Comments (2)
I fear that is between you and your RHEL machine as CRAN is happy (and has generally been):
Same of course on, say, my local box (running standard Ubuntu):
edd@rob:~$ ldd /usr/local/lib/R/site-library/RcppZiggurat/libs/RcppZiggurat.so | grep gsl
libgsl.so.23 => /usr/lib/x86_64-linux-gnu/libgsl.so.23 (0x00007fa8fed3f000)
libgslcblas.so.0 => /usr/lib/x86_64-linux-gnu/libgslcblas.so.0 (0x00007fa8fe314000)
edd@rob:~$ dpkg -S /usr/lib/x86_64-linux-gnu/libgsl.so.23
libgsl23:amd64: /usr/lib/x86_64-linux-gnu/libgsl.so.23
edd@rob:~$
i.e. the standard GSL shared library from the standard GSL package (I happen to be the Debian maintainer for it too) is used.
It really only affects an example, so you could take the scissors to the package and #ifdef
out the GSL use.
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And Crossposted to StackOverflow which seems to indicate you did not set up your parallel code right. I think Rui is correct and you need to register the cluster.
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Related Issues (13)
- Not an issue but a request HOT 6
- Setting a seed to value of getSeed() doesn't produce expected draws HOT 11
- rcppziggurat installation fails on linux HOT 15
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- Compilation failure HOT 1
- Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared object '/usr/lib/R/library/RcppGSL/libs/RcppGSL.so': libgsl.so.23: cannot open shared object file: No such file or directory HOT 3
- Missing dependency libgsl.so HOT 6
- libgsl.so.27 not found for GSL local installation HOT 14
- Setting a seed only works when naming a preferred generator
- Use .Random.seed HOT 1
- demos throw errors Windows HOT 1
- R integration HOT 6
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