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- all benchmarks - binary-trees chameneos-redux fannkuch fasta k-nucleotide mandelbrot meteor-contest n-body pidigits regex-dna reverse-complement spectral-norm thread-ring - all languages - Ada 2005 GNAT ATS C GNU gcc C# Mono C++ GNU g++ Clean Erlang HiPE F# Mono Fortran Intel Go 6g 8g Haskell GHC Java 6 -server Java 6 -Xint Java 6 steady state JavaScript TraceMonkey JavaScript V8 Lisp SBCL Lua OCaml Pascal Free Pascal Perl PHP Python CPython Ruby JRuby Ruby MRI Scala Scheme PLT Smalltalk VisualWorks

 How big is the measured performance difference?

Each chart bar shows how many times more Time or how many times more Memory one unidentified ↓ k-nucleotide program used, compared to the program that used least Time or the program that used least Memory.

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

This table shows 5 measurements - CPU Time, Elapsed Time, Memory, Code and ~ CPU Load.

Compare how much Memory the k-nucleotide programs used - sort Memory KB. Compare how much Code the programs used - sort Code B

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

		sort	sort	sort	sort
×	Program Source Code	CPU secs	Elapsed secs	Memory KB	Code B	~ CPU Load
1.0	C++ GNU g++ #6	11.72	3.49	140,436	3415	78% 94% 81% 82%
1.6	C++ GNU g++ #2	20.27	5.54	177,148	2673	99% 88% 90% 93%
2.4	C++ GNU g++ #3	29.89	8.23	176,520	2313	98% 88% 88% 88%
2.6	C++ GNU g++	33.05	9.01	176,668	2106	89% 88% 89% 99%
3.4	Ada 2005 GNAT #2	27.89	11.89	256,692	4504	45% 75% 30% 84%
4.2	Java 6 -server #2	49.22	14.57	480,408	1602	79% 78% 98% 82%
7.3	Java 6 -server	88.50	25.67	1,568,640	1330	85% 89% 85% 85%
7.9	Scala #4	91.39	27.61	981,336	1287	89% 79% 82% 79%
11	ATS	36.73	36.73	125,868	1336	100% 0% 0% 0%
11	OCaml #2	88.25	37.80	574,588	1205	41% 25% 81% 85%
11	OCaml #3	94.18	39.93	476,980	1095	79% 24% 87% 44%
16	Haskell GHC #3	128.58	56.53	427,128	2749	34% 72% 48% 42%
22	C GNU gcc #2	78.17	78.17	1,702,416	1141	0% 0% 100% 0%
22	Perl	256.15	78.58	2,883,780	648	81% 71% 88% 84%
25	Fortran Intel	86.88	86.88	229,912	2238	0% 0% 100% 0%
26	OCaml	91.03	91.03	496,616	870	0% 0% 100% 0%
31	C# Mono	108.42	107.49	560,924	1420	0% 0% 0% 100%
33	Python CPython #6	5 min	114.57	489,420	520	48% 47% 92% 89%
35	Lisp SBCL #3	121.38	121.38	348,620	1284	0% 0% 100% 0%
36	Clean	124.87	124.87	2,097,740	1511	0% 100% 0% 0%
36	Pascal Free Pascal	126.78	126.79	129,848	2380	0% 0% 0% 100%
37	Pascal Free Pascal #2	125.95	128.13	129,844	2383	1% 1% 96% 1%
38	PHP #3	7 min	131.69	248,696	1268	97% 89% 67% 79%
38	Python CPython #5	6 min	133.04	489,424	557	76% 46% 96% 66%
41	C GNU gcc	140.85	144.81	150,612	1340	1% 5% 92% 0%
47	C# Mono #3	6 min	163.38	496,168	1404	94% 20% 14% 92%
49	Erlang HiPE #3	7 min	171.07	711,560	932	58% 71% 84% 60%
56	C# Mono #2	197.24	196.86	524,652	1012	1% 2% 56% 41%
58	Lua #2	204.16	204.16	670,800	613	0% 0% 0% 100%
59	Lua	204.89	206.26	685,508	601	98% 1% 1% 0%
66	Erlang HiPE	8 min	229.90	3,845,368	930	60% 58% 55% 72%
67	Scheme PLT	232.84	233.18	1,298,832	623	91% 3% 3% 2%
67	Perl #2	229.45	233.57	780,232	359	0% 1% 0% 98%
86	Java 6 -Xint #2	17 min	5 min	336,432	1602	85% 85% 88% 99%
87	Go 6g 8g	5 min	5 min	379,480	874	0% 96% 3% 0%
118	Java 6 -Xint	25 min	6 min	787,536	1330	92% 91% 99% 92%
122	Lisp SBCL	7 min	7 min	382,300	847	1% 96% 1% 2%
123	PHP #2	7 min	7 min	222,736	914	100% 0% 0% 0%
127	JavaScript TraceMonkey	7 min	7 min	1,057,340	423	98% 1% 1% 0%
132	Python CPython	7 min	7 min	486,900	475	1% 0% 99% 1%
143	Ruby JRuby #2	8 min	8 min	534,384	420	2% 33% 66% 2%
155	JavaScript TraceMonkey #3	9 min	9 min	442,884	390	0% 0% 48% 51%
244	Ruby MRI #2	14 min	14 min	166,340	420	0% 0% 100% 0%
	Erlang HiPE #2	Failed			997
	Haskell GHC #2	Failed			1767
	JavaScript TraceMonkey #2	Bad Output			400
	JavaScript V8	Timed Out	1h 00 min		423
	JavaScript V8 #2	Failed			400
	JavaScript V8 #3	Timed Out	1h 00 min		390
	Lisp SBCL #4	Failed			1434
	Smalltalk VisualWorks	Bad Output			1191
	Smalltalk VisualWorks #4	Bad Output			1296
interesting alternative programs
0.8	C++ GNU g++ #5	7.92	2.73	49,540	3416
missing programs
	F# Mono	No program
	Java 6 steady state	No program

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

diff program output for this 100KB input file (generated with the fasta program N = 10000) with this output file to check your program is correct before contributing.

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).