dc.contributor.author | Pratas, F. | en |
dc.contributor.author | Trancoso, Pedro | en |
dc.contributor.author | Sousa, L. | en |
dc.contributor.author | Stamatakis, A. | en |
dc.contributor.author | Shi, G. | en |
dc.contributor.author | Kindratenko, V. | en |
dc.creator | Pratas, F. | en |
dc.creator | Trancoso, Pedro | en |
dc.creator | Sousa, L. | en |
dc.creator | Stamatakis, A. | en |
dc.creator | Shi, G. | en |
dc.creator | Kindratenko, V. | en |
dc.date.accessioned | 2019-11-13T10:42:05Z | |
dc.date.available | 2019-11-13T10:42:05Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54885 | |
dc.description.abstract | Currently, we are facing a situation where applications exhibit increasing computational demands and where a large variety of parallel processor systems are available. In this paper we focus on exploiting fine-grain parallelism for three applications with distinct characteristics: a Bioinformatics application (MrBayes), a Molecular Dynamics application (NAMD), and a database application (TPC-H). We assess, side-by-side, the performance of the three applications on general-purpose multi-core processors, the Cell Broadband Engine (Cell/BE), and Graphics Processing Units (GPU). Our results indicate that application performance depends on the characteristics of the parallel architectures and on the computational requirements of the core functions of the respective applications. For MrBayes the best overall performance is achieved on general-purpose multi-core processors, for NAMD on the Cell/BE, and for TPC-H on GPUs. © 2011 Elsevier B.V. All rights reserved. | en |
dc.source | Parallel Computing | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862697881&doi=10.1016%2fj.parco.2011.08.002&partnerID=40&md5=bfeb3cdac4c28baacdd3f123198f6d3c | |
dc.subject | Parallel architectures | en |
dc.subject | Parallel processing systems | en |
dc.subject | Molecular dynamics | en |
dc.subject | Computer graphics | en |
dc.subject | Microprocessor chips | en |
dc.subject | Multi-core processor | en |
dc.subject | Bioinformatics | en |
dc.subject | Program processors | en |
dc.subject | Performance evaluation | en |
dc.subject | Multi core | en |
dc.subject | Database workload | en |
dc.subject | Database workloads | en |
dc.subject | Fine grain parallelism | en |
dc.subject | Fine-grain parallelism | en |
dc.subject | Multi-core acelerators | en |
dc.subject | Multi-core processors | en |
dc.subject | Scientific workloads | en |
dc.title | Fine-grain parallelism using multi-core, Cell/BE, and GPU systems | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1016/j.parco.2011.08.002 | |
dc.description.volume | 38 | |
dc.description.issue | 8 | |
dc.description.startingpage | 365 | |
dc.description.endingpage | 390 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :13</p> | en |
dc.source.abbreviation | Parallel Comput | en |
dc.contributor.orcid | Trancoso, Pedro [0000-0002-2776-9253] | |
dc.gnosis.orcid | 0000-0002-2776-9253 | |