A Simple Compressive Sensing Algorithm for Parallel Many-Core Architectures

Authors:
Alexandre Borghi;Jérôme Darbon;Sylvain Peyronnet;Tony F. Chan;Stanley Osher
Affiliations:
Laboratoire de Recherche en Informatique (LRI), Université Paris Sud, Orsay, France;CMLA, ENS Cachan, CNRS, PRES UniverSud, Cachan, France and Department of Mathematics, UCLA, Los Angeles, USA;Laboratoire de Recherche en Informatique (LRI), Université Paris Sud, Orsay, France;Department of Mathematics, UCLA, Los Angeles, USA and The Hong-Kong University of Science and Technology, Kowloon, Hong Kong;Department of Mathematics, UCLA, Los Angeles, USA
Venue:
Journal of Signal Processing Systems
Year:
2013

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Abstract

In this paper we consider the l 1-compressive sensing problem. We propose an algorithm specifically designed to take advantage of shared memory, vectorized, parallel and many-core microprocessors such as the Cell processor, new generation Graphics Processing Units (GPUs) and standard vectorized multi-core processors (e.g. quad-core CPUs). Besides its implementation is easy. We also give evidence of the efficiency of our approach and compare the algorithm on the three platforms, thus exhibiting pros and cons for each of them.