Distributed computing in practice: the Condor experience: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
JouleSort: a balanced energy-efficiency benchmark
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Dryad: distributed data-parallel programs from sequential building blocks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments
ISCA '08 Proceedings of the 35th Annual International Symposium on Computer Architecture
Proceedings of the VLDB Endowment
Gordon: using flash memory to build fast, power-efficient clusters for data-intensive applications
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
DRAM errors in the wild: a large-scale field study
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
FAWN: a fast array of wimpy nodes
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
Energy-efficient cluster computing with FAWN: workloads and implications
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Web search using mobile cores: quantifying and mitigating the price of efficiency
Proceedings of the 37th annual international symposium on Computer architecture
Optimizing the datacenter for data-centric workloads
Proceedings of the international conference on Supercomputing
Does low-power design imply energy efficiency for data centers?
Proceedings of the 17th IEEE/ACM international symposium on Low-power electronics and design
Modeling energy consumption for master---slave applications
The Journal of Supercomputing
Market mechanisms for managing datacenters with heterogeneous microarchitectures
ACM Transactions on Computer Systems (TOCS)
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This paper conducts a survey of several small clusters of machines in search of the most energy-efficient data center building block targeting data-intensive computing. We first evaluate the performance and power of single machines from the embedded, mobile, desktop, and server spaces. From this group, we narrow our choices to three system types. We build five-node homogeneous clusters of each type and run Dryad, a distributed execution engine, with a collection of data-intensive workloads to measure the energy consumption per task on each cluster. For this collection of data-intensive workloads, our high-end mobile-class system was, on average, 80% more energy-efficient than a cluster with embedded processors and at least 300% more energy-efficient than a cluster with low-power server processors.