
Energy-Efficient Computing and Data Centers
Description
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Content
- 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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