Recursive Task Generation for Scalable SDF Graph Execution on Multicore Processors

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Abstrakti

Dataflow modelling is a popular technique for describing parallel algorithms. Using dataflow, algorithm parallelism can be modelled and analysed efficiently at a high level of abstraction. However, challenges arise when translating dataflow semantics into executable code, mainly due to scheduling and synchronization overheads. Invoking task programming models in order to generate efficient code from dataflow representations has been proposed as a promising methodology to optimise the translation process.In this paper, we propose recursive task execution as an optimisation for the dataflow-based code generation process. Our approach is based on extracting synchronous dataflow graph information in order to reduce scheduling overheads and improve load balancing when executing task-based code on multicore processors. We use PREESM dataflow-based prototyping framework to implement and test our concept. Results show that our proposed optimisation enhances code scalability therefore enabling higher application throughput.

AlkuperäiskieliEi tiedossa
OtsikkoProceedings 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing PDP 2020
KustantajaIEEE Computer Society Conference Publishing Services (CPS)
Sivut
ISBN (elektroninen)978-1-7281-6582-0
ISBN (painettu)978-1-7281-6583-7
DOI - pysyväislinkit
TilaJulkaistu - 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaEuromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP) - 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
Kesto: 11 maaliskuuta 202013 maaliskuuta 2020

Konferenssi

KonferenssiEuromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
Ajanjakso11/03/2013/03/20

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