CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

BMC Bioinformatics

Table 3 Smith-Waterman in CUDA running on single and double GPU vs. Farrar's solution

*Sequence*		SW-Cuda*		SW-Cuda**		*Farrar*
*Name*	*Length*	*Time (s)*	*MCUPS*	*Time (s)*	*MCUPS*	*Time (s)*	*MCUPS*
P02232	143	5.59	1845	2.95	3497	9	1149
P01111	189	7.59	1796	3.84	3551	10	1367
P05013	189	7.59	1796	3.84	3551	10	1367
P14942	222	8.84	1812	4.48	3575	12	1338
P00762	246	9.85	1802	5.01	3542	13	1369
P10318	362	14.71	1775	7.57	3450	15	1746
P07327	374	15.28	1766	7.86	3433	16	1691
P01008	464	18.96	1765	9.83	3405	18	1864
P10635	497	20.39	1758	10.43	3438	19	1892
P25705	553	22.83	1747	11.88	3358	19	2105
P03435	567	23.32	1754	11.96	3420	20	2045

Substitution matrix used: BLOSUM50. Gap-open penalty: 10. Gap-extension penalty: 2.
Database used: SwissProt (Rel. 49.1 – 208,005 proteins and 75,841,138 amino acids).
* Smith-Waterman in CUDA running on an NVidia GeForce 8800 GTX
** Smith-Waterman in CUDA running on two NVidia GeForce 8800 GTX

ISSN: 1471-2105