The Authoritative Dictionary of IEEE Standards Terms
The Authoritative Dictionary of IEEE Standards Terms
Metrics for Parallel Job Scheduling and Their Convergence
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments
ISCA '08 Proceedings of the 35th Annual International Symposium on Computer Architecture
Internet-scale service infrastructure efficiency
Proceedings of the 36th annual international symposium on Computer architecture
FAWN: a fast array of wimpy nodes
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Web search using mobile cores: quantifying and mitigating the price of efficiency
Proceedings of the 37th annual international symposium on Computer architecture
Wimpy node clusters: what about non-wimpy workloads?
Proceedings of the Sixth International Workshop on Data Management on New Hardware
Pitfalls in parallel job scheduling evaluation
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
The low-power architecture approach towards exascale computing
Proceedings of the second workshop on Scalable algorithms for large-scale systems
Totally green: evaluating and designing servers for lifecycle environmental impact
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
A model for green design of online news media services
Proceedings of the 22nd international conference on World Wide Web
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Large-scale data centers consume megawatts in power and cost hundreds of millions of dollars to equip. Reducing the energy and cost footprint of servers can therefore have substantial impact. Web, Grid, and cloud servers in particular can be hard to optimize, since they are expected to operate under a wide range of workloads. For our upcoming data center, we set out to significantly improve its power efficiency, cost, reliability, serviceability, and environmental footprint. To this end, we redesigned many dimensions of the data center and servers in conjunction. This paper focuses on our new server design, combining aspects of power, motherboard, thermal, and mechanical design. We calculate and confirm experimentally that our custom-designed servers can reduce power consumption across the entire load spectrum while at the same time lower acquisition and maintenance costs. Importantly, our design does not reduce the servers' performance or portability, which would otherwise limit its applicability.