Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis
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Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosisFecha
2017Cita bibliográfica
Jorge González-Domínguez, Beatriz Remeseiro, María J. Martín, Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis, Computer Methods and Programs in Biomedicine, Volume 139, 2017, Pages 51-60, ISSN 0169-2607, https://doi.org/10.1016/j.cmpb.2016.10.027.
Resumen
[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.
Palabras clave
Dry eye syndrome
Tear film map
Parallel programming
High performance computing
Message passing
Tear film map
Parallel programming
High performance computing
Message passing
Versión del editor
Derechos
Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
1872-7565
0169-2607
0169-2607