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Table 4 Performance 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 0,863 2,581 10,055
  8000 0,875 2,676 10,597
  12000 0,888 2,711 10,740
154 2000 1,677 2,647 10,296
  4000 1,693 2,801 10,980
  6000 1,696 2,865 11,349
257 2000 2,160 2,685 10,544
  4000 2,177 2,835 11,173
  6000 2,187 2,898 11,513
459 2000 2,824 2,709 10,679
  4000 2,834 2,837 11,274
  6000 2,831 2,846 11,370
608 800 2,842 2,358 9,224
  1200 2,871 2,493 9,720
  1600 2,885 2,469 9,770
1103 800 3,154 2,366 9,293
  1200 3,151 2,442 9,752
  1600 3,144 2,478 9,819
  1. Mean values of GCUPS (Giga Cell Updates Per Second) for the Smith-Waterman algorithm applied on different sets of sequences. The GCUPS value is mainly used for score-only versions of the algorithm. Here, the performance of the GPU-based method is understated, because the value does not count in any additional operations (or cells) needed by the backtracking stage while the entire computational time is always considered.