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Running the scripts


../../ -c linux -m gcc -r -n 16 -p 16

where -n 16 is the total number of processors and -p 16 is the number of processors per node. Note that (and, which uses requires a power of 2 for the number of processors.

Multiple processor configuration can be run with:

../../ -c linux -m gcc -r -n "16 32 64" -p "16 32 64"

Post-processing the results

First, save the output of the run to a file:

../../ -c linux -m gcc -r -n 16 -p 16 > run_001.txt

and then use one of the postprocess-plot-*.py scripts (which require the python package matplotlib) or the script, e.g.:

python run_001.txt

Note that the postprocess-*.py scripts can read multiple files at a time just by listing them on the command line and also read the standard input if no files were specified on the command line.

Plotting performance comparisons

The script can be used to plot the performance ratios between two sets of data, e.g. vector (BP2) vs scalar (BP1), or two compilers: XLC vs GCC. Sample usage:

python bp1_gcc_n16.txt bp2a_gcc_n16.txt
python bp1_gcc_n16.txt bp1_xlc_n16.txt
python bp1_gcc_n16.txt bp3_gcc_n16.txt