Handling large-size discrete wavelet transform on network-based computing systems — parallelization via divisible load paradigm

The discrete wavelet transform (DWT) is a powerful signal processing tool, but comes with a considerable computation cost. In this paper, we consider the problem of parallelizing the DWT computation on loosely-coupled networked systems. We first systematically analyze the data dependencies among DWT computations, identify the partitionable portions and then by applying the divisible load theory (DLT), we derive a novel scheduling strategy to schedule DWT computation onto bus networks. Our study is first of its kind in the DLT literature to demonstrate handling a highly coupled recursive computational nature of this problem towards gaining a significant speed-up.