Timeline for Basic software libraries for numerical analysis using modern programming languages?
Current License: CC BY-SA 2.5
4 events
| when toggle format | what | by | license | comment | |
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| Jul 19, 2012 at 2:17 | history | made wiki | Post Made Community Wiki by S. Carnahan♦ | ||
| Oct 15, 2010 at 7:58 | comment | added | Neel Krishnaswami | F# is a very nice language. However, it plays in the same space as Java or C#: it offers excellent bindings to platform linear algebra packages (such as BLAS) and the base language is fast enough that statistical programs that have significant non-matrix components will run acceptably fast. Actually writing the matrix code itself in it won't work well. (Compare this with R, Matlab, or Numpy, where the non-matrix part of the language is hopelessly slow. This sucks for (eg) robust statistics, where algorithms often do many small matrix ops, rather than a few big ones.) | |
| Oct 13, 2010 at 10:56 | comment | added | Tim van Beek | Thanks! Never heard of those...F# is sometimes marketed as exactly the kind of thing as SAC, as you describe it, which is why I wanted to know that the professionals think about it :-) | |
| Oct 13, 2010 at 9:35 | history | answered | Neel Krishnaswami | CC BY-SA 2.5 |