A J model of the QR decomposition can be found in
http://code.jsoftware.com/wiki/Essays/QR_Decomposition

> He builded better than he knew: it relies on +/ .* for most of the
numeric work.

(Ahem) actually I knew.  It was part of my M.Sc. thesis and is another
lemma which shows that %.x has the same order of complexity as +/ .* , at
the time O(n*2^.7) (better than the conventional O(n*3)), now down to
O(n*2.3728639) according to Wikipedia.  The algorithm is also good answer
to claims that QR and other matrix decompositions are inherently loopy.
See Hui & Iverson, _A Note on Programming Style_, Vector, volume 12, number
13, 1996-01.





On Sun, Sep 8, 2019 at 1:14 PM Henry Rich <henryhr...@gmail.com> wrote:

> For years Joey Tuttle has used the performance of (%. y) as a simple
> measure of the performance of J releases.  It has improved pretty steadily.
>
> This surprised me, because I know where the gaussian-elimination code
> is, and that code doesn't do much except C loops that do add and
> subtract.  I didn't see how improvements to the JE would have any effect
> on (%. y).  Not wanting to mess up a good story, I kept my doubts to
> myself.
>
> Finally I understand.  The code I had been looking at is used only for
> rational matrices.  The code for general (%. y) is a lovely little
> recursive QR decomposition that does lots of memory allocation and calls
> to internal J arithmetic functions.  In fact, it's a pretty good
> exercise of the computational side of the system.  It's quite short but
> uses general utilities so that it works on all fixed-precision numeric
> types.  Bravo to Roger.  He builded better than he knew: it relies on +/
> . * for most of the numeric work, and that code has now been polished so
> well that it is the most efficient code in the system.
>
> Long live Joey's benchmark!
>
> Henry Rich
>
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