Big Data Applications Using Workflows for Data Parallel Computing
| dc.contributor.author | Wang, Jianwu | |
| dc.contributor.author | Crawl, Daniel | |
| dc.contributor.author | Altintas, Ilkay | |
| dc.contributor.author | Li, Weizhong | |
| dc.date.accessioned | 2024-02-14T17:27:15Z | |
| dc.date.available | 2024-02-14T17:27:15Z | |
| dc.date.issued | 2014-04-16 | |
| dc.description.abstract | In the Big Data era, workflow systems need to embrace data parallel computing techniques for efficient data analysis and analytics. Here, the authors present an easy-to-use, scalable approach to build and execute Big Data applications using actor-oriented modeling in data parallel computing. They use two bioinformatics use cases for next-generation sequencing data analysis to verify the feasibility of their approach. | |
| dc.description.sponsorship | We thank the rest of the Kepler and bioKepler teams for their collaboration. This work was supported by bioKepler's US National Science Foundation ABI Award DBI-1062565. | |
| dc.description.uri | https://ieeexplore.ieee.org/document/6799151 | |
| dc.format.extent | 16 pages | |
| dc.genre | journal articles | |
| dc.genre | postprints | |
| dc.identifier | doi:10.13016/m2kdft-8wba | |
| dc.identifier.citation | J. Wang, D. Crawl, I. Altintas and W. Li, "Big Data Applications Using Workflows for Data Parallel Computing," in Computing in Science & Engineering, vol. 16, no. 4, pp. 11-21, July-Aug. 2014, doi: 10.1109/MCSE.2014.50. | |
| dc.identifier.uri | https://doi.org/10.1109/MCSE.2014.50 | |
| dc.identifier.uri | http://hdl.handle.net/11603/31619 | |
| dc.language.iso | en_US | |
| dc.publisher | IEEE | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Center for Accelerated Real Time Analysis | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
| dc.relation.ispartof | UMBC Data Science | |
| dc.relation.ispartof | UMBC Joint Center for Earth Systems Technology (JCET) | |
| dc.relation.ispartof | UMBC Center for Real-time Distributed Sensing and Autonomy | |
| dc.rights | © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
| dc.subject | UMBC Big Data Analytics Lab | |
| dc.title | Big Data Applications Using Workflows for Data Parallel Computing | |
| dc.type | Text | |
| dcterms.creator | https://orcid.org/0000-0002-9933-1170 |