From caba9647b9c06132b3e64f3428bd5f11c90d2be6 Mon Sep 17 00:00:00 2001
From: Youngdae Kim <youngdae@anl.gov>
Date: Fri, 4 Jun 2021 23:40:56 -0500
Subject: [PATCH] deletes unnecessary scripts.

---
 figure5.sh | 32 --------------------------------
 figure6.sh | 36 ------------------------------------
 figure8.sh | 32 --------------------------------
 3 files changed, 100 deletions(-)
 delete mode 100755 figure5.sh
 delete mode 100755 figure6.sh
 delete mode 100755 figure8.sh

diff --git a/figure5.sh b/figure5.sh
deleted file mode 100755
index 3125bb2..0000000
--- a/figure5.sh
+++ /dev/null
@@ -1,32 +0,0 @@
-#!/bin/bash
-#
-# This script describes how to reproduce the results of Figure 5.
-# This is just an example for iillustration purposes. Different platforms
-# (such as Summit cluster) may require different setups.
-#
-# For each run of admm_standalone.jl, it will generate iteration logs
-# and timing results. The relevant timing results for Figure 5 are printed
-# at the end of its run and will be the following:
-#
-#   Branch/iter = %.2f (millisecs)
-#
-# The above timing results were used for Figure 5.
-#
-# Prerequisite:
-#  - CUDA library files should be accessible before executing this script,
-#    e.g., module load cuda/10.2.89.
-#  - CUDA aware MPI should be available.
-
-export JULIA_CUDA_VERBOSE=1
-export JULIA_MPI_BINARY="system"
-
-DATA=("case2868rte" "case6515rte" "case9241pegase" "case13659pegase" "case19402_goc")
-PQ=(10 20 50 50 500)
-VA=(1000 2000 5000 5000 50000)
-ITER=(6000 15000 35000 45000 30000)
-
-for i in ${!DATA[@]}; do
-    echo "Solving ${DATA[$i]} . . ."
-    julia --project ./src/admm_standalone.jl "./data/${DATA[$i]}" ${PQ[$i]} ${VA[$i]} ${ITER[$i]} true > output_gpu1_${DATA[$i]}.txt 2>&1
-done
-
diff --git a/figure6.sh b/figure6.sh
deleted file mode 100755
index 182fae0..0000000
--- a/figure6.sh
+++ /dev/null
@@ -1,36 +0,0 @@
-#!/bin/bash
-#
-# This script describes how to reproduce the results of Figure 6.
-# This is just an example for iillustration purposes. Different platforms
-# (such as Summit cluster) may require different setups.
-#
-# For each run of launch_mpi.jl, it will generate iteration logs
-# and timing results. The relevant timing results for Figure 6 are printed
-# at the end of its run and will be the following:
-#
-#   (Br+MPI)/iter = %.2f (millisecs)
-#
-# We divide the above timing results by the timing results obtained when
-# we use a single GPU.
-#
-# Prerequisite:
-#  - CUDA library files should be accessible before executing this script,
-#    e.g., module load cuda/10.2.89.
-#  - CUDA aware MPI should be available.
-
-export JULIA_CUDA_VERBOSE=1
-export JULIA_MPI_BINARY="system"
-
-DATA=("case2868rte" "case6515rte" "case9241pegase" "case13659pegase" "case19402_goc")
-PQ=(10 20 50 50 500)
-VA=(1000 2000 5000 5000 50000)
-ITER=(5648 13651 30927 41126 28358)
-NGPU=(2 3 4 5 6)
-
-for j in ${!NGPU[@]}; do
-    for i in ${!DATA[@]}; do
-        echo "Solving ${DATA[$i]} using ${NGPU[$j]} GPUs . . ."
-        mpirun -np ${NGPU[$j]} julia --project ./src/launch_mpi.jl "./data/${DATA[$i]}" ${PQ[$i]} ${VA[$i]} ${ITER[$i]} true > output_gpu${NGPU[$j]}_${DATA[$i]}.txt 2>&1
-        mv br_time_gpu.txt br_time_gpu${NGPU[$j]}_${DATA[$i]}.txt
-	done
-done
diff --git a/figure8.sh b/figure8.sh
deleted file mode 100755
index 2fa71ca..0000000
--- a/figure8.sh
+++ /dev/null
@@ -1,32 +0,0 @@
-#!/bin/bash
-#
-# This script describes how to reproduce the results of Figure 8.
-# This is just an example for iillustration purposes. Different platforms
-# (such as Summit cluster) may require different setups.
-#
-# For each run of launch_mpi.jl, it will generate iteration logs
-# and timing results. The relevant timing results for Figure 8 are printed
-# at the end of its run and will be the following:
-#
-#   (Br+MPI)/iter = %.2f (millisecs)
-#
-# We use these numbers for the timings of 40 CPU cores and use the timings
-# from Figure 6 for 6 GPUs.
-#
-# Prerequisite:
-#  - CUDA library files should be accessible before executing this script,
-#    e.g., module load cuda/10.2.89.
-#  - CUDA aware MPI should be available.
-
-export JULIA_CUDA_VERBOSE=1
-export JULIA_MPI_BINARY="system"
-
-DATA=("case2868rte" "case6515rte" "case9241pegase" "case13659pegase" "case19402_goc")
-PQ=(10 20 50 50 500)
-VA=(1000 2000 5000 5000 50000)
-ITER=(5718 13640 30932 41140 28358)
-
-for i in ${!DATA[@]}; do
-    echo "Solving ${DATA[$i]} using 40 CPU cores . . ."
-    mpirun -np 40 julia --project ./src/launch_mpi.jl "./data/${DATA[$i]}" ${PQ[$i]} ${VA[$i]} ${ITER[$i]} false > output_cpu40_${DATA[$i]}.txt 2>&1
-done