论文标题
基于Web的志愿者分发计算用于处理时间关键的紧急工作负载
Web-based volunteer distributed computing for handling time-critical urgent workloads
论文作者
论文摘要
紧急计算工作负载是时间关键,不可预测和高度动态的时间。尽管正在努力在传统的HPC机器上运行这些努力,但另一种选择是利用志愿者捐赠的计算能力。志愿计算,公众将其一些CPU时间捐赠给大型项目已经很受欢迎了多年,因为这是为特定问题提供计算的有力方法,公众经常渴望为有社会利益的良好事业做出贡献。但是,传统的志愿者计算需要用户安装专业软件,这是进入障碍的,并且项目本身的开发,即使是现有框架的顶部也是不平凡的。 因此,近年来,向这些志愿者计算项目捐赠CPU时间的用户数量有所减少,这是在经常受气候变化驱动的灾难频率快速上升的时候。我们认为,另一种方法,网站访问者在浏览时捐赠了一些CPU时间,它有可能解决这些问题。但是,基于Web的分布式计算是一个不成熟的领域,必须回答许多问题,以充分了解利用网站访问者代表的大规模并行性的可行性。在本文中,我们首次使用现实世界硬件和现实世界浏览习惯对两个基准测试进行了基于网络的分布式计算框架,Panther和对两个基准测试的深入性能实验。通过探索我们方法的性能特征,我们证明了这对于紧急工作负载是可行的,但是有很多警告,尤其是网站上最合适的访问者模式,必须考虑在内。
Urgent computing workloads are time critical, unpredictable, and highly dynamic. Whilst efforts are on-going to run these on traditional HPC machines, another option is to leverage the computing power donated by volunteers. Volunteer computing, where members of the public donate some of their CPU time to large scale projects has been popular for many years because it is a powerful way of delivering compute for specific problems, with the public often eager to contribute to a good cause with societal benefits. However, traditional volunteer computing has required user installation of specialist software which is a barrier to entry, and the development of the software itself by the projects, even on-top of existing frameworks, is non-trivial. As such, the number of users donating CPU time to these volunteer computing projects has decreased in recent years, and this comes at a time when the frequency of disasters, often driven by climate change, are rising fast. We believe that an alternative approach, where visitors to websites donate some of their CPU time whilst they are browsing, has the potential to address these issues. However, web-based distributed computing is an immature field and there are numerous questions that must be answered to fully understand the viability of leveraging the large scale parallelism that website visitors represent. In this paper we describe our web-based distributed computing framework, Panther, and perform in-depth performance experiments for two benchmarks using real world hardware and real world browsing habits for the first time. By exploring the performance characteristics of our approach we demonstrate that this is viable for urgent workloads, but there are numerous caveats, not least the most appropriate visitor patterns to a website, that must be considered.