Parallelization of a Bokeh application on embedded multicore DSP systems

Bokeh application presents the blur or the aesthetic quality of blurring in out-of-focus areas of an image. The out-of-focus effect of Bokeh results depends on accuracy of depth information and blurring effects produced by image postprocessing. To obtain accurate depth information, current stereo vision techniques however consume a huge amount of processing time. In this paper, we present a case study on parallelizing a Bokeh application on an embedded multicore platform, which features one MPU and one DSP sub-system consisting of two VLIW DSP processors. The Bokeh application employs a Belief Propagation method to obtain depth information of input images and uses the information to generate output images with out-of-focus effect. This study also illustrates how to deliver performance for applications on embedded multicore systems. To sustain heavy computation requirement of the stereo vision techniques, DSPs with their SIMD instructions are leveraged to exploit data parallelism in critical kernels. In addition, DMAs on the multicore system are also incorporated to facilitate data transmission between processors. The access to SIMD and DMAs is provided by two essential programming models we developed for embedded multicore systems. Our work also gives the firsthand experiences of how C++ classes and abstractions can be used to help parallelization of applications on embedded multicore DSP systems. Finally, in our experiments, we utilize DSPs, SIMD and DMAs to obtain performance for two key components of the Bokeh application with their speedups of 1.67 and 2.75, respectively.