The ANTAREX tool flow for monitoring and autotuning energy efficient HPC systems

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2017-04-20

Autores

Jorge Manuel Gomes Barbosa (Autor) FEUP; João M. P. Cardoso (Autor) FEUP; João Bispo (Autor) FEUP; Ricardo Nobre (Autor) FEUP

Ata de Conferência Internacional

Título: International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation

Páginas: 308-316

Indexação

Scopus - 16 Citações

Classificação Científica

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia de computadores

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-00N-X4Y

DOI: 10.1109/samos.2017.8344645

Abstract (EN): Designing and optimizing HPC applications are difficult and complex tasks, which require mastering specialized languages and tools for performance tuning. As this is incompatible with the current trend to open HPC infrastructures to a wider range of users, the availability of more sophisticated programming languages and tools to assist and automate the design stages is crucial to provide smoothly migration paths towards novel heterogeneous HPC platforms. The ANTAREX project intends to address these issues by providing a tool flow, a Domain Specific Launguage and APIs to provide application's adaptivity and to runtime manage and autotune applications for heterogeneous HPC systems. Our DSL provides a separation of concerns, where analysis, runtime adaptivity, performance tuning and energy strategies are specified separately from the application functionalities with the goal to increase productivity, significantly reduce time to solution, while making possible the deployment of substantially improved implementations. This paper presents the ANTAREX tool flow and shows the impact of optimization strategies in the context of one of the ANTAREX use cases related to personalized drug design. We show how simple strategies, not devised by typical compilers, can substantially speedup the execution and reduce energy consumption. © 2017 IEEE.

Idioma: Inglês

Tipo (Avaliação Docente): Científica