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= Usage =
To make a binary use our custom installation of the GNU C Library, we need to
make sure the modern version of the dynamic linker is used, with the location
of the modern C Library at the front of the dynamic library load path.
For example:
exec /projects/nlpl/software/glibc/2.18/lib/ \
  --library-path /projects/nlpl/software/glibc/2.18/lib:${LD_LIBRARY_PATH} \
  /projects/nlpl/software/tensorflow/1.11/bin/.python3.5 "$@"
We should generalize the above a little more, i.e. make the script determine
the actual binary to be invoked as a function of <tt>$0</tt>.

Revision as of 21:53, 19 September 2018


The operating system on Abel dates back to the original year of installation (2012, for all we recall). While many development tools and libraries are available in newer versions (through the module system), the version of the basic GNU C Library is intricately linked to the Linux kernel. Some packages that are distributed in pre-compiled form (typically as Python wheels) require more recent versions of the C Library. A little bit of trickery makes it possible to get these binaries to execute on Abel, using a custom, NLPL-specific installation of the GNU C Library and its dynamic linker.


tar jpSxf glibc-2.18.tar.bz2
cd glibc-2.18
mkdir build
cd build
module purge
module load gcc/4.9.2 cuda/8.0
../configure --prefix=/projects/nlpl/software/glibc/2.18
make -j 8
make install
make localedata/install-locales
ln -s /usr/share/zoneinfo/Europe/Oslo /projects/nlpl/software/glibc/2.18/etc/localtime

To pre-configure the custom dynamic linker, allowing it to make use of ‘standard’ library locations that need not be on $LD_LIBRARY_PATH. In mid-September 2018, at least, basic CUDA libraries appear to be installed into /usr/lib64/, but only on GPU-enabled compute nodes.

qlogin --account=nn9106k --time=6:00:00 --partition=accel --gres=gpu:1
cp -pr /etc/* /projects/nlpl/software/glibc/2.18/etc
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