = Cost of 100W Electricity (Idle State) for 16 Hours out of 24 Cost of Condor = Cost of 150W Electricity (Condor State) – Cost of 100W Electricity (Idle State) Cost of Dedicated = Cost of 150W Electricity (Condor State) + Cost of 100W Electricity (Air Con)

  10. Based on a P4 3GHz PC with 512MB RAM Environmental Impact • Makes sound environmental sense • Hibernate saves 650Kg CO2 per year • Condor = 325Kg CO2 per year (max) • Dedicated = 1,625Kg CO2 per year • Condor is 5 times greener Saving of Hibernate = Cost of 100W Electricity (Idle State) for 16 Hours out of 24 Cost of Condor = Cost of 150W Electricity (Condor State) – Cost of 100W Electricity (Idle State) Cost of Dedicated = Cost of 150W Electricity (Condor State) + Cost of 100W Electricity (Air Con)

  11. Based on 10,000 P4 3GHz PCs with 512MB RAM Across Campus • Makes sound financial sense • Hibernate would save £600,000 per year • Hibernate 16 out of 24 hours • Makes sound environmental sense • Hibernate would save 6,500T CO2 per year • Rainforest required = 52Km2 • Rainforest required = 40% area of Cardiff Saving of Hibernate = Cost of 100W Electricity (Idle State) for 16 Hours out of 24 Cost of Condor = Cost of 150W Electricity (Condor State) – Cost of 100W Electricity (Idle State) Cost of Dedicated = Cost of 150W Electricity (Condor State) + Cost of 100W Electricity (Air Con)

  12. The best of both worlds? • What if we could power-off idle machines and wake them up when Condor has jobs to run? • JISC Low Carbon ICT project • http://projects.oucs.ox.ac.uk/lowcarbonict/ • Develop an institution-wide wake-on-LAN service • Monitor energy consumption across the University • Write and implement a communications strategy • Towards Low Carbon ICT conference • Oxford, 19th March 2008 www.gridcomputingnow.org

  13. Data Centres and HPC Centres Need: 2xProcessing Capacity per annum; Target: 60% Energy Reduction from 1990 levels by 2050 www.gridcomputingnow.org

  14. The scale of the problem • Power consumption by data centres: • Estimated 1.5% of UK national electricity generation • Peak consumption of 8GW • Estimated to rise from 46 TWH in 2006 to 93 TWH in 2020 • Comparable with consumption by refrigeration… • … or greenhouse gases emitted by aviation www.gridcomputingnow.org

  15. Technology Power Loss Chain:Fossil Fuel – CPU Used Slide from BCS DCSG

  16. Policies and measurement • BCS DCSG model • Open source model of energy-efficiency for data centres and servers • The Green Grid • Vendor consortium • EU code of conduct on data centres • Development of baseline measures • Voluntary contribution of data from subscribing organisations www.gridcomputingnow.org

  17. Press Examples • Ultraspeed DC-based system in East London • Claims 30% power saving from use of DC • Extra 10% saving from diskless servers • http://pcworld.about.com/od/recyclin1/Data-center-claims-power-cuts.htm • Plan for green data farm in Lockerbie • Using renewable energy sources • Waste heat used to heat new “eco village” • http://www.redwasp.co.uk/newsitem.asp?id=280 www.gridcomputingnow.org

  18. GCN! Webinar • The Business Case and Methods for the Green Data Centre • Recording available on the web • Zahl Limbuwala • Chair, BCS Data Centre Specialist Group • Motivation and an introduction to the BCS model • Kate Craig Wood • Managing Director, Memset Ltd. • Practical steps to running a “carbon-neutral” data centre www.gridcomputingnow.org

  19. Finance and administration • Who sees the power bills? • Who calculates the total cost of ownership? • Does this affect purchasing decisions? • Trade-off: cost of reliability vs. cost of downtime • Don’t overspecify • Staff requirements • Specialised HPC kit may need specialised staff • Other kit may not www.gridcomputingnow.org

  20. Power engineering • Location • Near power stations • Or local generation (CHP?) • AC or DC? • Provisioning levels • Nameplate provisioning is inefficient • Cables • Oversize for lower resistance (can halve losses) • Route through cool underfloor area www.gridcomputingnow.org

  21. Example benchmarks Slide from Kate Craig-Wood

  22. Graded UPS usage • Latest switch-mode based generation vastly more efficient • 96-96% vs. ~90% • Most efficient when fully loaded (98%)‏ • Don't run at half-capacity • 40KVA steps, rather than typical 500KVA steps Slide from Kate Craig-Wood

  23. Cooling • What target temperature? • Water or air? • Store heated water externally? • External air or recycled air? • Savings from fresh air cooling of 72% (Source: BCS) • Modular cooling • Cabinets or rooms? • Modelling and controlling heat flow • Waste heat • How to sell or reuse? www.gridcomputingnow.org

  24. Fresh Air Cooling www.gridcomputingnow.org

  25. State of the art? • “By careful design, matching the specification of the plant to the needs of the machine(s) we have brought the summer time cooling overhead down from 60 - 65% (very typical of most computer rooms) to 25 - 30%. • Further, by using freecool this drops to 7% in the winter.” www.gridcomputingnow.org

  26. System utilisation • Server virtualisation • Load balancing • Note – this is typically done already for compute clusters • May still apply to other university systems • Choice of equipment • Multi-core, power management, etc. • Diskless servers www.gridcomputingnow.org

  27. Ways forward • Best practice document(s) • Perhaps proven + experimental? • Shared facilities • Shared data centres? • Shared compute clusters (a la NGS)? • Training for IT staff? • Case studies? • Input to policy (Unis, RCs, government) www.gridcomputingnow.org

  28. Benchmarks and Labelling Slide from BCS DCSG

  29. More references • GCN! Webinar • http://tinyurl.com/2gtslj • BCS Data Centre Specialist Group • http://tinyurl.com/2dyy5t • EU Code of Conduct • http://tinyurl.com/2drxoh • HTC week • http://www.nesc.ac.uk/action/esi/contribution.cfm?Title=831 • Technology Strategy Board • http://www.berr.gov.uk/innovation/technologystrategyboard www.gridcomputingnow.org

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