Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis. (February 2017)

• Record Type: Journal Article
• Authors: González-Domínguez, Jorge; Remeseiro, Beatriz; Martín, María J.
• Is Part Of: Computer methods and programs in biomedicine. Volume 139(2017)
• Page Start: 51
• Page End: 60
• Publication Date: 2017-02
• Subjects: Dry eye syndrome -- Tear film map -- Parallel programming -- High performance computing -- Message passing; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2016.10.027
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Tear film maps can be used in the diagnosis of the dry eye syndrome. Our method accelerates the generation of tear film maps on distributed-memory clusters. Novel hybrid parallel approach that uses MPI and multithreading. Time reduced from around 2 minutes in the state of the art to less than 10 seconds. Runtime reduction can extend the use of tear film maps among medical experts. Abstract: Background and objectives: The analysis of the interference patterns on the tear film lipid layer is a useful clinical test to diagnose dry eye syndrome. This task can be automated with a high degree of accuracy by means of the use of tear film maps. However, the time required by the existing applications to generate them prevents a wider acceptance of this method by medical experts. Multithreading has been previously successfully employed by the authors to accelerate the tear film map definition on multicore single-node machines. In this work, we propose a hybrid message-passing and multithreading parallel approach that further accelerates the generation of tear film maps by exploiting the computational capabilities of distributed-memory systems such as multicore clusters and supercomputers. Methods: The algorithm for drawing tear film maps is parallelized using Message Passing Interface (MPI) for inter-node communications and the multithreading support available in the C++11 standard for intra-node parallelization. The original algorithm is modified to reduce the communications and increase the scalability. Results: The hybrid method has been tested on 32 nodes of an Intel cluster (with two 12-core Haswell 2680v3 processors per node) using 50 representative images. Results show that maximum runtime is reduced from almost two minutes using the previous only-multithreaded approach to less than ten seconds using the hybrid method. Conclusions: The hybrid MPI/multithreaded implementation can be used by medical experts to obtain tear film maps in only a few seconds, which will significantly accelerate and facilitate the diagnosis of the dry eye syndrome.