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GPU profiling with rocprof

In this exercise we examine performance behaviour of multi-GPU program with rocprof. As a a test program you can use the heat-equation in the Multiple GPU hands-on.

rocprof is standard command line profiler included in rocm installation, which can produce both a flat profile, and a trace of GPU kernels and HIP API calls. rocprof does not profile any CPU code or MPI calls, just GPU functions.

In order to use rocprof no recompilation is needed, it is enough to start the application with rocprof. As rocprof has no knowledge about MPI, for multi-GPU programs one typically needs launch rocprof via wrapper script, so that output from different MPI processes is written to different files.

  1. You can work with existing build of heat-equation. For profiling, you can update the batch job script as follows:

    #SBATCH ...

cat << EOF > rocprof_wrapper.sh
#!/bin/bash

exec rocprof --hip-trace -o results_\${SLURM_PROCID}.csv \$*
EOF

chmod +x ./rocprof_wrapper.sh
srun ./rocprof_wrapper.sh ./heat_offload
rm -f ./rocprof_wrapper.sh

    After run you should have a set of "results_x" files. "results_0.stats.csv" contains the flat profile of process 0, and "results_0.json" the trace for process 0. Traces can be investigated with web browser:

    • Download the trace file(s) (e.g. "results_0.json") to your laptop
    • Go with a browser (chrome recommended, firefox should also work) to https://ui.perfetto.dev/
    • Open the trace file. You see the list of perfetto controls by typing ?

    Try to compare traces for cases both with and without GPU aware MPI. (You can provide different base filename for the two cases and open them e.g. to two tabs/windows