Fig. 5From: K-mer clustering algorithm using a MapReduce framework: application to the parallelization of the Inchworm module of TrinityStratification of the runtime in terms of individual steps within both versions of Inchworm, for the experimental mouse dataset (see Table 1). OI represents Original Inchworm; MR represents MapReduce-Inchworm. On the X-axis, original represents the original version of Inchworm, while 32–192 represent the numbers of compute nodes allocated for MapReduce-Inchworm. The original Inchworm is divided into three steps: step1 corresponds to Jellyfish [44]; step 2 corresponds to parsing kmers; and step3 corresponds to Inchworm contig construction. MapReduce-Inchworm is divided into six steps: an initial step for splitting input reads and steps 1–5. The initial step splits an input file (containing the RNA-Seq reads) into multiple files according to the number of allocated compute nodes. Steps 1 to 5 of the main algorithm are described in detail in Methods. Results are given with pagesize assigned to 2GB, cf. Fig. 3(b) Back to article page