Distanceless Label Propagation: an Efficient Direct Connected Component Labeling Algorithm for GPUs

Abstract : Modern computer architectures are mainly composed of multi-core processors and GPUs. Consequently, solely providing a sequential implementation of algorithms or comparing algorithm performance without regard to architecture is no longer pertinent. Today, algorithms have to address parallelism, multithreading and memory topology (private/shared memory, cache or scratchpad, ...). Most Connected Component Labeling (CCL) algorithms are sequential, direct and optimized for processors. Few were designed specifically for GPU architectures and none were designed to be adapted to different architectures. The most efficient GPU implementations are iterative; in order to manage synchronizations between processing units, but the number of iterations depends on the image shape and density. This paper describes the DLP (Distanceless Label Propagation) algorithms, an adaptable set of algorithms usable both on GPU and multi-core architectures, and DLP-GPU, an efficient direct CCL algorithm for GPU based on DLP mechanisms.
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Contributor : Laurent Cabaret <>
Submitted on : Wednesday, December 13, 2017 - 4:11:02 PM
Last modification on : Thursday, March 21, 2019 - 1:19:40 PM
Long-term archiving on : Wednesday, March 14, 2018 - 12:31:36 PM

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Laurent Cabaret, Lionel Lacassagne, Daniel Etiemble. Distanceless Label Propagation: an Efficient Direct Connected Component Labeling Algorithm for GPUs. IPTA2017 - International Conference on Image Processing Theory, Tools and Applications, Nov 2017, Montreal, Canada. ⟨hal-01656756⟩

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