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Table 3 Comparison of MaxSSmap and MaxSSmap_fast to a GPU and a SIMD high performance Smith-Waterman implementation

From: MaxSSmap: a GPU program for mapping divergent short reads to genomes with the maximum scoring subsequence

 (a) Percent of 100,000 251 bp reads mapped correctly to the E.coli genome. Shown in parenthesis are incorrectly mapped reads and remaining are rejected
Div MaxSSmap_fast MaxSSmap CUDASW++ SSW
Reads without gaps  
.1 95 (0.4) 96 (0.4) 94 (0.9) 97 (3)
.2 95 (0.6) 95.3 (0.6) 94 (1) 97 (3)
.3 90 (1.1) 94.2 (0.9) 93 (1.3) 96 (4)
Reads with gaps  
.1 92 (1.5) 93.1 (1.9) 94 (0.9) 97 (3)
.2 90 (1.7) 92.5 (2.1) 92 (1) 96 (4)
.3 81 (2.8) 89.9 (3.5) 92 (1.4) 95 (5)
(b) Time in minutes to map 100,000 251 bp reads to the E.coli genome
Div MaxSSmap_fast MaxSSmap CUDASW++ SSW
Reads without gaps  
.1 20 28 164 1288
.2 20 28 164 1275
.3 20 28 164 1255
Reads with gaps  
.1 20 28 163 1283
.2 20 28 162 1266
.3 20 28 162 1235
  1. These are simulated Illumina reads and contain realistic base qualities generated from Illumina short reads. Each divergence represents the average percent of mismatches in the reads. So 0.1 means 10% mismatches on the average. The gaps are randomly chosen to occur in the read or the genome and are of length at most 30.