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Efficient code development for improving execution performance in high-performance computing centers

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Abstract

Thanks to high-performance computing (HPC), it is possible to solve all kinds of highly complex projects from multiple scientific disciplines that require computationally intensive tasks to be undertaken and which otherwise could not be addressed. Unfortunately, since the development of parallel codes requires highly specific knowledge, it can become a challenge for beginners and non-expert programmers, especially when it comes to making adequate and efficient use of the available computing resources. To this end, we developed a transcompiler for helping researchers and inexperienced users who do not have the necessary skills in the use of parallel programming, and aimed at improving the performance of their HPC routines and tasks. Current efforts are focused on an additional module for optimizing code fragments in order to reduce their running times. In order to achieve this, twenty-six software techniques were selected from the literature to be integrated into this new module, all of them aimed at improving execution times of HPC programs by directly writing efficient code. Their effectiveness is analyzed and discussed in the current manuscript through a complete set of tests designed and conducted to measure and evaluate benefits achieved when applying these techniques.

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Acknowledgements

This research is partly financed by the European Union through the European Regional Development Fund (ERDF) Programme: Extremadura Operational Programme 2014–2020, Thematic objective 1: Research and Innovation, and Thematic Objective 2: Information and communication technologies. Ref. 2018.14.02.332A.444.00, CultivData Project. This work was also supported in part by the European Regional Development Fund and the Regional Ministry of Economy, Science and Digital Agenda of the Junta of Extremadura under project GR18195. This work has also been partially subsidized by the Government of Spain (Ministry of Science, Innovation and Universities, RTI2018-094591-B-I00) with the contribution of the ERDF.

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Authors and Affiliations

  1. CénitS-COMPUTAEX, Extremadura Supercomputing, Technological Innovation and Research Center, 10071, Cáceres, Spain

    Javier Corral-García & Felipe Lemus-Prieto

  2. Computer Science Department, University of Extremadura, 10003, Cáceres, Spain

    Miguel-Ángel Pérez-Toledano

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  1. Javier Corral-García
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  2. Felipe Lemus-Prieto
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  3. Miguel-Ángel Pérez-Toledano
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Correspondence to Javier Corral-García.

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Corral-García, J., Lemus-Prieto, F. & Pérez-Toledano, MÁ. Efficient code development for improving execution performance in high-performance computing centers. J Supercomput 77, 3261–3288 (2021). https://doi.org/10.1007/s11227-020-03382-z

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