Shell script and slurm file.

fast/gpu.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+
+# Slurm job options (job-name, compute nodes, job time)
+#SBATCH --job-name=Devito_GPU
+#SBATCH --time=00:15:00
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1
+#SBATCH --gpus-per-task=1
+
+# Replace [budget code] below with your project code (e.g. t01)
+#SBATCH --account=d011
+#SBATCH --partition=gpu
+#SBATCH --qos=short
+#SBATCH -o ./jobs-output/gpu.%j.out # STDOUT
+
+# Propagate the cpus-per-task setting from script to srun commands
+#    By default, Slurm does not propagate this setting from the sbatch
+#    options to srun commands in the job script. If this is not done,
+#    process/thread pinning may be incorrect leading to poor performance
+export SRUN_CPUS_PER_TASK=$SLURM_CPUS_PER_TASK
+
+# Simple script to run single threaded benchmarks locally,
+# for simple sanity checks.
+
+# Use the cray compiler, if available.
+export DEVITO_PLATFORM=nvidiaX
+# Enable debug logging.
+export DEVITO_LOGGING=BENCH
+
+# Just extract the reported throughput from the whole output of the passed command
+# For GPU computing, we currently measure only the compute part
+# That is, we exclude the data copying to and from the device.
+get_throughput() {
+    #echo $($@)
+    $@ |& grep section0 | head -n 1 | cut -d ' ' -f10
+}
+
+# Iterate over benchmarks and cases, print simple CSV data to stdout
+# Copy-pastes nicely in Google Sheets
+echo bench_name,so,Devito,xDSL
+for bench in "wave2d_b.py -d 1024 1024 --nt 1024" "wave3d_b.py -d 512 512 512 --nt 512" "diffusion_2D_wBCs.py -d 8192 8192 --nt 1024" "diffusion_3D_wBCs.py -d 512 512 512 --nt 512"
+# for bench in "wave2d_b.py -d 8192 8192 --nt 1024" "diffusion_2D_wBCs.py -d 8192 8192 --nt 1024"
+do
+  # Get the benchmark file for printing
+  bench_name=$(echo $bench | cut -d ' ' -f1)
+  # Iterate over measured space orders
+  for so in 2 4 8
+    do
+      # Get the throughputs
+      devito_time=$(get_throughput srun python $bench -so $so --devito 1)
+      xdsl_time=$(get_throughput srun python $bench -so $so --xdsl 1)
+      # print CSV line
+      echo $bench_name,$so,$devito_time,$xdsl_time
+  done
+done

fast/slurm-jobs/gpu.slurm

@@ -0,0 +1,36 @@
+#!/bin/bash
+
+# Simple script to run single threaded benchmarks locally,
+# for simple sanity checks.
+
+# Use the cray compiler, if available.
+export DEVITO_PLATFORM=nvidiaX
+# Enable debug logging.
+export DEVITO_LOGGING=BENCH
+
+# Just extract the reported throughput from the whole output of the passed command
+# For GPU computing, we currently measure only the compute part
+# That is, we exclude the data copying to and from the device.
+get_throughput() {
+    #echo $($@)
+    $@ |& grep section0 | head -n 1 | cut -d ' ' -f10
+}
+
+# Iterate over benchmarks and cases, print simple CSV data to stdout
+# Copy-pastes nicely in Google Sheets
+echo bench_name,so,Devito,xDSL
+for bench in "wave2d_b.py -d 1024 1024 --nt 1024" "wave3d_b.py -d 512 512 512 --nt 512" "diffusion_2D_wBCs.py -d 8192 8192 --nt 1024" "diffusion_3D_wBCs.py -d 512 512 512 --nt 512"
+# for bench in "wave2d_b.py -d 8192 8192 --nt 1024" "diffusion_2D_wBCs.py -d 8192 8192 --nt 1024"
+do
+  # Get the benchmark file for printing
+  bench_name=$(echo $bench | cut -d ' ' -f1)
+  # Iterate over measured space orders
+  for so in 2 4 8
+    do
+      # Get the throughputs
+      devito_time=$(get_throughput python $bench -so $so --devito 1)
+      xdsl_time=$(get_throughput python $bench -so $so --xdsl 1)
+      # print CSV line
+      echo $bench_name,$so,$devito_time,$xdsl_time
+  done
+done