Hi Yan,
thank you very much for your comment. I read now the section 6 of the parallel
package documentation.
It's better to give programming a little more time than to get at the end
undefined behavior. At this point only a short question: I use the nlopt
library, constructing in every thread an nlopt::opt object. That should be
thread-safe right as I have an object for every thread (the void data pointer
is constructed in every thread and it is not shared)?
Best
Simon
On Feb 14, 2013, at 11:24 PM, Yan Zhou <zhou...@me.com> wrote:
> It runs in parallel does not mean it works correctly.
>
> Simply increase seed certainly not avoid overlapping. The best algorithm that
> use MT19937 in parallel environment without overlapping has a complexity
> O(log n) AFAIK.
>
> Second, R's RNG has a single instance within the whole program, which means
> your program does not work as you thought. There are obvious race conditions
> in your approach.
>
> I suggest you google a little bit of how RNG really works before purse how to
> generate them in parallel. For example section 6 of the R's parallel
> package's document.
>
> Best,
>
> Yan Zhou
>
> On Feb 14, 2013, at 09:40 PM, Simon Zehnder <szehn...@uni-bonn.de> wrote:
>
>> Well, in OpenMP it seems to work, if I use inside the #pragma parallel for:
>>
>> Rcpp::Environment base("package:base");
>> Rcpp::Function SetSeed = base["set.seed"];
>> SetSeed(1 + i * nobs_intern * 3);
>>
>> I used OMP_NUMTHREADS = 4 and 8 iterations.
>>
>> Best Simon
>>
>> On Feb 14, 2013, at 10:10 PM, Simon Zehnder <szehn...@uni-bonn.de> wrote:
>>
>> > I made all my simple tests now by using Rcpp::Environment and then
>> > Rcpp::Function for "set.seed" when calling R::rnorm. The next step would
>> > be to parallelize the iterations via OpenMP. The suggestion of Yan makes
>> > quite sense to produce a RNG via std::mt19937. This is also the way I did
>> > it when I used Scythe Statistical Library.
>> > As I use now the R RNG it should be able to use it in parallel, if
>> > Rcpp::Function is a kind of wrapper which contains the code of "set.seed".
>> > But I would rather guess, that it is a call object, that just calls the R
>> > function "set.seed" in R, which then would not be threadsafe (as also the
>> > RNG would then just be called when using R::rnorm).....
>> >
>> > So I guess falling back to std::mt19937 is not a bad idea. For no
>> > overlapping I just increase the seed in every iteration dependent on the
>> > iteration and the number of random numbers to generate.
>> >
>> > Best Simon
>> >
>> >
>> >
>> >
>> > On Feb 11, 2013, at 2:16 PM, Chris Jefferson <ch...@bubblescope.net> wrote:
>> >
>> >> On 11/02/13 10:23, c s wrote:
>> >>> On Sun, Feb 10, 2013 at 12:32 AM, Yan Zhou <zhou...@me.com> wrote:
>> >>>> To have Armadillo randn use MT19937 is not easy.
>> >>>> Since it use srand() for seed, I guess it also use C rand(),
>> >>>> whose quality is quite questionable.
>> >>> The quality of the rand() function from C depends on the
>> >>> implementation in libc, which varies from system to system.
>> >>>
>> >>> While I'd like to incorporate a Mersenne-Twister random number
>> >>> generator directly in Armadillo, it would either add a dependency on
>> >>> Boost, or on C++11. Boost might not be available on a user's system,
>> >>> and the degree of support for C++11 features varies from compiler to
>> >>> compiler. We also have to bear in mind that R folks currently
>> >>> disallow CRAN packages that use C++11.
>> >>
>> >> If you just want a mersenne-twister random number generator, I will
>> >> extract it from boost (which is under a fairly free licence).
>> >>
>> >> Chris
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