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

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Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications
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.
Frank J. Seinstra, Dennis Koelma
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where IPPS
Authors Frank J. Seinstra, Dennis Koelma
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