Embedded Runtime for Reconfigurable Dataflow Graphs on Manycore Architectures

Hugo Miomandre, Julien Hascoët, Karol Desnos, Kevin J. M. Martin, Benoît Dupont de Dinechin Kalray, Jean-François Nezan
2018 Proceedings of the 9th Workshop and 7th Workshop on Parallel Programming and RunTime Management Techniques for Manycore Architectures and Design Tools and Architectures for Multicore Embedded Computing Platforms - PARMA-DITAM '18  
Embedded manycore architectures offer energyefficient 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 tradeoff between
more » ... pplication 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 Networkson-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.
doi:10.1145/3183767.3183780 dblp:conf/hipeac/MiomandreHDMDN18 fatcat:sj5437ax2jgcrdkhv6ss4o4dom