Towards a Serverless Bioinformatics Cyberinfrastructure Pipeline
Towards a Serverless Bioinformatics Cyberinfrastructure Pipeline
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DOI：
10.1145/3452413.3464787
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发表时间：
2020-06
期刊：
影响因子：
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通讯作者：
S. Yao;Muhammad Ali Gulzar;Liqing Zhang;A. Butt
中科院分区：
文献类型：
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作者：
S. Yao;Muhammad Ali Gulzar;Liqing Zhang;A. Butt
功能即服务（FaaS）和无服务器计算模型为支持云中的大规模应用程序提供了强大的抽象。在这种情况下，一个主要的障碍是将应用程序（即使是已经容器化的应用程序）转换为FaaS实现并不简单。在本文中，我们迈出了第一步，支持更轻松，更高效的应用程序转换到FaaS。我们提出了一个系统的方案，将用Python编写的应用程序转换为一组功能，然后可以自动部署在AWS Lamda等平台上。我们的目标是生物信息学网络基础设施管道CIWARS，该管道提供废水分析，以识别耐药细菌和病毒，如SARS-CoV-2。根据我们在实现基于FaaS的CIWARS方面的经验，我们开发了一种方法，可以帮助其他类似应用程序转换为FaaS模型。我们的评估表明，我们的方法可以正确地将CIWARS转换为FaaS，并且新的基于FaaS的CIWARS对于代表性工作负载仅产生可忽略不计的（≤2%）不到2%的开销。
Function-as-a-Service (FaaS) and the serverless computing model offer a powerful abstraction for supporting large-scale applications in the cloud. A major hurdle in this context is that it is non-trivial to transform an application, even an already containerized one, to a FaaS implementation. In this paper, we take the first step towards supporting easier and efficient application transformation to FaaS. We present a systematic scheme to transform applications written in Python into a set of functions that can then be automatically deployed atop platforms such as AWS Lamda. We target a Bioinformatics cyberinfrastructure pipeline, CIWARS, that provides waste-water analysis for the identification of antibiotic-resistant bacteria and viruses such as SARS-CoV-2. Based on our experience with enabling FaaS-based CIWARS, we develop a methodology that would help the conversion of other similar applications to the FaaS model. Our evaluation shows that our approach can correctly transform CIWARS to FaaS, and the new FaaS-based CIWARS incurs only negligible(≤2%) less than 2% overhead for representative workloads.