2 research outputs found
The Parallel Algorithm for the 2-D Discrete Wavelet Transform
The discrete wavelet transform can be found at the heart of many
image-processing algorithms. Until now, the transform on general-purpose
processors (CPUs) was mostly computed using a separable lifting scheme. As the
lifting scheme consists of a small number of operations, it is preferred for
processing using single-core CPUs. However, considering a parallel processing
using multi-core processors, this scheme is inappropriate due to a large number
of steps. On such architectures, the number of steps corresponds to the number
of points that represent the exchange of data. Consequently, these points often
form a performance bottleneck. Our approach appropriately rearranges
calculations inside the transform, and thereby reduces the number of steps. In
other words, we propose a new scheme that is friendly to parallel environments.
When evaluating on multi-core CPUs, we consistently overcome the original
lifting scheme. The evaluation was performed on 61-core Intel Xeon Phi and
8-core Intel Xeon processors.Comment: accepted for publication at ICGIP 201
Accelerating discrete wavelet transforms on parallel architectures
The 2-D discrete wavelet transform (DWT) can be found in the heart of many image-processing algorithms. Until
recently, several studies have compared the performance of such transform on various shared-memory parallel architectures,
especially on graphics processing units (GPUs). All these studies, however, considered only separable
calculation schemes. We show that corresponding separable parts can be merged into non-separable units, which
halves the number of steps. In addition, we introduce an optional optimization approach leading to a reduction in
the number of arithmetic operations. The discussed schemes were adapted on the OpenCL framework and pixel
shaders, and then evaluated using GPUs of two biggest vendors. We demonstrate the performance of the proposed
non-separable methods by comparison with existing separable schemes. The non-separable schemes outperform
their separable counterparts on numerous setups, especially considering the pixel shaders