Large parameter space explorations are among the most time consuming yet critically important tasks in many fields of modern research. ExpoCloud enables the researcher to harness cloud compute resources to achieve time and budget-effective large-scale concurrent parameter space explorations. ExpoCloud enables maximal possible levels of concurrency by creating compute instances on-the-fly, saves money by terminating unneeded instances, provides a mechanism for saving both time and money by avoiding the exploration of parameter settings that are as hard or harder than the parameter settings whose exploration timed out. Effective fault tolerance mechanisms make ExpoCloud suitable for large experiments. ExpoCloud provides an interface that allows its use under various cloud environments. As a proof of concept, we implemented a class supporting the Google Compute Engine (GCE). We also implemented a class that simulates a cloud environment on the local machine, thereby facilitating further development of ExpoCloud. The article describes ExpoCloud's features and provides a usage example. The software is well documented and is available under the MIT license.
翻译:大型参数空间探索是现代研究许多领域最耗时但又至关重要的任务之一。 展览使研究人员能够利用云计算资源,实现时间和具有预算效益的大规模并行参数空间探索。 展览通过在飞行中计算各种情况,节省了资金,通过终止不必要的事件节省了资金,提供了节省时间和金钱的机制,避免了对比参数设置更难或更难的参数设置的探索,而参数设置的勘探时间已经过长。有效的断层容忍机制使得大爆发适合大型实验。 展览提供了一个界面,允许在各种云环境中使用。作为概念的证明,我们实施了支持谷歌计算引擎(GCE)的类。我们还实施了模拟当地机器云层环境的类,从而便利了博览的进一步发展。 文章描述了“ 博览” 的特征,并提供了一个使用范例。 软件有详细记录,并可在麻省理工省理工学院的许可证下查阅。