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 | 11.41 | 11.41 | 142,264 | 3415 | 0% 0% 0% 100% |
| 1.5 | C++ GNU g++ #3 | 17.10 | 17.10 | 135,792 | 2313 | 0% 0% 0% 100% |
| 1.6 | C++ GNU g++ #2 | 18.29 | 18.30 | 146,264 | 2673 | 0% 0% 0% 100% |
| 1.9 | C++ GNU g++ | 21.15 | 21.16 | 135,792 | 2106 | 0% 0% 0% 100% |
| 2.4 | Ada 2005 GNAT #2 | 27.52 | 27.54 | 256,692 | 4504 | 0% 0% 0% 100% |
| 3.3 | ATS | 37.11 | 37.12 | 125,864 | 1336 | 0% 0% 0% 100% |
| 4.9 | Java 6 -server #2 | 55.75 | 55.78 | 368,424 | 1602 | 0% 0% 0% 100% |
| 6.9 | C GNU gcc #2 | 78.50 | 78.50 | 1,682,764 | 1141 | 0% 0% 0% 100% |
| 7.6 | Fortran Intel | 86.91 | 86.90 | 229,908 | 2238 | 0% 0% 0% 100% |
| 7.7 | Scala #4 | 87.73 | 87.82 | 902,212 | 1287 | 0% 0% 0% 100% |
| 7.7 | Java 6 -server | 87.83 | 87.89 | 1,230,996 | 1330 | 0% 0% 0% 100% |
| 7.7 | OCaml #2 | 88.09 | 88.09 | 574,588 | 1205 | 0% 0% 0% 100% |
| 8.0 | OCaml | 91.24 | 91.23 | 496,616 | 870 | 0% 0% 0% 100% |
| 8.1 | OCaml #3 | 92.03 | 92.03 | 476,980 | 1095 | 0% 0% 0% 100% |
| 8.5 | C# Mono #3 | 96.77 | 96.76 | 495,764 | 1404 | 0% 0% 0% 100% |
| 9.4 | C# Mono | 107.61 | 107.61 | 560,936 | 1420 | 0% 0% 0% 100% |
| 9.5 | Haskell GHC #3 | 107.98 | 107.98 | 433,276 | 2749 | 1% 1% 1% 100% |
| 11 | Lisp SBCL #3 | 121.40 | 121.39 | 348,620 | 1284 | 0% 0% 0% 100% |
| 11 | Clean | 124.87 | 124.87 | 2,097,736 | 1511 | 0% 0% 0% 100% |
| 11 | Pascal Free Pascal | 125.05 | 125.05 | 129,848 | 2380 | 0% 0% 0% 100% |
| 11 | Pascal Free Pascal #2 | 125.20 | 127.79 | 129,848 | 2383 | 0% 0% 0% 100% |
| 13 | C GNU gcc | 141.66 | 145.39 | 150,612 | 1340 | 0% 0% 0% 100% |
| 17 | C# Mono #2 | 194.23 | 194.81 | 524,652 | 1012 | 0% 0% 0% 100% |
| 19 | Lua | 221.06 | 221.05 | 600,988 | 601 | 0% 0% 0% 100% |
| 20 | Perl #2 | 225.09 | 228.97 | 780,228 | 359 | 0% 0% 0% 100% |
| 20 | Lua #2 | 231.17 | 231.16 | 684,924 | 613 | 0% 0% 0% 100% |
| 20 | Scheme PLT | 232.64 | 232.80 | 1,298,828 | 623 | 0% 0% 0% 100% |
| 21 | Perl | 243.28 | 243.53 | 2,827,104 | 648 | 0% 0% 1% 100% |
| 27 | Go 6g 8g | 5 min | 5 min | 379,480 | 874 | 0% 0% 0% 100% |
| 28 | Erlang HiPE #3 | 5 min | 5 min | 646,524 | 932 | 1% 10% 89% 1% |
| 29 | Python CPython #6 | 5 min | 5 min | 489,420 | 520 | 0% 0% 1% 100% |
| 30 | Erlang HiPE | 5 min | 5 min | 3,779,824 | 930 | 3% 92% 5% 3% |
| 35 | Python CPython #5 | 6 min | 6 min | 489,424 | 557 | 0% 0% 0% 100% |
| 37 | Lisp SBCL | 7 min | 7 min | 341,040 | 847 | 0% 0% 0% 100% |
| 38 | PHP #3 | 7 min | 7 min | 248,700 | 1268 | 0% 0% 0% 100% |
| 38 | JavaScript TraceMonkey | 7 min | 7 min | 1,057,344 | 423 | 0% 0% 0% 100% |
| 40 | PHP #2 | 7 min | 7 min | 248,704 | 914 | 0% 0% 0% 100% |
| 41 | Python CPython | 7 min | 7 min | 486,904 | 475 | 0% 0% 0% 100% |
| 43 | Ruby JRuby #2 | 8 min | 8 min | 515,084 | 420 | 0% 0% 0% 100% |
| 47 | JavaScript TraceMonkey #3 | 9 min | 9 min | 442,876 | 390 | 0% 0% 0% 100% |
| 75 | Ruby MRI #2 | 14 min | 14 min | 166,344 | 420 | 0% 0% 0% 100% |
| 77 | Java 6 -Xint #2 | 14 min | 14 min | 324,680 | 1602 | 0% 0% 0% 100% |
| 107 | Java 6 -Xint | 20 min | 20 min | 654,360 | 1330 | 0% 0% 0% 100% |
| 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 | ||||||
| 0.7 | C++ GNU g++ #5 | 7.68 | 7.68 | 50,496 | 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).