Analysis of the ParConnect algorithm ran on Intel Xeon Phi Knights Landing

•Analysis of the results of the Parconnect algorithm.•Compare ParConnect algorithm to related approaches.•Running the algorithm on Intel Xeon Phi architecture. Huge volume of data and high data complexity are the main challenges in metagenomic assembly. Therefore, Patrick Flick et al. present a nove...

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Vydané v:Parallel computing Ročník 70; s. 46 - 53
Hlavní autori: Hornung, Maximilian, Stefanov, Svilen, Schneller, David, Møller, Sharru
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.12.2017
Predmet:
Bioinformatics
De Bruijn Graph
Intel Xeon Phi
Reproducibility
Intel Xeon Phi
Reproducibility
Bioinformatics
De Bruijn Graph
ISSN:0167-8191, 1872-7336
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Popis
Shrnutí:•Analysis of the results of the Parconnect algorithm.•Compare ParConnect algorithm to related approaches.•Running the algorithm on Intel Xeon Phi architecture. Huge volume of data and high data complexity are the main challenges in metagenomic assembly. Therefore, Patrick Flick et al. present a novel highly-scalable distributed-memory parallel algorithm (ParConnect) to find connected subgraphs. Their approach to this subject leads to the well-studied problem of finding weakly connected components in a de Bruijn graph, which is used to represent overlaps between sequences of symbols. At the Student Cluster Competition 2016 (SCC 2016), we reproduced the results of their paper on an Intel Xeon Phi Knights Landing cluster and analyzed the share of communication time compared to the whole computation.
ISSN:0167-8191
1872-7336
DOI:10.1016/j.parco.2017.08.011