Comments (3)
RcppArmadillo is header-only (apart from the example / illustration that is fastLm()
) so it is up to your package to organize its compiler flags.
The default configuration we set in the RcppArmadillo headers in order to wrap and set up for R use should not get in the way. If you find otherwise, let us know!
Demos with SIMD turned on would be welcome, this may make for a nice post at the Rcpp Gallery. Maybe you can write something up?
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I had a similar hunch based on the work we have done with RcppSimdJson (which is crazy fast thanks to really well engineered code inside). But it does not require 'magic switches' -- the modern compiler mostly know already. So yes: -O2 or -O3 coupled with -march=native will (on suitable modern hardware) already all that is there and the package should not leave anything behind. Which, I think, your tests confirmed. So closing this.
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Related Issues (20)
- Fails to compile vs HOT 3
- package compilation failure HOT 20
- Two failures in test_cube.R on PowerPC HOT 33
- Armadillo 12.0.0 regressions HOT 2
- `RCPP_ARMADILLO_RETURN_ANYVEC_AS_VECTOR` in an R package? HOT 2
- using namespace arma; HOT 1
- Issue on call by reference with a NA matrix HOT 1
- Update indMatrix->arma::SpMat and pMatrix->arma::SpMat for Matrix 1.5-5 HOT 2
- install issue HOT 3
- [DOCS] - Review DESCRIPTION's Date HOT 2
- Failed to install RcppArmadillo on Linux Hyper Cluster HOT 4
- compilation on fedora39 raise error: cannot run C++ compiled programs HOT 6
- Install issue HOT 10
- Platform dependent output for sample()? HOT 9
- RcppArmadillo not available for R 4.3.2 + compilation errors HOT 14
- arma::randu incorrect output HOT 14
- Remove stale C++11 compilation standard setter in plugin HOT 1
- Rcpp required version might need updating? HOT 1
- Preparing for Armadillo 14.0.0 HOT 24
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