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The efficient execution of image processing algorithms is an active area ofBioinformatics. In image processing, one of the classes of algorithms orcomputing pattern that works with irregular data structures is the IrregularWavefront Propagation Pattern (IWPP). In this class, elements propagateinformation to neighbors in the form of wave propagation. This propagationresults in irregular access to data and expansions. Due to this irregularity,current implementations of this class of algorithms requires atomic operations,which is very costly and also restrains implementations with SingleInstruction, Multiple Data (SIMD) instructions in Many Integrated Core (MIC)architectures, which are critical to attain high performance on this processor.The objective of this study is to redesign the Irregular Wavefront PropagationPattern algorithm in order to enable the efficient execution on processors withMany Integrated Core architecture using SIMD instructions. In this work, usingthe Intel (R) Xeon Phi (TM) coprocessor, we have implemented a vector versionof IWPP with up to 5.63x gains on non-vectored version, a parallel versionusing First In, First Out (FIFO) queue that attained speedup up to 55x ascompared to the single core version on the coprocessor, a version usingpriority queue whose performance was 1.62x better than the fastest version ofGPU based implementation available in the literature, and a cooperative versionbetween heterogeneous processors that allow to process images bigger than theIntel (R) Xeon Phi (TM) memory and also provides a way to utilize all theavailable devices in the computation.

Efficient Execution of Irregular Wavefront Propagation Pattern on Many Integrated Core Architecture