Skip to main content

Table 10 Running time comparison of CUDA and OpenCL implementations of MaxSSmap (denoted by MSS)

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

  (a) Time in minutes to map 100,000 251 bp reads to the E.coli genome. See Table 3 caption for details about reads

Div

MSS_fast

MSS

MSS_fast

MSS

MSS_fast

MSS

CUDA 4.2

CUDA 6.0

 

OpenCL

 

Reads without gaps

 

.1

20

28

17

27

17

27

.2

20

28

17

27

17

27

.3

20

28

17

27

17

27

Reads with gaps

 

.1

20

28

17

27

17

27

.2

20

28

17

27

17

27

.3

20

28

17

27

17

27

   (b) Time in minutes to map paired human reads from NA12878 in 1000 genomes (SRR016607) of length 101 bp to the human

   genome. We denote NextGenMap by NGM and MaxSSmap by MSS. See Table 8 for more details about reads

NGM+

NGM+

NGM+

NGM+

NGM+

NGM+

 

MSS_fast

MSSmap

MSS_fast

MSS

MSS_fast

MSS

 

CUDA 4.2

 

s

 

OpenCL

  

1295.9

2242.4

1183.5

2092.7

1252.7

2159.9

 

   (c) Time in minutes to map 100,000 ancient horse DNA reads (SRR111892) of length 76 bp to

   the horse genome Equus_caballus EquCab2 (GCA_000002305.1). See Table 9 for more details

   about reads

NGM+

NGM+

NGM+

NGM+

NGM+

NGM+

 

MSS_fast

MSSmap

MSS_fast

MSS

MSS_fast

MSS

 

CUDA 4.2

 

CUDA 6.0

 

OpenCL

  

1609.6

2836

1515

2689.8

1561.8

2736.8

 
  1. The output from the three methods give the same accuracies and errors as given earlier but the running times vary. We find the CUDA 6.0 implementation to have the lowest runtimes followed by OpenCL and CUDA 4.2.