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Applying dynamic balancing to improve the performance of MPI parallel genomics applications
dc.contributor.author | Fernández Fraga, Alejandro | |
dc.contributor.author | González-Domínguez, Jorge | |
dc.contributor.author | Martín, María J. | |
dc.date.accessioned | 2024-07-15T10:18:00Z | |
dc.date.available | 2024-07-15T10:18:00Z | |
dc.date.issued | 2024-05-21 | |
dc.identifier.citation | Alejandro Fernandez-Fraga, Jorge Gonzalez-Dominguez, and Maria J. Martin. 2024. Applying dynamic balancing to improve the performance of MPI parallel genomics applications. In Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (SAC '24). Association for Computing Machinery, New York, NY, USA, 506–514. https://doi.org/10.1145/3605098.3635986 | es_ES |
dc.identifier.isbn | 979-8-4007-0243-3 | |
dc.identifier.uri | http://hdl.handle.net/2183/37990 | |
dc.description | © ACM 2024. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (SAC '24). | es_ES |
dc.description.abstract | [Absctract]: Genomics applications are becoming more and more important in the field of bioinformatics, as they allow researchers to extract meaningful information from the huge amount of data generated by the new sequencing technologies. The analysis of these data is a very time consuming task and, therefore, the use of High Performance Computing (HPC) and parallel processing techniques is essential. Although the structure of these applications can be easily adapted to parallel systems by distributing the data to be processed among the available processors, load imbalance is a usual cause of performance degradation. In this paper we propose a dynamic load balancing method based on MPI RMA one-sided communications to minimize the synchronization among processes and the overhead due to communications while improving the workload balance. The strategy is applied, as a case study, to ParRADMeth, an MPI/OpenMP parallel application for the identification of Differential Methylated Regions (DMRs). Results show that the new version of the tool outperforms the previous one in all cases, achieving high performance and scalability. For example, our approach is up to 243 times faster than the sequential version and 1.74 times faster than the previous parallel version when processing a real dataset on a cluster with 8 nodes, each one with 32 CPU cores. | es_ES |
dc.description.sponsorship | This work has been supported by grants PID2019-104184RB-I00 and PID2022-136435NB-I00, both grants funded by MCIN/AEI/ 10.13039/501100011033, PID2022 also funded by "ERDF A way of making Europe", EU; the Ministry of Universities of Spain under grant FPU21/03408; and by Xunta de Galicia and FEDER funds (Centro de Investigación de Galicia accreditation 2019-2022 and Consolidation Program of Competitive Reference Groups, under Grants ED431G 2019/01 and ED431C 2021/30, respectively) | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2021/30 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Association for Computing Machinery (ACM) | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104184RB-I00/ES/DESAFIOS ACTUALES EN HPC: ARQUITECTURAS, SOFTWARE Y APLICACIONES | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-136435NB-I00/ES/ARQUITECTURAS, FRAMEWORKS Y APLICACIONES DE LA COMPUTACION DE ALTAS PRESTACIONES | es_ES |
dc.relation | info:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/FPU21%2F03408/ES/ | es_ES |
dc.relation.uri | https://doi.org/10.1145/3605098.3635986 | es_ES |
dc.subject | Differential Methylation | es_ES |
dc.subject | MPI | es_ES |
dc.subject | OpenMP | es_ES |
dc.subject | RMA | es_ES |
dc.subject | Dynamic Load Balancing | es_ES |
dc.title | Applying dynamic balancing to improve the performance of MPI parallel genomics applications | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Proceedings of the 39th ACM/ SIGAPP Symposium on Applied Computing (SAC '24) | es_ES |
UDC.startPage | 506 | es_ES |
UDC.endPage | 514 | es_ES |
UDC.conferenceTitle | SAC '24: 39th ACM/SIGAPP Symposium on Applied Computing | es_ES |