Automatic Instrumentation of Dataflow Applications using PAPI

Madroñal Quintín, Daniel; Morvan, Antoine; Lazcano López, Raquel; Salvador Perea, Rubén; Desnos, Karol; Juárez Martínez, Eduardo y Sanz, César (2018). Automatic Instrumentation of Dataflow Applications using PAPI. En: "CF ’18: Computing Frontiers Conference", 8-11 Mayo de 2018, Ischya, Italia. https://doi.org/10.1145/3203217.3209886.

Descripción

Título: Automatic Instrumentation of Dataflow Applications using PAPI
Autor/es:
  • Madroñal Quintín, Daniel
  • Morvan, Antoine
  • Lazcano López, Raquel
  • Salvador Perea, Rubén
  • Desnos, Karol
  • Juárez Martínez, Eduardo
  • Sanz, César
Tipo de Documento: Ponencia en Congreso o Jornada (Póster)
Título del Evento: CF ’18: Computing Frontiers Conference
Fechas del Evento: 8-11 Mayo de 2018
Lugar del Evento: Ischya, Italia
Título del Libro: CF ’18: Computing Frontiers Conference
Fecha: 8 Mayo 2018
Materias:
Escuela: Centro de Investigación en Tecnologías Software y Sistemas Multimedia para la Sostenibilidad (CITSEM) (UPM)
Departamento: Otro
Licencias Creative Commons: Ninguna

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Resumen

The widening of the complexity-productivity gap witnessed in the last years is becoming unaffordable from the application development point of view. New design methods try to automate most designers tasks in order to bridge this gap. In addition, new Models of Computation (MoC), as those dataflow-based, ease the expression of parallelism within applications and lead to higher productivity. Rapid prototyping design tools offer fast estimations of the soundness of design choices. A key step when prototyping an application is to have representative performance indicators to estimate the validity of the design choices. Such indicators can be obtained using hardware information through the Performance API (PAPI). In this work, PAPI and a dataflow MoC are integrated within a Y-chart design flow. The implementation takes the form of a dedicated automatic code generation scheme within the PREESM tool. Preliminary results show that depending on the complexity of the application, the computation time overhead due to monitoring varies from being almost negligible to more than 50%. Also, on top of offering accurate hardware performance indicators, the extracted values can be combined to estimate power or energy consumption.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
Horizonte 2020EH160010411CERBEROSin especificarCross-layer modEl-based fRamework for multi-oBjective dEsign of Reconfigurable systems in unceRtain hybRid envirOnments

Más información

ID de Registro: 51789
Identificador DC: http://oa.upm.es/51789/
Identificador OAI: oai:oa.upm.es:51789
Identificador DOI: 10.1145/3203217.3209886
Depositado por: D Daniel Madroñal Quintín
Depositado el: 30 Jul 2018 19:45
Ultima Modificación: 30 Jul 2018 19:47
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