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Energy-Driven Computing Performance Optimization: Rethinking Objectives

Explore the fusion of energy consumption and performance goals in data-intensive computing. Investigate opportunities for energy-efficient query optimization in databases. Delve into the alignment of hardware and software needs to enhance energy efficiency. Collaboration between stakeholders and holistic approaches essential for effective energy consumption optimization. Funded by NSF and Microsoft, with student Willis Lang and Jignesh M. Patel.

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Energy-Driven Computing Performance Optimization: Rethinking Objectives

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  1. Energy Consumption as a First-Class “Performance” Goal for Data Intensive Computing Credits: Student: Willis Lang Funding: NSF, Microsoft Jignesh M. Patel

  2. Rethinking Objectives for Data Intensive Computing Performance Performance SLA Requirements Energy Consumption

  3. Energy Efficiency Opportunities

  4. Energy-Enhanced DBMS Query Optimization SLA Commercial DB: join, 5GB WB tables, 0.01% selectivity

  5. Synergies

  6. Questions? • Can the hardware and software tango together? • Does the hardware provide mechanisms that the software really needs? • Can the software specify what it needs from the hardware? • At the DC level, what are the real pain-points in energy-efficiency? • Need to take a holistic end-to-end approach • Are the low DC utilization observations still relevant with techniques like spot-pricing?

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