2 research outputs found
GPU Profiling of Singular Value Decomposition in OLPCA Method for Image Denoising
We focus on the Graphic Processor Unit (GPU) profiling of the Singular
Value Decomposition (SVD) that is a basic task of the Overcomplete Local
Principal Component Analysis (OLPCA) method. More in detail, we
investigate the impact of the SVD on the OLPCA algorithm for the
Magnetic Resonance Imaging (MRI) denoising application. We have resorted
several parallel approaches based on scientific libraries in order to
investigate the heavy computational complexity of the algorithm. The GPU
implementation is based on two specific libraries: NVIDIA cuBLAS and
CULA, in order to compare them. Our results show how the GPU library
based solution could be adopted for improving the performance of same
tasks in a denoising algorithm