Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications

  • Authors:

  • F. J. Seinstra;D. Koelma

  • Affiliations:

  • -;-

  • Venue:
  • IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
  • Year:
  • 2003

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Abstract

Performance obtained with existing library-based parallelization tools for implementing high performance image processing applications is often sub-optimal. This is because inter-operation optimization (or: optimization across library calls) is often not incorporated in the library implementations. This paper presents a simple, efficient, finite state machine-based method for global performance optimization, called 'lazy parallelization'. Experimental results based on this approach show significant performance improvements over non-optimized parallel implementations.