Embedded Runtime for Reconfigurable Dataflow Graphs on Manycore Architectures

Hugo Miomandre 1 Julien Hascoët 1 Karol Desnos 1 Kevin Martin 2 Benoît Dupont de Dinechin 3 Jean-François Nezan 1
2 Lab-STICC_UBS_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : Embedded manycore architectures offer energy-efficient super-computing capabilities but are notoriously difficult to program with traditional parallel Application Programming Interfaces (APIs). To address this challenge, dataflow Models of Computation (MoCs) are increasingly used as their high-level of abstraction eases the automation of computation mapping, memory allocation, and communication management. Reconfigurable dataflow is a class of dataflow MoC that fosters a unique trade-off between application dynamicity and predictability. This paper introduces the first embedded runtime manager enabling the execution of reconfigurable dataflow graphs on a Non-Uniform Memory Access (NUMA) architecture. The proposed runtime manager dynamically deploys reconfigurable dataflow graphs on clustered Processing Elements (PEs) through the Networks-on-Chips (NoCs) of the manycore architecture. An open-source implementation on the Kalray MPPA R processor demonstrates the feasibility and the great potential of such a runtime. The first results with an image processing application show a power efficiency 2.5 times better than on a multicore x86 architecture.
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Communication dans un congrès
PARMA-DITAM, Jan 2018, Manchester, United Kingdom
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Hugo Miomandre, Julien Hascoët, Karol Desnos, Kevin Martin, Benoît Dupont de Dinechin, et al.. Embedded Runtime for Reconfigurable Dataflow Graphs on Manycore Architectures. PARMA-DITAM, Jan 2018, Manchester, United Kingdom. 〈hal-01704702〉

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