x64 Ubuntu : Intel® Q6600® quad-core
Computer Language Benchmarks Game      [[ Play ]]

- all benchmarks - n-body fannkuch-redux meteor-contest fasta fasta-redux spectral-norm reverse-complement mandelbrot k-nucleotide regex-dna pidigits chameneos-redux thread-ring binary-trees-redux binary-trees - all languages - Ada 2005 GNAT ATS C gcc Clojure C# Mono C++ g++ Dart Erlang Erlang HiPE F# Mono Fortran Intel Go Haskell GHC Java 7 Lisp SBCL OCaml Pascal Free Pascal Perl PHP Python 3 Racket Ruby 2.0 Ruby JRuby Scala x86 one core x64 quad-core x86 quad-core x64 one core

 k-nucleotide benchmark ≈240MB N=25,000,000

Each chart bar shows how many times slower, one ↓ k-nucleotide program was, compared to the fastest program.

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.

		sort		sort	sort
×	Program Source Code	CPU secs	Elapsed secs	Memory KB	Code B	≈ CPU Load
1.0	C++ g++ #3	25.89	7.79	155,916	1252	78% 80% 78% 98%
1.1	Scala #2	23.86	8.31	215,304	2080	56% 79% 75% 77%
1.7	Ada 2005 GNAT #2	36.22	13.19	256,144	4865	49% 42% 100% 84%
1.7	Java 7  #3	46.39	13.25	450,972	1630	86% 84% 96% 85%
1.7	Java 7  #2	46.47	13.27	447,016	1602	85% 94% 89% 82%
2.1	C gcc #7	44.64	16.00	180,380	2280	35% 50% 98% 97%
2.4	C gcc #6	59.59	18.40	180,380	2439	97% 55% 75% 97%
2.4	Haskell GHC	68.50	18.58	374,488	1693	91% 93% 93% 93%
2.6	Haskell GHC #2	74.79	20.02	374,916	1965	93% 94% 92% 96%
2.8	OCaml #3	56.82	21.99	258,480	1789	55% 39% 100% 65%
3.3	ATS #3	92.32	25.57	177,832	3810	88% 96% 89% 88%
3.3	Fortran Intel #2	65.52	25.74	196,212	2079	48% 38% 90% 83%
3.6	C# Mono #4	85.26	28.21	561,292	1696	93% 69% 71% 70%
4.3	Go #5	83.26	33.62	262,224	1268	97% 86% 36% 30%
4.5	Clojure #7	111.62	34.80	1,006,640	3030	84% 74% 84% 80%
4.7	OCaml #2	85.15	36.74	437,928	1205	32% 31% 81% 88%
4.8	Lisp SBCL #5	37.08	37.13	138,312	2301	0% 0% 0% 100%
4.8	Lisp SBCL #4	37.26	37.30	138,304	2272	0% 0% 0% 100%
5.3	ATS #2	41.54	41.57	125,912	3238	0% 0% 0% 100%
5.4	Haskell GHC #3	120.21	42.02	496,844	2749	62% 100% 50% 75%
6.0	Scala #6	166.11	46.37	489,420	1380	91% 89% 89% 91%
6.5	Clojure #6	136.12	50.87	999,864	1737	78% 78% 63% 49%
7.2	C# Mono #5	188.32	56.25	539,248	2445	85% 81% 81% 90%
8.5	Clojure #4	214.92	65.97	995,992	1944	89% 83% 67% 87%
9.0	OCaml	70.22	70.30	411,188	870	0% 0% 100% 0%
9.0	Perl	240.60	70.32	1,886,164	648	84% 90% 82% 87%
9.7	Go	213.09	75.34	380,312	980	85% 100% 35% 63%
11	Pascal Free Pascal #2	86.05	86.09	130,568	2383	91% 0% 0% 9%
11	C# Mono	86.90	86.31	537,916	1420	1% 2% 97% 1%
11	Fortran Intel	88.60	88.68	187,120	2238	0% 0% 100% 0%
12	Racket #4	89.60	89.61	378,488	881	0% 0% 100% 0%
12	PHP #4	5 min	92.65	247,640	1060	88% 81% 93% 96%
14	C# Mono #3	6 min	111.08	506,444	1404	87% 93% 94% 85%
16	F# Mono	6 min	124.91	975,260	701	78% 77% 77% 69%
17	Python 3 #8	6 min	129.56	451,488	647	60% 98% 58% 81%
18	Erlang HiPE #3	6 min	143.11	1,133,724	932	68% 78% 64% 60%
18	Lisp SBCL #3	143.15	143.25	489,872	1284	0% 3% 97% 0%
19	Lisp SBCL #2	147.82	148.16	489,872	1277	0% 15% 85% 0%
20	Erlang #3	7 min	157.60	996,280	932	80% 73% 64% 57%
23	Ruby JRuby	9 min	176.19	939,416	637	94% 69% 74% 83%
23	Ruby JRuby #3	9 min	176.42	934,968	540	67% 91% 78% 75%
23	C# Mono #2	177.06	176.66	550,328	1012	1% 4% 67% 29%
23	Erlang HiPE	6 min	181.00	3,734,268	930	84% 50% 53% 68%
25	Erlang	7 min	195.37	3,684,516	930	82% 49% 58% 73%
25	Racket	195.96	195.98	1,304,560	542	0% 0% 27% 73%
26	Ruby 2.0	11 min	201.03	128,768	637	88% 84% 70% 98%
29	Perl #2	221.13	224.63	778,212	359	97% 1% 0% 0%
57	Python 3	7 min	7 min	402,568	487	86% 6% 8% 0%
72	Ruby 2.0 #2	9 min	9 min	289,620	420	0% 0% 0% 100%
77	Ruby 2.0 #3	11 min	10 min	291,564	540	22% 33% 33% 21%
	C++ g++	Make Error			2106
	Erlang #2	Failed			997
	Erlang HiPE #2	Failed			997
	Lisp SBCL	Bad Output			847
	Racket #2	Bad Output			842
	Ruby JRuby #2	Failed			421
	Scala	Failed			1625
	Scala #4	Failed			1287
"wrong" (different) algorithm / less comparable programs
0.3	C++ g++ #5	7.76	2.47	49,264	3416
0.3	C gcc #4	9.04	2.69	174,464	2409
0.4	C++ g++ #6	11.80	3.33	139,240	3415
0.4	Java 7	11.76	3.36	167,120	5211
0.9	Ada 2005 GNAT	14.47	7.05	399,744	6503
2.0	C# Mono #6	44.13	15.63	271,240	1433
2.5	C gcc #5	56.66	19.51	282,036	2519
7.0	Python 3 #2	97.00	54.37	497,084	624
missing benchmark programs
	Dart	No program

 k-nucleotide benchmark : Hashtable update and k-nucleotide strings

diff program output for this 250KB input file (generated with the fasta program N = 25000) 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 FASTA files generated by the fasta benchmark as input for this benchmark. Note: the file may include both lowercase and uppercase codes.

Each program should

• read line-by-line a redirected FASTA format file from stdin
• extract DNA sequence THREE
• define a procedure/function to update a hashtable of k-nucleotide keys and count values, for a particular reading-frame — even though we'll combine k-nucleotide counts for all reading-frames (grow the hashtable from a small default size)
• use that procedure/function and hashtable to
  • count all the 1-nucleotide and 2-nucleotide sequences, and write the code and percentage frequency, sorted by descending frequency and then ascending k-nucleotide key
  • count all the 3- 4- 6- 12- and 18-nucleotide sequences, and write the count and code for the specific sequences GGT GGTA GGTATT GGTATTTTAATT GGTATTTTAATTTATAGT

In practice, less brute-force would be used to calculate k-nucleotide frequencies, for example Virus Classification using k-nucleotide Frequencies and A Fast Algorithm for the Exhaustive Analysis of 12-Nucleotide-Long DNA Sequences. Applications to Human Genomics (105KB pdf).

  Home   Conclusions   License   Play