Within a Julia shell install BenchmarkTools and NCDatasets using these julia commands:

using Pkg
Pkg.add(["BenchmarkTools","NCDatasets"])

Install the python packages netCDF4 and numpy using this shell command:

pip install netCDF4 numpy

Within a R shell install microbenchmark and ncdf4 using these R commands:

install.packages("microbenchmark")
install.packages("ncdf4")

These are the steps to run the benchmark:

• Prepare the file filename_fv.nc with:

julia generate_data.jl

• Run the shell script benchmark.sh.

./benchmark.sh

The script will output a markdown table with the benchmark statistics.

The operating systems typically caches access to the file system. To make these benchmarks more realistic, the file system caches can be dropped at every iteration using the benchmark script with the option --drop-caches so that the disk IO is included in the reported run times. On Linux, the caches are dropped by writing 3 to the file /proc/sys/vm/drop_caches however this requires super user privileges. In this case, these benchmarks require a Linux operating system (as dropping file caches is OS-specific).

• As a root user, run the shell script benchmark.sh. It is necessary that the root user has access to the Julia, python and R netCDF packages (NCDatasets, netCDF4 and ncdf4 respectively).

./benchmark.sh --drop-caches

If all packages are installed in the home directory of an unpriviledges user e.g. my_user_name, they can be made available to the root user changing temporarily the HOME environement variable to /home/my_user_name in the root shell before running ./benchmark.sh:

HOME=/home/my_user_name ./benchmark.sh --drop-caches

The table in the README file are obtained with this option enabled.