Toward a domain‐specific language for scientific workflow‐based applications on multicloud system. (30th April 2020)

• Record Type: Journal Article
• Authors: Cordasco, Gennaro; D'Auria, Matteo; Negro, Alberto; Scarano, Vittorio; Spagnuolo, Carmine
• Other Names: Oh Sangyoon guestEditor.; de Camargo Raphael Y. guestEditor.; Marozzo Fabrizio guestEditor.; Martins Wellington guestEditor.; Kołodziej Joanna guestEditor.; Jaatun Martin Gilje guestEditor.
• Is Part Of: Concurrency and computation. Volume 33:Number 18(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-30
• Subjects: distributed computing -- domain‐specific languages -- functions as a service -- parallel computing -- scientific computing -- serverless computing -- workflow‐based application; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5802
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: 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.