A DSL-based runtime adaptivity framework for Java

• Tipo: Artigo em Revista Científica Internacional
• Data: 2023

Autores

Carvalho, T (Autor) Outra; João Bispo (Autor) FEUP; Pinto, P (Autor) Outra; João M. P. Cardoso (Autor) FEUP

Revista

Título: SoftwareX

Vol. 23

Editora: Elsevier

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00Z-14W

DOI: 10.1016/j.softx.2023.101496

Abstract (EN): This article presents Kadabra, a Java source-to-source compiler that allows users to make code queries, code analysis and code transformations, all user-programmable using the domain-specific language LARA. We show how Kadabra can be used as the basis for developing a runtime autotuning and adaptivity framework, able to adapt existing source Java code in order to take advantage of runtime autotuning. Specifically, this article presents the framework, consisting of Kadabra and an API for runtime adaptivity. We show the use of the framework to extend Java applications with autotuning and runtime adaptivity mechanisms to target performance improvement and/or energy saving goals.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7