Exploiting idle cycles to execute data mining applications on clusters of PCs

Author:

Senger Hermes,Hruschka Eduardo R.,Silva Fabrício A.B.,Sato Liria M.,Bianchini Calebe P.,Jerosch Bruno F.

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance evaluation of a SaaS cloud under different levels of workload computational demand variability and tardiness bounds;Simulation Modelling Practice and Theory;2019-02

2. The Effect of Workload Computational Demand Variability on the Performance of a SaaS Cloud with a Multi-tier SLA;2017 IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud);2017-08

3. Scheduling real‐time bag‐of‐tasks applications with approximate computations in SaaS clouds;Concurrency and Computation: Practice and Experience;2017-06-20

4. Simulation-Based Performance Evaluation of an Energy-Aware Heuristic for the Scheduling of HPC Applications in Large-Scale Distributed Systems;Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion;2017-04-18

5. Performance improvement of data mining in Weka through multi-core and GPU acceleration: opportunities and pitfalls;Journal of Ambient Intelligence and Humanized Computing;2015-06-24

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