Recursive Task Generation for Scalable SDF Graph Execution on Multicore Processors

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Sammanfattning

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.

OriginalspråkOdefinierat/okänt
Titel på gästpublikationProceedings 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing PDP 2020
FörlagIEEE Computer Society Conference Publishing Services (CPS)
Sidor
ISBN (elektroniskt)978-1-7281-6582-0
ISBN (tryckt)978-1-7281-6583-7
DOI
StatusPublicerad - 2020
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangEuromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP) - 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
Varaktighet: 11 mar 202013 mar 2020

Konferens

KonferensEuromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
Period11/03/2013/03/20

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