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-rwxr-xr-xTools/batchScripts/script_profiling_summit.sh48
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diff --git a/Tools/batchScripts/script_profiling_summit.sh b/Tools/batchScripts/script_profiling_summit.sh
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+#!/bin/bash
+#BSUB -P GEN109
+#BSUB -W 0:10
+#BSUB -nnodes 1
+#BSUB -J WarpX
+#BSUB -o WarpXo.%J
+#BSUB -e WarpXe.%J
+
+module load pgi
+module load cuda/9.1.85
+module list
+set -x
+
+omp=1
+export OMP_NUM_THREADS=${omp}
+#EXE="../main3d.pgi.DEBUG.TPROF.MPI.ACC.CUDA.ex"
+EXE="../main3d.pgi.TPROF.MPI.ACC.CUDA.ex"
+#JSRUN="jsrun -n 4 -a 1 -g 1 -c 1 --bind=packed:${omp} "
+#JSRUN="jsrun -n 1 -a 4 -g 4 -c 4 --bind=packed:${omp} "
+JSRUN="jsrun -n 1 -a 1 -g 1 -c 1 --bind=packed:${omp} "
+
+rundir="${LSB_JOBNAME}-${LSB_JOBID}"
+mkdir $rundir
+cp $0 $rundir
+cp inputs $rundir
+cd $rundir
+
+# 1. Run normally
+${JSRUN} --smpiargs="-gpu" ${EXE} inputs
+
+# 2. Run under cuda-memcheck
+# ${JSRUN} --smpiargs="-gpu" cuda-memcheck ${EXE} inputs &> memcheck.txt
+
+# 3. Run under nvprof and direct all stdout and stderr to nvprof.txt
+#${JSRUN} --smpiargs="-gpu" nvprof --profile-child-processes ${EXE} inputs &> nvprof.txt
+
+# 4. Run under nvprof and store performance data in a nvvp file
+# Can be converted to text using nvprof -i nvprof-timeline-%p.nvvp
+#${JSRUN} --smpiargs="-gpu" nvprof --profile-child-processes -o nvprof-timeline-%p.nvvp ${EXE} inputs
+
+# COLLECT PERFORMANCE METRICS - THIS IS MUCH SLOWER. Set nsteps=2 in the inputs files
+# 5. Run under nvprof and collect metrics for a subset of kernels
+#${JSRUN} --smpiargs="-gpu" nvprof --profile-child-processes --kernels '(deposit_current|gather_\w+_field|push_\w+_boris)' --analysis-metrics -o nvprof-metrics-kernel-%p.nvvp ${EXE} inputs
+
+# 6. Run under nvprof and collect metrics for all kernels -- much slower!
+#${JSRUN} --smpiargs="-gpu" nvprof --profile-child-processes --analysis-metrics -o nvprof-metrics-%p.nvvp ${EXE} inputs
+
+cp ../WarpX*.${LSB_JOBID} .
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