  The efficient execution of image processing algorithms is an active area of
Bioinformatics. In image processing, one of the classes of algorithms or
computing pattern that works with irregular data structures is the Irregular
Wavefront Propagation Pattern (IWPP). In this class, elements propagate
information to neighbors in the form of wave propagation. This propagation
results 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 Single
Instruction, 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 Propagation
Pattern algorithm in order to enable the efficient execution on processors with
Many Integrated Core architecture using SIMD instructions. In this work, using
the Intel (R) Xeon Phi (TM) coprocessor, we have implemented a vector version
of IWPP with up to 5.63x gains on non-vectored version, a parallel version
using First In, First Out (FIFO) queue that attained speedup up to 55x as
compared to the single core version on the coprocessor, a version using
priority queue whose performance was 1.62x better than the fastest version of
GPU based implementation available in the literature, and a cooperative version
between heterogeneous processors that allow to process images bigger than the
Intel (R) Xeon Phi (TM) memory and also provides a way to utilize all the
available devices in the computation.
