Title

Accelerating Matlab Image Processing Toolbox Functions On Gpus

Keywords

CUDA; GPGPU; Image processing; MATLAB; OpenCL

Abstract

In this paper, we present our effort in developing an open-source GPU (graphics processing units) code library for the MATLAB Image Processing Toolbox (IPT). We ported a dozen of representative functions from IPT and based on their inherent characteristics, we grouped these functions into four categories: data independent, data sharing, algorithm dependent and data dependent. For each category, we present a detailed case study, which reveals interesting insights on how to efficiently optimize the code for GPUs and highlight performance-critical hardware features, some of which have not been well explored in existing literature. Our results show drastic speedups for the functions in the data-independent or data-sharing category by leveraging hardware support judiciously; and moderate speedups for those in the algorithm-dependent category by careful algorithm selection and parallelization. For the functions in the last category, fine-grain synchronization and data-dependency requirements are the main obstacles to an efficient implementation on GPUs. Copyright© 2010 ACM.

Publication Date

5-19-2010

Publication Title

International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS

Number of Pages

75-85

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/1735688.1735703

Socpus ID

77952261493 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/77952261493

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