Format:
1 Online-Ressource (156 Seiten)
Edition:
Second edition
Edition:
Electronic reproduction; Available via World Wide Web
ISBN:
9781627050104
Series Statement:
Synthesis Lectures on Computer Architecture 24
Content:
As computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. In other words, we must treat the datacenter itself as one massive warehouse-scale computer (WSC). We describe the architecture of WSCs, the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. We hope it will be useful to architects and programmers of today's WSCs, as well as those of future many-core platforms which may one day implement the equivalent of today's WSCs on a single board
Content:
As computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. In other words, we must treat the datacenter itself as one massive warehouse-scale computer (WSC). We describe the architecture of WSCs, the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. We hope it will be useful to architects and programmers of today's WSCs, as well as those of future many-core platforms which may one day implement the equivalent of today's WSCs on a single board
Content:
1. Introduction -- 1.1 Warehouse-scale computers -- 1.2 Cost efficiency at scale -- 1.3 Not just a collection of servers -- 1.4 One datacenter vs. several datacenters -- 1.5 Why WSCS might matter to you -- 1.6 Architectural overview of WSCS -- 1.6.1 Storage -- 1.6.2 Networking fabric -- 1.6.3 Storage hierarchy -- 1.6.4 Quantifying latency, bandwidth, and capacity -- 1.6.5 Power usage -- 1.6.6 Handling failures --
Content:
2. Workloads and software infrastructure -- 2.1 Datacenter vs. desktop -- 2.2 Performance and availability toolbox -- 2.3 Platform-level software -- 2.4 Cluster-level infrastructure software -- 2.4.1 Resource management -- 2.4.2 Hardware abstraction and other basic services -- 2.4.3 Deployment and maintenance -- 2.4.4 Programming frameworks -- 2.5 Application-level software -- 2.5.1 Workload examples -- 2.5.2 Online: web search -- 2.5.3 Offline: scholar article similarity -- 2.6 A monitoring infrastructure -- 2.6.1 Service-level dashboards -- 2.6.2 Performance debugging tools -- 2.6.3 Platform-level health monitoring -- 2.7 Buy vs. build -- 2.8 Tail-tolerance -- 2.9 Further reading --
Content:
3. Hardware Building Blocks -- 3.1 Cost-efficient server hardware -- 3.1.1 The impact of large SMP communication efficiency -- 3.1.2 Brawny vs. wimpy servers -- 3.1.3 Balanced designs -- 3.2 WSC storage -- 3.2.1 Unstructured WSC storage -- 3.2.2 Structured WSC storage -- 3.2.3 Interplay of storage and networking technology -- 3.3 WSC networking -- 3.4 Further reading --
Content:
4. Datacenter basics -- 4.1 Datacenter tier classifications and specifications -- 4.2 Datacenter power systems -- 4.2.1 Uninterruptible power systems -- 4.2.2 Power distribution units -- 4.2.3 Alternative: DC distribution -- 4.3 Datacenter cooling systems -- 4.3.1 CRACs, chillers, and cooling towers -- 4.3.2 CRACs -- 4.3.3 Chillers -- 4.3.4 Cooling towers -- 4.3.5 Free cooling -- 4.3.6 Air flow considerations -- 4.3.7 In-rack, in-row cooling, and cold plates -- 4.3.8 Case study: Google's in-row cooling -- 4.3.9 Container-based datacenters -- 4.4 Summary --
Content:
5. Energy and power efficiency -- 5.1 Datacenter energy efficiency -- 5.1.1 The PUE metric -- 5.1.2 Issues with the PUE metric -- 5.1.3 Sources of efficiency losses in datacenters -- 5.1.4 Improving the energy efficiency of datacenters -- 5.1.5 Beyond the facility -- 5.2 The energy efficiency of computing -- 5.2.1 Measuring energy efficiency -- 5.2.2 Server energy efficiency -- 5.2.3 Usage profile of warehouse-scale computers -- 5.3 Energy-proportional computing -- 5.3.1 Causes of poor energy proportionality -- 5.3.2 Improving energy proportionality -- 5.3.3 Energy proportionality, the rest of the system -- 5.4 Relative effectiveness of low-power modes -- 5.5 The role of software in energy proportionality -- 5.6 Datacenter power provisioning -- 5.6.1 Deploying the right amount of equipment -- 5.6.2 Oversubscribing facility power -- 5.7 Trends in server energy usage -- 5.7.1 Using energy storage for power management -- 5.8 Conclusions -- 5.8.1 Further reading --
Content:
6. Modeling costs -- 6.1 Capital costs -- 6.2 Operational costs -- 6.3 Case studies -- 6.3.1 Real-world datacenter costs -- 6.3.2 Modeling a partially filled datacenter -- 6.3.3 The cost of public clouds --
Content:
7. Dealing with failures and repairs -- 7.1 Implications of software-based fault tolerance -- 7.2 Categorizing faults -- 7.3 Machine-level failures -- 7.4 Repairs -- 7.5 Tolerating faults, not hiding them --
Content:
8. Closing remarks -- 8.1 Hardware -- 8.2 Software -- 8.3 Economics -- 8.4 Key challenges -- 8.4.1 Rapidly changing workloads -- 8.4.2 Building responsive large scale systems -- 8.4.3 Energy proportionality of non-CPU components -- 8.4.4 Overcoming the end of Dennard scaling -- 8.4.5 Amdahl's cruel law -- 8.5 Conclusions --
Content:
Bibliography -- Author biographies
Note:
Description based upon print version of record
,
Acknowledgments; Note to the Reader; Introduction; 1.1Warehouse-Scale Computers; 1.2Cost Efficiency at Scale; 1.3Not Just a Collection of Servers; 1.4One Datacenter Vs. Several Datacenters; 1.5Why WSCS Might Matter to You; 1.6Architectural Overview of WSCS; 1.6.1Storage; 1.6.2Networking Fabric; 1.6.3Storage Hierarchy; 1.6.4Quantifying Latency, Bandwidth, and Capacity; 1.6.5Power Usage; 1.6.6Handling Failures; Workloads and Software Infrastructure; 2.1Datacenter Vs. Desktop; 2.2Performance and Availability Toolbox; 2.3Platform-Level Software; 2.4 Cluster-Level Infrastructure Software
,
2.4.1Resource Management2.4.2Hardware Abstraction and Other Basic Services; 2.4.3Deployment and Maintenance; 2.4.4Programming Frameworks; 2.5Application-Level Software; 2.5.1Workload Examples; 2.5.2Online: Web Search; 2.5.3Offline: Scholar Article Similarity; 2.6A Monitoring Infrastructure; 2.6.1Service-Level Dashboards; 2.6.2Performance Debugging Tools; 2.6.3Platform-Level Health Monitoring; 2.7Buy Vs. Build; 2.8Tail-Tolerance; 2.9Further Reading; Hardware Building Blocks; 3.1Cost-Efficient Server Hardware; 3.1.1The Impact of Large SMP Communication Efficiency; 3.1.2Brawny vs. Wimpy Servers
,
3.1.3Balanced Designs3.2WSC Storage; 3.2.1Unstructured WSC Storage; 3.2.2Structured WSC Storage; 3.2.3Interplay of Storage and Networking Technology; 3.3WSC Networking; 3.4Further Reading; Datacenter Basics; 4.1Datacenter Tier Classifications and Specifications; 4.2 Datacenter Power Systems; 4.2.1Uninterruptible Power Systems; 4.2.2Power Distribution Units; 4.2.3Alternative: DC Distribution; 4.3Datacenter Cooling Systems; 4.3.1CRACs, Chillers, and Cooling Towers; 4.3.2CRACs; 4.3.3Chillers; 4.3.4Cooling towers; 4.3.5Free Cooling; 4.3.6Air Flow Considerations
,
4.3.7In-Rack, In-Row Cooling, and Cold Plates4.3.8Case Study: Google's In-row Cooling; 4.3.9Container-Based Datacenters; 4.4Summary; Energy and Power Efficiency; 5.1Datacenter Energy Efficiency; 5.1.1The PUE Metric; 5.1.2Issues with the PUE Metric; 5.1.3Sources of Efficiency Losses in Datacenters; 5.1.4Improving the Energy Efficiency of Datacenters; 5.1.5Beyond the Facility; 5.2The Energy Efficiency of Computing; 5.2.1Measuring Energy Efficiency; 5.2.2Server Energy Efficiency; 5.2.3Usage Profile of Warehouse-Scale Computers; 5.3Energy-Proportional Computing
,
5.3.1Causes of Poor Energy Proportionality5.3.2Improving Energy Proportionality; 5.3.3Energy Proportionality-The Rest of the System; 5.4Relative Effectiveness of Low-Power Modes; 5.5The Role of Software in Energy Proportionality; 5.6Datacenter Power Provisioning; 5.6.1Deploying the Right Amount of Equipment; 5.6.2Oversubscribing Facility Power; 5.7Trends in Server Energy Usage; 5.7.1Using Energy Storage for Power Management; 5.8Conclusions; 5.8.1Further Reading; Modeling Costs; 6.1Capital Costs; 6.2Operational Costs; 6.3Case Studies; 6.3.1Real-World Datacenter Costs
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6.3.2Modeling a Partially Filled Datacenter
,
Electronic reproduction; Available via World Wide Web
,
Mode of access: World Wide Web.
,
System requirements: Adobe Acrobat Reader.
Additional Edition:
ISBN 9781627050098
Additional Edition:
Print version The Datacenter as a Computer An Introduction to the Design of Warehouse-Scale Machines, Second edition
Language:
English
Keywords:
Electronic books
DOI:
10.2200/S00516ED2V01Y201306CAC024
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