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Data Center Energy Efficiency: Analysis and Test of Energy Consumption Benchmark Tools. Erick Butler Poletto (Matricola: 720403) Ricardo Alexandre Fiorelli (Matricola: 719874) Prof.ssa Chiara Francalanci. July 21 th , 2009. Outline. Introduction Research Objectives Methodology
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Data Center Energy Efficiency: Analysisand Test of Energy ConsumptionBenchmark Tools Erick Butler Poletto (Matricola: 720403) Ricardo Alexandre Fiorelli (Matricola: 719874) Prof.ssa Chiara Francalanci July 21th, 2009
Outline • Introduction • Research Objectives • Methodology • Analysis and Conclusions • Further Work
Green ICT or Green Computing • What is Green Computing? • Green ICT Phases • Assessment and Action Plan • Green ICT Benefits: • Reduction of costs • Reduction of power consumption • Reduction of data center used area • Marketing strategy
Green ICT: Approaches Green of ICT Green by ICT Reduce the burden on the environment by improving efficiency through the use of ICT Reduce the burden of ICT on the environment • Data Center • Centralization • Hosting • Communication • Remote Data Access
State of the Art research • Machine Configuration • Policies / Tools / Labels • Thin Client Architectures • Virtualization in servers • Data Storage • Power Architectures • Cooling
Outline • Introduction • Research Objectives • Methodology • Analysis and Conclusions • Further Work
Research Objectives • Creation of a Database of components • Evaluate power consumption data of a benchmarking tool (SANDRA) • Identification of critical power consumption spots in a datacenter • Easy choice of power-efficient machine configurations Objectives Benefits
Outline • Introduction • Research Objectives • Methodology • Analysis and Conclusions • Further Work
Acquisition of Data • For Database of Components: • SiSoftware Sandra • WebSPHINX (web crawler) • For Data Validation: • Energy Measurement Device
Sandra (benchmarking tool) • Benchmark for several typologies of components • Database of components that permits comparisons between them • Provides information about components power, performance and price
Sandra Database • Main source of gathered data • Sandra database – no centralized component repository • Each benchmark has its own list of components • Solution: • Introduction of the MPN code
Component Database • Set of categories and relations: • Classification Relations • Characteristic Relations • Benchmark Relations • Price Relation • Provides a way to compare and evaluate the data center components
Energy Measurement Device • Validate the measures from Sandra
Outline • Introduction • Research Objectives • Methodology • Analysis and Conclusions • Further Work
Result Analysis :Measurements • Comparison between: • Sandra estimated processor power • Nominal processor power (specification) • Sandra measured power > nominal power for 30% of the components
Result Analysis: Comparison • Idle and stressed processor
Result Analysis • Why Sandra is not reliable? • Sandra power estimates can be are higher than nominal power • Its measures differ by a large margin from the ones made with the measuring tool
Result Analysis • Possible reasons for observed Sandra innacuracies: • Not centralized component database • Sandra may associate the benchmarked component to a different one in its database • Power information can be erroneous • Power information is not associated with the machine workload • Does it refer to idle or stressed component?
Result Analysis • Measurement error sources: • Power hypotheses: • Hard Drives and Wireless << Processor, Memory or PSU • Oscillations in measurement • Use of PSU and monitor power estimates
Result Analysis • Although the measurements were not completely accurate themselves, Sandra was regarded as non reliable • Sum of hard disk and wireless card powers usually is around 2,5W • For a certain operation level, the measured power did not oscillate much • In some cases, Sandra provided a processor power estimate incoherent with their nominal power • The error commited in the estimates of the PSU and monitor power do not explain the observed deviations
Conclusions • The database of components is a very effective tool • With relation to power consumption, Sandra is not the best source of data • Other sources of power-related data should be considered
Outline • Introduction • Research Objectives • Methodology • Analysis and Conclusions • Further Work
Further Work • Automated update of the database. A back-end robot would crawl the web for new components and their specifications/prices • Use of a new source of power-related data • a GUI front-end software for an interactive and effective way of comparing the components
Thank you Erick Butler Poletto Ricardo Alexandre Fiorelli