Leveraging Serverless Computing to Improve Performance for Sequence Comparison
Leveraging Serverless Computing to Improve Performance for Sequence Comparison
复制标题
DOI：
10.1145/3307339.3343465
复制
发表时间：
2019-09
期刊：
影响因子：
--
通讯作者：
Xingzhi Niu;Dimitar Kumanov;Ling-Hong Hung;W. Lloyd;K. Y. Yeung
中科院分区：
文献类型：
--
作者：
Xingzhi Niu;Dimitar Kumanov;Ling-Hong Hung;W. Lloyd;K. Y. Yeung
云计算提供按需、可扩展的计算和存储，已成为分析大生物医学数据的重要资源。云计算的通常方法要求用户保留和配置虚拟服务器。一种新兴的替代方法是让提供者动态地分配机器资源。这种类型的无服务器计算在易用性、即时可扩展性和成本效益方面对生物医学研究具有巨大的潜力。在我们的概念验证示例中，我们演示了无服务器计算如何按需提供对数百个CPU的低成本访问，只需很少或无需设置。特别是，我们说明了所有独特的人类蛋白质之间的所有对所有成对比较可以在大约2分钟内完成，成本不到1美元，使用Amazon Web Services Lambda。我们还使用Google Functions证明了我们方法的可行性，并表明可以在大约11.5分钟内完成相同的成对蛋白质序列比较任务。相比之下，在一台典型的笔记本电脑上运行相同的任务需要8.7小时。
Cloud computing offers on-demand, scalable computing and storage, and has become an essential resource for the analyses of big biomedical data. The usual approach to cloud computing requires users to reserve and provision virtual servers. An emerging alternative is to have the provider allocate machine resources dynamically. This type of serverless computing has tremendous potential for biomedical research in terms of ease-of-use, instantaneous scalability, and cost effectiveness. In our proof of concept example, we demonstrate how serverless computing provides low cost access to hundreds of CPUs, on demand, with little or no setup. In particular, we illustrate that the all-against-all pairwise comparison among all unique human proteins can be accomplished in approximately 2 minutes, at a cost of less than $1, using Amazon Web Services Lambda. We also demonstrate the feasibility of our approach using Google Functions and show that the same task of pairwise protein sequence comparison can be accomplished in approximately 11.5 minutes. In contrast, running the same task on a typical laptop computer required 8.7 hours.