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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…mehr
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. Table of Contents: Introduction / Workloads and Software Infrastructure / Hardware Building Blocks / Datacenter Basics / Energy and Power Efficiency / Modeling Costs / Dealing with Failures and Repairs / Closing Remarks
Luiz Andre Barroso has worked across several engineering areas including web search, software infrastructure, storage availability, energy efficiency, and hardware design. He was the first manager of Google's Platforms Engineering team, the group responsible for designing the company's computing platform, and currently leads engineering infrastructure for Google Maps. Prior to Google, he was a member of the research staff at Digital Equipment Corporation (later acquired by Compaq), where his group did some of the pioneering work on processor and memory system design for multi-core CPUs. He holds a Ph.D. in computer engineering from the University of Southern California and B.S/M.S. degrees in electrical engineering from the PUC, Rio de Janeiro. Luiz is a Google Fellow, a Fellow of the ACM, and a Fellow of the American Association for the Advancement of Science. Urs Holzle served as Google's first vice president of engineering and has been leading the development of Google's technical infrastructure since 1999. His current responsibilities include the design and operation of the servers, networks, datacenters, and software infrastructure that power Google's internal and external cloud platforms. He is also renowned for both his red socks and his free-range Leonberger, Yoshka (Google's original top dog). Urs grew up in Switzerland and received a master's degree in computer science from ETH Zurich and, as a Fulbright scholar, a Ph.D. from Stanford. While at Stanford (and then a start-up later acquired by Sun Microsystems), he invented fundamental techniques used in most of today's leading Java compilers. Before joining Google, he was a professor of computer science at the University of California, Santa Barbara. He is a Fellow of the ACM and AAAS, a member of the Swiss Academy of Technical Sciences and the National Academy of Engineering, and serves on the board of the US World Wildlife Fund.
Inhaltsangabe
Introduction.- Workloads and Software Infrastructure.- Hardware Building Blocks.- Datacenter Basics.- Energy and Power Efficiency.- Modeling Costs.- Dealing with Failures and Repairs.- Closing Remarks.
Introduction.- Workloads and Software Infrastructure.- Hardware Building Blocks.- Datacenter Basics.- Energy and Power Efficiency.- Modeling Costs.- Dealing with Failures and Repairs.- Closing Remarks.
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