Recommendations for Research and Development Activities

Activities

Although the policy recommendations outlined above offer immediate opportunities to improve the energy efficiency of data centers, there are also significant longer-term opportunities to improve data center energy efficiency through the development of new technologies and practices. These opportunities span the entire breadth of the data center: computing software; computing, storage and network hardware; the power conversion chain; heat removal; and controls. In all these areas, however, research is needed to better understand the effect of energy-efficient technologies on data center performance, availability, and cost.

The list below identifies R&D strategies that have the significant potential to affect energy use in data centers. It is not a comprehensive list but includes those items identified in the course of researching this report. A final recommendation to prepare a comprehensive R&D plan is included in this list.

Data center R&D may be pursued by federal or state governments or by industry. In particular, the government can play a valuable role by undertaking high-risk early-stage research;

conducting research that is objective, vendor-neutral, and publicly available; and by ensuring that the public interest (i.e., energy efficiency) is incorporated into research goals.

8.2.1. Computing Software

• Improve available data, metrics, and test standards to measure computational (or other “output”) energy efficiency of IT equipment (servers, storage, and network equipment); also, facilitate public availability of test applications and workloads that realistically represent the complexity and variability of computational loads.

• Improve virtualization software for all aspects of IT equipment (computation, storage, and networking) to reduce virtualization overhead, allow easier configuration and management, and dynamically match hardware resources to the load.

• Develop, validate, and demonstrate the effectiveness of virtualization software-based system power management.

• Improve software development tools and techniques to allow software to more efficiently use chip-level multiprocessing (improved parallelization).

• Develop better metrics, software development processes, and tools to improve the

efficiency of software.

• Improve application resiliency to delayed response times from power-managed storage (or other IT equipment).

8.2.2. IT Hardware (Computing, Storage and Network)

• Improve energy performance of hardware-based virtualization technologies (reduce virtualization overhead).

• Improve server platform power management capabilities.

• Develop lower power states for use at lower utilization levels.

• Improve power management for storage systems, to allow many disks to remain off most of the time with little impact on performance; investigate impact of storage latency.

• Investigate the reliability impacts of thermal cycles in a power-managed server and ways to retard thermal fatigue and thermal failures in low-cost packages.

• Investigate application of solid-state (non-mechanical) storage technologies to data centers.

8.2.3. Power Conversion Chain

• Improve the efficiency of power conversion and backup systems across all load levels and under various redundancy practices.

• Develop efficient modular and scalable power systems.

• Develop components, architectures, and standards for DC-powered data centers.

• For CHP/DG systems, continue technology development in the areas of cost reduction, system control, absorption and adsorption chiller systems, and data-center-specific cooling configurations.

• For CHP/DG installations at data centers, quantify the user and social benefits of

increased reliability, reduction in environmental emissions, and operating cost reductions.

8.2.4. Heat Removal

• Develop scientific understanding of the impact of environmental conditions (temperature, humidity, particulates and other pollutants) on IT equipment operation and reliability, to expand operating ranges without decreasing reliability.

• Explore tradeoffs between “hardening” IT equipment for more extreme environments vs. energy costs associated with maintaining tight environmental conditions.

• Develop systems and guidelines for reliable use of outside air economizers (air treatment requirements, necessary filter technology, controls and monitoring systems)

• Test, demonstrate, and evaluate emerging pre-engineered products for liquid-based energy-efficient rack, row, and in-chassis cooling.

8.2.5. Controls and Management

• Improve server operating systems to increase power management enabling rates in servers.

• Develop improved computing control strategies (such as statistical machine learning or control theory) to allow better power management of IT equipment at the system, cluster, and data center level.

• Improve hardware and control algorithms for close-coupled control of IT and HVAC systems.

• Develop active power management strategies for high-performance computing systems, e.g., taking advantage of workload imbalances to reduce the power of lightly loaded system components.

• Develop standard communication protocols to allow continuous energy monitoring and interoperability among IT equipment and data center infrastructure products.

• Develop best practices for improving energy efficiency through storage optimization and server virtualization.

8.2.6. Cross-Cutting Activities

• Develop improved public data sets of data center energy use, performance, and physical characteristics, to allow improved whole-building benchmarking models. Particular emphasis is needed to include the performance of IT equipment in these data sets to allow development of end-to-end data center performance metrics (e.g., Total Data Center Energy Use ÷ Data Processing Output). One avenue to collect these data would be the EIA’s Commercial Building Energy Consumption Survey. Also need better information about the energy-use characteristics of non-data center locations for IT equipment (e.g., server closets and rooms).

• Understand and mitigate the impact of energy-efficiency strategies on performance, availability, and cost of the data center (IT, power, and cooling);

− Identify ways in which energy efficiency affects IT equipment reliability (e.g., disk drive power management or processor thermal cycling).

− Develop technologies to improve component reliability while improving energy efficiency.

− Produce information for manufacturers, purchasers, and operators to use to

confidently make decisions about the level of redundancy actually required to meet desired levels of reliability.

• Analyze and quantify the net impact of data centers and IT equipment generally on overall U.S. energy use (e.g., trade off between e-commerce and transportation energy).

• Undertake a more comprehensive effort to assess R&D opportunities in data centers, including basic research (e.g., semiconductor materials) and opportunities in software and IT equipment that have the potential for large efficiency gains.