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

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.