Toward a domain-specific language for scientific workflow-based applications on multicloud system

摘要

The cloud computing paradigm has emerged as the backbone of modern price-aware scalable computing systems. Many cloud service models are competing to become the leading doorway to access the computational power of cloud providers. Recently, a novel service model, called function-as-a-service (FaaS), has been proposed, which enables users to exploit the cloud computational scalability, left out the configuration and management of huge computing infrastructures. This article discloses Fly, a domain-specific language, which aims at reconciling cloud and high-performance computing paradigms adopting a multicloud strategy by providing a powerful, effective, and pricing-efficient tool for developing scalable workflow-based scientific applications by exploiting different and at the same time FaaS cloud providers as computational backends in a transparent fashion. We present several improvements of the Fly language, as well as a new enhanced version of a source-to-source compiler, which currently supports Symmetric Multiprocessing, Amazon AWS, and Microsoft Azure backends and translation of functions in Java, JavaScript, and Python programming languages. Furthermore, we discuss a performance evaluation of Fly on a popular benchmark for distributed computing frameworks, along with a collection of case studies with an analysis of their performance results and costs.