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Table 3 Time comparison between our solution and the Farrars' implementation

From: Protein alignment algorithms with an efficient backtracking routine on multiple GPUs

avg. length # of sequences CPU, Farrar 1 GPU 4 GPUs
51 4000 24,113 8,064 2,070
  8000 95,156 31,111 7,855
  12000 210,806 69,083 17,439
154 2000 28,300 17,931 4,609
  4000 112,109 67,747 17,284
  6000 251,730 149,030 37,622
257 2000 61,182 49,226 12,535
  4000 242,756 186,436 47,305
  6000 543,656 410,255 103,278
459 2000 149,269 155,631 39,478
  4000 594,976 594,140 149,539
  6000 1339,538 1332,831 333,593
608 800 41,675 50,222 12,840
  1200 92,776 106,840 27,406
  1600 164,135 191,793 48,463
1103 800 123,572 164,780 41,946
  1200 278,194 359,065 89,899
  1600 495,624 628,847 158,699
  1. Mean times (in seconds) for the Smith-Waterman algorithm applied to different sets of sequences. Average lengths of sequences as well as cardinality of sets are given. The Farrar's implementation computes only scores while our GPU-based implementation computes scores and alignments.