The Community for Technology Leaders
RSS Icon
Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
ISBN: 978-1-4673-2892-0
pp: 319-326
Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually topology-aware applications. Therefore, considering the topology of a scientific application during the development will benefit the performance of the application. However, it is challenging to automatically discover and make use of the communication pattern of a scientific application while deploying the application on cloud. To attack this challenge, in this paper, we propose a framework to discover the communication topology of a scientific application by pre-execution and multi-scale graph clustering, based on which the deployment can be optimized. Comprehensive experiments are conducted by employing a well-known MPI benchmark and comparing the performance of our method with those of other methods. The experimental results show the effectiveness of our topology-aware deployment method.
Topology, Clustering algorithms, Benchmark testing, Cloud computing, Partitioning algorithms, Clustering methods, Throughput, cloud computing, Topology-aware, communication topology, scientific applications, deployment
Pei Fan, Zhenbang Chen, Ji Wang, Zibin Zheng, Michael R. Lyu, "Topology-Aware Deployment of Scientific Applications in Cloud Computing", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 319-326, doi:10.1109/CLOUD.2012.70
17 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool