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Standard-sized container - Very efficient air-flow

Quantifying the Environmental Advantages of Large-Scale Computing Vlasia Anagnostopoulou , Heba Saadeldeen , and Frederic T. Chong. INTRO. BACKGROUND. EXP. MODEL.

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Standard-sized container - Very efficient air-flow

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  1. Quantifying the Environmental Advantages of Large-Scale Computing VlasiaAnagnostopoulou, HebaSaadeldeen, and Frederic T. Chong INTRO BACKGROUND EXP. MODEL Cloud Computing has offered new possibilities to small companies, especially start-ups, as it allows them to harness substantial processing power and large storage without the cost of deploying and maintaining an actual computing system locally. However, the manufacturing and use phase of datacenters burden the environment significantly: - A desktop computer requires 260 kg of fossil fuel + 6400 MJ of energy for its production - An average cooling unit requires 527 kg of primary materials, while an average power unit 8 tons. - As of 2006, U.S. datacenters consumed 10% of total U.S. energy consumption, projected to double in 5 years Besides deployment costs, what are the environmental and operational costs with datacenter scale? Datacenter case: Various datacenter sizes - Comp. room (1-2 racks), Small (20) , Medium (50), Large (100) - Building /container installation - Cooling and power provisioned w/o redundancy (tier-I) and w. N+1 redundancy (tier-II) - In case of comp. room, assume existing chilled-water loop Business case: -Two representative types of business apps - E-commerce - Financial Simulated by TPC council’s TPC-C and TPC-H benchmarks (in respect) Standard-sized container - Very efficient air-flow -Better PUE (Power Usage Efficiency = Total Power/ IT-Power) - External cooling and power loops are same METHO-DOLOGY Environmental cost For each size configuration: i) From vendor’s specs, add weights of power & cooling components ii) Calculate amount of materials iiiI) Use material breakdown tables to come up with amount of metals, plastic, and glass/ceramic • Capital cost (CAPEX) • Cooling and Power CAPEX (part of TCO) • Assumptions: • Loan with interest rate: 8% • Cooling & Power provisioning: 2x • Application-requirements double every 2 years • Small facility upgrade period is 4 years • Large facility upgrade is 6 months, except for Chiller • Life-cycle of 10 years • Operational cost (OPEX) • Calculated PUE based on: • Active-power*work-hours + Idle-power*idle-hours • Power based on inefficiency related to size • For container, used PUE from specs (same for all sizes) RESULTS • Lesson #1: Material efficiency • - Large (tier-I) installations are up to 53% more efficient • - Tier-II (w. N+1 redundancy) up to 75% • Preferring a large installation can save up to 95 tons of materials, from which: • Primary metals: 62 tons • Plastics: 27 tons • Glass/Ceramic: 7 tons • -Because of disproportional use of materials in power and cooling manufacturing + effect of redundancy Lesson #3: Operational efficiency - Large (building) installations can have up to 16% better PUE - Their operational energy consumption can be up to 67% less - Containers can have up to 38% better PUE - Because the larger the datacenter, the less inefficiencies in power and cooling - Although we don’t evaluate here, large datacenter have better practices and more staff resources • Lesson #2: Cost advantage • - A large installation can be up to 24% cheaper • - Because of faster outpayment of loans • However, a small datacenter installation is 10% more expensive compared to an equivalent # of comp. rooms • Because we assume that in the case of a comp. room deployment, • the building’s chilled-water loop is used

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