reverse-complement benchmark ≈240MB N=25,000,000

Each chart bar shows how many times more Code, one ↓ reverse-complement program used, compared to the program that used least Code.

These are not the only programs that could be written. These are not the only compilers and interpreters. These are not the only programming languages.

Column × shows how many times more each program used compared to the benchmark program that used least.

    sortsortsort 
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Ruby JRuby #2 24.8418.241,284,372255  22% 14% 14% 88%
1.0Ruby #2 8.218.22132,256255  1% 0% 0% 100%
1.0Hack #2 6.916.92586,520261  1% 1% 1% 100%
1.0PHP #2 6.406.41444,376262  0% 0% 0% 100%
1.1Perl #3 2.902.90374,704284  0% 0% 0% 100%
1.2Hack 6.686.69459,952294  99% 1% 1% 0%
1.2Python 3 #3 19.8419.87966,060295  1% 0% 1% 100%
1.2PHP 6.596.61369,940297  0% 0% 0% 100%
1.3Python 3 #4 5.925.941,008,592325  1% 1% 1% 100%
1.5OCaml #2 4.504.51211,504394  0% 0% 0% 100%
1.7Rust 80.5680.59129,892433  1% 0% 100% 1%
2.0Scala #4 2.202.14415,572501  72% 24% 3% 6%
2.1Go #3 1.141.14160,720543  2% 1% 100% 1%
2.1Go #2 1.111.11160,948546  0% 0% 100% 3%
2.1Racket 13.6313.64546,072547  1% 0% 1% 100%
2.2Dart #3 19.5719.211,757,524551  2% 0% 100% 2%
2.2Dart #2 28.0227.611,754,748555  1% 1% 2% 100%
2.2C++ g++ 2.702.71247,208571  3% 1% 100% 1%
2.3Java  #4 2.592.49488,368592  95% 2% 6% 2%
2.4Erlang #3 68.5166.571,087,836624  32% 51% 19% 3%
2.4Erlang HiPE #3 57.1454.901,233,548624  38% 31% 21% 16%
2.5C++ g++ #5 19.3719.38185,728646  0% 1% 100% 1%
2.8C gcc #4 1.141.14125,212704  0% 3% 100% 0%
2.9Clojure #5 4.062.73569,780727  15% 35% 95% 7%
2.9Rust #2 1.481.49254,760739  0% 3% 100% 1%
2.9C gcc #2 0.770.51250,784741  21% 18% 74% 43%
2.9Java  #6 1.651.36523,400745  80% 36% 4% 5%
2.9Pascal Free Pascal #2 2.022.02125,648751  1% 0% 100% 2%
3.0Scala #8 1.791.34503,168761  6% 3% 90% 40%
3.0Fortran Intel #2 6.476.48174,276772  0% 0% 0% 100%
3.2C++ g++ #3 1.241.24125,160810  1% 1% 3% 100%
3.4C# Mono #3 8.048.05294,644863  75% 5% 21% 1%
3.5Ada 2005 GNAT 5.705.71125,744885  1% 96% 0% 4%
3.5Lisp SBCL 2.262.26291,560896  1% 0% 100% 0%
3.6Haskell GHC #2 2.842.44618,532919  6% 6% 100% 7%
3.9Clojure #4 5.554.18475,752997  58% 14% 52% 11%
3.9Haskell GHC #3 1.551.38126,340999  99% 4% 4% 4%
4.0Fortran Intel 1.161.17246,4881013  0% 0% 100% 1%
4.0Racket #2 4.364.36171,3081026  0% 1% 100% 1%
4.1Clojure 4.493.20427,3561044  13% 92% 24% 14%
4.2Rust #3 1.181.18254,7601059  3% 99% 0% 0%
4.2OCaml 1.5962,9761064  4% 25% 65% 62%
4.2C++ g++ #2 1.061.06247,1561082  0% 2% 4% 100%
4.3C# Mono 2.702.70178,7841099  0% 27% 73% 1%
4.6Erlang HiPE #4 43.4734.81641,3401167  76% 29% 10% 11%
4.6Erlang #4 46.0835.90631,9281167  17% 54% 20% 39%
4.9Go 0.920.76250,6801243  88% 9% 26% 3%
5.1Erlang HiPE 20.7110.53947,6881302  42% 75% 38% 43%
5.1Erlang 20.4410.301,002,1881302  40% 70% 38% 52%
5.2OCaml #3 0.7830,8401314  52% 29% 60% 78%
6.4Java  #7 2.187.74274,6001640  69% 22% 4% 71%
6.5Java  #3 2.731.25307,7401661  37% 90% 44% 50%
7.3C gcc 0.970.61445,9441867  25% 3% 98% 37%
7.9Rust #4 0.740.49257,1602015  12% 82% 41% 18%
8.1OCaml #4 1.531.54135,0962064  1% 0% 10% 99%
8.9C++ g++ #4 1.020.65247,5082275  17% 64% 34% 48%
13Ada 2005 GNAT #2 0.980.83198,9083220  31% 80% 11% 4%
Scala #6 Failed519
Scala #7 Failed949
Scala #5 Failed329
"wrong" (different) algorithm / less comparable programs
1.2Python 3 #5 4.094.10482,816306
1.9Java  1.571.54523,892476
3.2Clojure #3 5.344.15576,444812
missing benchmark programs
F# Mono No program

 reverse-complement benchmark : Read DNA sequences - write their reverse-complement

You can write your own program for this task and contribute to the benchmarks game by following these general instructions.

More specifically:

diff program output for this 10KB input file (generated with the fasta program N = 1000) with this output file to check your program is correct before contributing.

We are trying to show the performance of various programming language implementations - so we ask that contributed programs not only give the correct result, but also use the same algorithm to calculate that result.

We use the FASTA file generated by the fasta benchmark as input for this benchmark. Note: the file may include both lowercase and uppercase codes.

Each program should

We use these code complements:

code  meaning   complement
A    A                   T
C    C                   G
G    G                   C
T/U  T                   A
M    A or C              K
R    A or G              Y
W    A or T              W
S    C or G              S
Y    C or T              R
K    G or T              M
V    A or C or G         B
H    A or C or T         D
D    A or G or T         H
B    C or G or T         V
N    G or A or T or C    N

"by knowing the sequence of bases of one strand of DNA we immediately know the sequence of the DNA strand which will bind to it, this strand is called the reverse complement"
DNA: Structure and Function

Revised BSD license

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