Dear Riccardo and Allin,

Huge thanks to you all! Your enhancements boosted the performance more than threefold! See for yourself: performance comparison of the initial version (AK), Riccardo’s one (RL), Allin’s one (AC) and the final version with the slight improvement (ACRL); measured in results per second (more = better). Tested in 5 runs under Windows and Linux (Debian) on a good modern (AMD FX-6200) and a bad obsolete system (Atom M270).

Perf     AK     RL     AC   ACRL
LnxGood 437 1346   2329   2483
WinGood 336   783    967   1026
LnxBad    49   168    347    381
WinBad    43   106    137    146

Might be interesting for you how those extra commands influenced the performance (extra kudos to Linux).

With great appreciation,

Andreï.

2014-03-12 21:15 GMT+04:00 Allin Cottrell <cottrell@wfu.edu>:

On Wed, 12 Mar 2014, Riccardo (Jack) Lucchetti wrote:

> On Wed, 12 Mar 2014, Allin Cottrell wrote:
>
>> This is the fastest version I can come up with on a quick go (if one
>> doesn't mind having the result as a matrix):
>>
>> <hansl>
>> set stopwatch
>> scalar T = 10000
>> matrix y = zeros(T,1)
>> scalar iters=10000
>> matrix DFT = zeros(iters,1)
>>
>> loop i=1..iters --quiet
>> y = cum(mnormal(T, 1))
>> DFT[i] = (T-2) * (mols(y[3:],mlag(y,1)[3:])-1)
>> endloop
>> mwrite(DFT, "DFT.mat")
>> printf "Time taken: %f seconds\n", $stopwatch
>> </hansl>
>
> Slight improvement:
>
> <hansl>
> loop i=1..iters --quiet
> y = cum(mnormal(T, 1))
> DFT[i] = (T-2) * (mols(y[3:],y[2:T-1])-1)
> endloop
> </hansl>

How did I miss that trick ;-)

Allin
_______________________________________________
Gretl-users mailing list
Gretl-users@lists.wfu.edu
http://lists.wfu.edu/mailman/listinfo/gretl-users