OpenMP support for TMB on Mac


Up to Mac Catalina, by default, installing R packages with OpenMP support (e.g. data.table, TMB) has been compiled without it.

For TMB codes, changes such as

  • use parallel_accumulator() or
  • include OpenMP’s headers and library, and
  • add #pragma openmp parallel for before for loop in the likelihood calculation

done after installing TMB from CRAN are not relevant – TMB was already compiled with _OPENMP flag undefined. This can be checked by running TMB::openmp() which outputs

OpenMP not supported.

or library(data.table) which outputs

…This installation of data.table has not detected OpenMP support. It should still work but in single-threaded mode. This is a Mac.


it works on my machine

The following steps are one way to make them work:

Important: this release uses Xcode 10.1 and GNU Fortran 8.2. If you wish to compile R packages from sources, you will need to download and GNU Fortran 8.2 - see the tools directory.

although the note’s clearly missing a word after “download”, should it be Clang? I assume it is.

Then for TMB

  • change the Makevars
# in terminal
touch ~/.R/Makevars
open ~/.R/Makevars


MY_LOC   =  /usr/local/clang8
CML_LOC  =  /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk
CC       =  $(MY_LOC)/bin/clang -fopenmp -isysroot $(CML_LOC)
CXX      =  $(MY_LOC)/bin/clang++ -fopenmp -isysroot $(CML_LOC)
  CFLAGS = -g -O3 -Wall -pedantic -std=gnu99 -mtune=native -pipe
CXXFLAGS = -g -O3 -Wall -pedantic -std=c++11 -mtune=native -pipe
LDFLAGS  = -L$(MY_LOC)/lib -Wl,-rpath,$(MY_LOC)/lib
git clone ~/adcomp
  • open a new R session, remove TMB if it is already installed and compile TMB locally, e.g. with devtools
[1] 8

The number of threads is now 8 (total cores on this Mac).

You might want to keep the Makevars as it is, and if a package failed to install afterwards it is most likely that that package has not included a check for _OPENMP flag. In this case, what a user can do is removing the -fopenmp flag in the Makevars above and notify the package’s owners.


We can run the linreg_parallel example to see if things speed up (noting that we are using the same Makevars but TMB does have a check for _OPENMP flag in parallel_accumulator code.)

> TMB::openmp()
[1] 0
Warning message:
In TMB::openmp() : OpenMP not supported.
v1 = microbenchmark::microbenchmark(TMB::runExample("linreg_parallel"))
> v1
Unit: milliseconds
                               expr      min       lq     mean  median       uq
 TMB::runExample("linreg_parallel") 189.8356 206.6781 460.8431 215.181 221.8238
      max neval
 24590.55   100

new R session

> TMB::openmp()
[1] 8
> v2 = microbenchmark::microbenchmark(TMB::runExample("linreg_parallel"))
> v2
Unit: milliseconds
                               expr      min       lq     mean   median
 TMB::runExample("linreg_parallel") 183.2058 200.7899 452.8837 211.5193
       uq      max neval
 222.3681 23842.13   100

Hmm, no improvement?