Energy-Efficient Computing and Data Centers.

Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Introduction -- Acknowledgments -- 1. Systems in Data Centers -- 1.1. Servers -- 1.2. Storage arrays -- 1.3. Data center networking -- 1.4. Components -- 1.4.1. Central processing unit -- 1.4.2. Graphics processing unit -- 1.4.3. Volatile memory -- 1.4.4. Non-volatile memory -- 1.4.5. Non-volatile storage -- 1.4.6. Spinning disks and tape storage -- 1.4.7. Motherboard -- 1.4.8. PCIe I/O cards -- 1.4.9. Power supplies -- 1.4.10. Fans -- 2. Cooling Servers -- 2.1. Evolution of cooling for mainframe, midrange and distributed computers from the 1960s to 1990s -- 2.2. Emergence of cooling for scale out computers from 1990s to 2010s -- 2.3. Chassis and rack cooling methods -- 2.4. Metrics considered for cooling -- 2.4.1. Efficiency -- 2.4.2. Reliability cost -- 2.4.3. Thermal performance -- 2.5. Material used for cooling -- 2.6. System layout and cooling air flow optimization -- 3. Cooling the Data Center -- 3.1. System cooling technologies used -- 3.2. Air-cooled data center -- 3.2.1. Conventional air-cooled data center -- 3.3. ASHRAE data center cooling standards -- 3.3.1. Operation and temperature classes -- 3.3.2. Liquid cooling classes -- 3.3.3. Server and rack power trend -- 3.4. Liquid-cooled racks -- 3.5. Liquid-cooled servers -- 3.5.1. Water heat capacity -- 3.5.2. Thermal conduction module -- 3.5.3. Full node heat removal with cold plates -- 3.5.4. Modular heat removal with cold plates -- 3.5.5. Immersion cooling -- 3.5.6. Recent DWC servers -- 3.6. Free cooling -- 3.7. Waste heat reuse -- 3.7.1. Reusing heat as heat -- 3.7.2. Transforming heat with adsorption chillers -- 4. Power Consumption of Servers and Workloads -- 4.1. Trends in power consumption for processors -- 4.1.1. Moore's and Dennard's laws -- 4.1.2. Floating point instructions on Xeon processors.

4.1.3. CPU frequency of instructions on Intel Xeon processors -- 4.2. Trends in power consumption for GPUs -- 4.2.1. Moore's and Dennard's laws -- 4.3. ACPI states -- 4.4. The power equation -- 5. Power and Performance of Workloads -- 5.1. Power and performance of workloads -- 5.1.1. SKU power and performance variations -- 5.1.2. System parameters -- 5.1.3. Workloads used -- 5.1.4. CPU-bound and memory-bound workloads -- 5.1.5. DC node power versus components power -- 5.2. Power, thermal and performance on air-cooled servers with Intel Xeon -- 5.2.1. Frequency, power and performance of simple SIMD instructions -- 5.2.2. Power, thermal and performance behavior of HPL -- 5.2.3. Power, thermal and performance behavior of STREAM -- 5.2.4. Power, thermal and performance behavior of real workloads -- 5.2.5. Power, thermal and frequency differences between CPUs -- 5.3. Power, thermal and performance on water-cooled servers with Intel Xeon -- 5.3.1. Impact on CPU temperature -- 5.3.2. Impact on voltage and frequency -- 5.3.3. Impact on power consumption and performance -- 5.4. Conclusions on the impact of cooling on power and performance -- 6. Monitoring and Controlling Power and Performance of Servers and Data Centers -- 6.1. Monitoring power and performance of servers -- 6.1.1. Sensors and APIs for power and thermal monitoring on servers -- 6.1.2. Monitoring performance on servers -- 6.2. Modeling power and performance of servers -- 6.2.1. Cycle-accurate performance models -- 6.2.2. Descriptive models -- 6.2.3. Predictive models -- 6.3. Software to optimize power and energy of servers -- 6.3.1. LoadLeveler job scheduler with energy aware feature -- 6.3.2. Energy Aware Runtime (EAR) -- 6.3.3. Other run time systems to manage power -- 6.4. Monitoring, controlling and optimizing the data center -- 6.4.1. Monitoring the data center.

6.4.2. Integration of the data center infrastructure with the IT devices -- 7. PUE, ERE and TCO of Various Cooling Solutions -- 7.1. Power usage effectiveness, energy reuse effectiveness and total cost of ownership -- 7.1.1. Power usage effectiveness and energy reuse effectiveness -- 7.1.2. PUE and free cooling -- 7.1.3. ERE and waste heat reuse -- 7.2. Examples of data centers PUE and EREs -- 7.2.1. NREL Research Support Facility, CO -- 7.2.2. Leibnitz Supercomputing data center in Germany -- 7.3. Impact of cooling on TCO with no waste heat reuse -- 7.3.1. Impact of electricity price on TCO -- 7.3.2. Impact of node power on TCO -- 7.3.3. Impact of free cooling on TCO -- 7.4. Emerging technologies and their impact on TCO -- 7.4.1. Waste heat reuse -- 7.4.2. Renewable electricity generation -- 7.4.3. Storing excess energy for later reuse -- 7.4.4. Toward a net-zero energy data center -- Conclusion -- References -- Index -- Other titles from iSTE in Computer Engineering -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.