Eriksson Henrik, Raciti Massimiliano, Basile Maurizio, Cunsolo Alessandro, Fröberg Anders, Leifler Ola, Ekberg Joakim, Timpka Toomas
Dept. of Comp. and Inform. Sci., Linköping University, Sweden.
AMIA Annu Symp Proc. 2011;2011:364-73. Epub 2011 Oct 22.
High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface.
大流行疫情的高保真模拟消耗资源。已有人建议采用基于集群的解决方案来执行此类复杂计算。我们提出了一种基于云的模拟架构，该架构利用本地可用的计算资源以及在线动态租用的计算资源。该方法使用Condor框架来进行作业分发以及管理亚马逊弹性计算云（EC2）和本地资源。该架构具有基于网络的用户界面，允许用户监控和控制模拟执行。在一次基准测试中，EC2 H-CPU 中型实例记录了最佳的成本调整性能，而一次现场试验表明作业配置对执行时间有重大影响，并且主节点的网络容量可能成为瓶颈。我们得出结论，开发一个使用基于云的解决方案并提供易于使用的图形用户界面的可扩展模拟环境是可行的。
