• DocumentCode
    3201053
  • Title

    Nexus#: A Distributed Hardware Task Manager for Task-Based Programming Models

  • Author

    Dallou, Tamer ; Elhossini, Ahmed ; Juurlink, Ben ; Engelhardt, Nina

  • Author_Institution
    Embedded Syst. Archit., Tech. Univ. Berlin, Berlin, Germany
  • fYear
    2015
  • fDate
    25-29 May 2015
  • Firstpage
    1129
  • Lastpage
    1138
  • Abstract
    In the era of multicore systems, it is expected that the number of cores that can be integrated on a single chip will be 3-digit. The key to utilize such a huge computational power is to extract the very fine parallelism in the user program. This is non-trivial for the average programmer, and becomes very hard as the number of potential parallel instances increases. Task-based programming models such as OmpSs are promising, since they handle the detection of dependencies and synchronization for the programmer. However, state-of-the-art research shows that task management is not cheap, and introduces a significant overhead that limits the scalability of OmpSs. Nexus# is a hardware accelerator for the OmpSs runtime system, which dynamically monitors dependencies between tasks. It is fully synthesizable in VHDL, and has a distributed task graph model to achieve the best scalability. Supporting tasks with arbitrary number of parameters and any dependency pattern, Nexus# achieves better performance than Nanos, the official OmpSs runtime system, and scales well for the H264dec benchmark with very fine grained tasks, among other benchmarks from the Starbench suite.
  • Keywords
    hardware description languages; multiprocessing systems; parallel programming; resource allocation; Nexus distributed hardware task manager; OmpS programming model; Starbench suite; VHDL; multicore systems; parallel instance; programmer dependency; programmer synchronization; task-based programming model; task-based programming models; user program parallelism; very high scale description language; Benchmark testing; Hardware; Multicore processing; Pipelines; Programming; Runtime; Scalability; data flow; hardware support; hardware task scheduler; parallel programming; task graph; task manager;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium (IPDPS), 2015 IEEE International
  • Conference_Location
    Hyderabad
  • ISSN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2015.79
  • Filename
    7161597