• DocumentCode
    2946307
  • Title

    Deadlock detection for distributed process networks

  • Author

    Olson, Alex G. ; Evans, Brian L.

  • Author_Institution
    Embedded Signal Process. Lab., Texas Univ., Austin, TX, USA
  • Volume
    5
  • fYear
    2005
  • fDate
    18-23 March 2005
  • Abstract
    The process network (PN) model, which consists of concurrent processes communicating over first-in first out unidirectional queues, is useful for modeling and exploiting functional parallelism in streaming data applications. The PN model maps easily onto multi-processor and/or multi-threaded targets. Since the PN model is Turing complete, memory requirements cannot be predicted statically. In general, any bounded-memory scheduling algorithm for this model requires run-time deadlock detection. The few PN implementations that perform deadlock detection detect only global deadlocks. Not all local deadlocks, however, will cause a PN system to reach global deadlock. In this paper, we present the first local deadlock detection algorithm for PN models. The proposed algorithm is based on the Mitchell and Merritt algorithm and is suitable for both parallel and distributed PN implementations.
  • Keywords
    concurrency control; multi-threading; multiprocessing systems; parallel processing; processor scheduling; Mitchell-Merritt algorithm; Turing complete model; bounded-memory scheduling algorithm; concurrent processes; distributed process networks; first-in first out unidirectional queues; local deadlock detection algorithm; memory requirement predictions; multiprocessor systems; multithreaded systems; parallel processing; process network model; run-time deadlock detection; streaming data functional parallelism; Concurrent computing; Detection algorithms; Laboratories; Parallel processing; Signal processing; Signal processing algorithms; Sonar; System recovery; Workstations; Yarn;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-8874-7
  • Type

    conf

  • DOI
    10.1109/ICASSP.2005.1416243
  • Filename
    1416243