Re: st: how to make stata run faster

[George Vega Yon <g.vegayon@gmail.com>]

Dear Eduardo,

One way to speedup computations without buying StataMP can by through
the module "parallel" ideas.repec.org/c/boc/bocode/s457527.html
(which I'll show at Stata Conference in New Orleans). The next version
of the module (which will be soon release) will include a set of tools
for use parallel within MATA. That said, you'll be able to efficiently
rewrite algorithms in such a way to take advantage of multicore CPUs.

As a way to promote my module, I've started rewriting some particulary
slow algorithms. For instance, in the next weeks I'll release
"nnmatch2", a new version of nearest neighbour matching (nnmatch)
implemented in mata + parallel computing. The MATA implementation have
speedup the algorithm in around 10 times; and the parallel part will
(at least) double that number (if you have a dual core computer...).

If you are up to, we can evaluate rewriting a part of Stata's "arima"
and see where does this leads us.

Please let me know,

Best wishes,

George


George Vega Yon
7 647 2552
http://cl.linkedin.com/in/georgevegayon


2013/5/21 Darren White <darrenm.white@health.qld.gov.au>:
> Hi
>
> STATA MP (multi processor) has optimised processing for many STATA computations/ routines.
>
> I recently upgraded and it is very quick.
>
> Darren
>
>>>> "JVerkuilen (Gmail)" <jvverkuilen@gmail.com> 5/21/2013 2:39 pm >>>
> You should indicate what version of Stata and the specifications of
> the platform. The answer might well be "get a better computer." ;)
>
> On Mon, May 20, 2013 at 4:09 PM, Eduardo de Masi <edu_masi@yahoo.com.br> wrote:
>>
>>
>> Dear,
>>
>> Please,
>>
>> I'm running a transfer function with ARIMA errors (Arimax) in STATA and processing is very slow, is taking three to four hours. My database has 626 observation and my model has five variables, and their lags. What can I do to Stata run faster?
>> I have the following memory allocated:
>>
>> Current memory allocation is:
>>
>> current                                 memory usage
>> settable          value     description                 (1M = 1024k)
>> --------------------------------------------------------------------
>> set maxvar         5000     max. variables allowed           1.909M
>> set memory       200M    max. data space                      200.000M
>> set matsize        5000     max. RHS vars in models        191.154M
>> -----------
>> 393.063M
>>
>> Thanks,
>> Eduardo de Masi
>> PhD student in Sciences
>>
>>
>> *
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>
>
>
> --
> JVVerkuilen, PhD
> jvverkuilen@gmail.com
>
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