Timeline for Accelerating creation of matrices and finding ways for optimal scaling
Current License: CC BY-SA 4.0
6 events
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| Jul 1, 2021 at 19:31 | comment | added | G. Sliepen |
I didn't delve into the internals of Rccp, but could it be that Rccp::rbinom() returns dynamically allocated memory? That means a lot of new and delete behind the scenes.
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| Jul 1, 2021 at 11:48 | comment | added | Jonathan1234 |
And lastly, the most significant time reduction was given by std::bernoulli_distribution distrib(p) and I was wondering why?? I mean a random draw from a Bernoulli distribution seems already easy and fast to implement what additionally they do that makes it even faster?
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| Jul 1, 2021 at 11:47 | comment | added | Jonathan1234 |
Also, as you pointed out I changed the .submat which requires the use of a non optimal binomial version with a For Loop that goes exactly to the places where we want to conduct the trial
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| Jul 1, 2021 at 11:45 | comment | added | Jonathan1234 |
This is a really helpful answer, I did manage to reduce the computational time with those suggestions!! So, for the H.zeros(); because each row will have zeros on the first cells and last cells I think I would have to use 3 loops, one for the first zeros, for the ones in the middle and for the zeros in the end. What I did is instead of using arma::mat H(N,K) and H.zeros(); I used NumericMatrix H(N,K) which is much faster and initializes the matrix with zeros.
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| Jul 1, 2021 at 11:41 | vote | accept | Jonathan1234 | ||
| Jun 30, 2021 at 20:39 | history | answered | G. Sliepen | CC BY-SA 4.0 |