diff --git a/examples/pi.slurm b/examples/diffusion.slurm
similarity index 80%
copy from examples/pi.slurm
copy to examples/diffusion.slurm
index 7fa09d8..61b5969 100644
--- a/examples/pi.slurm
+++ b/examples/diffusion.slurm
@@ -1,43 +1,48 @@
 #!/bin/bash
-# author: gilles foureste (EPFL)
+# author: gilles fourestey (EPFL)
 #
 #SBATCH --nodes=2
 #  ntasks per node MUST be one, because multiple slaves per work doesn't
 #  work well with slurm + spark in this script (they would need increasing
 #  ports among other things)
 #SBATCH --ntasks-per-node=1
 #SBATCH --cpus-per-task=24
 #SBATCH --mem=8192
 #  Beware! $HOME will not be expanded and invalid paths will result Slurm jobs
 #  hanging indefinitely with status CG (completing) when calling scancel!
-##SBATCH --time=96:00:00
+#SBATCH --time=00:30:00
 #SBATCH --partition=scitas
-#SBATCH --qos=scitas
 #set -x
 #
+
+module load spark/2.0.2
+
+### modify the path to your scripts directory
+export PATH=/home/rezzonic/scitas_sparkservice/scripts:$PATH
+### end modif
+
+
 echo "---- starting $0 on $HOSTNAME"
 echo
 #
 MASTER_NODE=""
 start-spark.sh
 echo "configuration done..."
 set -x
 #
 #echo $MASTER_NODE
 #echo $MASTER
 #
 #MASTER_IP=$(cat ./sparklogs_${SLURM_JOBID}/spark_master)
 MASTER_IP=$(cat ${SLURM_JOBID}_spark_master)
 #
 echo $MASTER_IP
 time time spark-submit \
 --executor-memory 5G \
 --master $MASTER_IP \
 ./diffusion.py
 #
 stop-spark.sh
-#scancel -u foureste
-#spark-submit --master $MASTER  ./pi.py
 
 
 
diff --git a/examples/pi.slurm b/examples/pi.slurm
index 7fa09d8..f08df34 100644
--- a/examples/pi.slurm
+++ b/examples/pi.slurm
@@ -1,43 +1,48 @@
 #!/bin/bash
-# author: gilles foureste (EPFL)
 #
 #SBATCH --nodes=2
 #  ntasks per node MUST be one, because multiple slaves per work doesn't
 #  work well with slurm + spark in this script (they would need increasing
 #  ports among other things)
 #SBATCH --ntasks-per-node=1
 #SBATCH --cpus-per-task=24
 #SBATCH --mem=8192
 #  Beware! $HOME will not be expanded and invalid paths will result Slurm jobs
 #  hanging indefinitely with status CG (completing) when calling scancel!
-##SBATCH --time=96:00:00
+#SBATCH --time=00:30:00
 #SBATCH --partition=scitas
-#SBATCH --qos=scitas
 #set -x
 #
+
+module load spark/2.0.2
+
+### modify here with correct path to scripts directory
+export PATH=/home/rezzonic/scitas_sparkservice/scripts:$PATH
+### end modify
+
 echo "---- starting $0 on $HOSTNAME"
 echo
 #
 MASTER_NODE=""
 start-spark.sh
 echo "configuration done..."
 set -x
 #
 #echo $MASTER_NODE
 #echo $MASTER
 #
 #MASTER_IP=$(cat ./sparklogs_${SLURM_JOBID}/spark_master)
 MASTER_IP=$(cat ${SLURM_JOBID}_spark_master)
 #
 echo $MASTER_IP
 time time spark-submit \
 --executor-memory 5G \
 --master $MASTER_IP \
-./diffusion.py
+./pi.py
 #
 stop-spark.sh
 #scancel -u foureste
 #spark-submit --master $MASTER  ./pi.py
 
 
 
diff --git a/scripts/execute.sh b/scripts/execute.sh
index 75b5197..127571a 100755
--- a/scripts/execute.sh
+++ b/scripts/execute.sh
@@ -1,70 +1,70 @@
 #!/bin/bash
 # author: gilles fourestey (EPFL)
 # based on http://serverfault.com/questions/776687/how-can-i-run-spark-on-a-cluster-using-slurm
 # debug flag
 # set -x
 
 #echo $0 $1
 
 #env | grep SPARK
 
 # This section will be run when started by sbatch
 if [ "x$1" == 'x' ]; then
     this=$0
     # I experienced problems with some nodes not finding the script:
     #   slurmstepd: execve(): /var/spool/slurm/job123/slurm_script:
     #   No such file or directory
     # that's why this script is being copied to a shared location to which 
     # all nodes have access to:
     #script=./${SLURM_JOBID}_$(basename "$0")
     #cp "$this" "$script"
     script=$this
     #
     # This might not be necessary on all clusters
     # module load scala/2.10.4 java/jdk1.7.0_25 cuda/7.0.28
     #
     export sparkLogs=./sparklogs/
     export sparkTmp=./sparktmp/
     mkdir -p "$sparkLogs" "$sparkTmp"
     #
-    export SPARK_ROOT=/home/foureste/Projects/Spark/spark-2.0.1-bin-hadoop2.7/
+    #export SPARK_ROOT=/home/foureste/Projects/Spark/spark-2.0.1-bin-hadoop2.7/
     export SPARK_WORKER_DIR=$sparkLogs
     export SPARK_LOCAL_DIRS=$sparkLogs
     export SPARK_MASTER_PORT=7077
     export SPARK_MASTER_WEBUI_PORT=8080
     export SPARK_WORKER_CORES=$SLURM_CPUS_PER_TASK
     #export SPARK_DRIVER_MEMORY=60G
     #export SPARK_DAEMON_MEMORY=$(( $SLURM_MEM_PER_CPU * $SLURM_CPUS_PER_TASK / 2 ))m
     #export SPARK_DAEMON_MEMORY=8G
     #export SPARK_WORKER_MEMORY=48G
     #export SPARK_MEM=$SPARK_DAEMON_MEMORY
     #export SPARK_MEM=48G
     #
     #srun --mem=60G "$script" 'srunning'
     srun "$script" 'srunning'
     #
 # If run by srun, then decide by $SLURM_PROCID whether we are master or worker
 elif [ "$1" == 'srunning' ]; then
 #set -x
     #source "$SPARK_ROOT/sbin/spark-config.sh"
     #source "$SPARK_ROOT/bin/load-spark-env.sh"
     if [ $SLURM_PROCID -eq 0 ]; then
         export SPARK_MASTER_IP=$(hostname)
         MASTER_NODE=$(scontrol show hostname $SLURM_NODELIST | head -n 1)
 	#
         # The saved IP address + port is necessary alter for submitting jobs
         #echo "spark://$SPARK_MASTER_IP:$SPARK_MASTER_PORT" > "$sparkLogs/${SLURM_JOBID}_spark_master"
         echo "spark://$SPARK_MASTER_IP:$SPARK_MASTER_PORT" > "./${SLURM_JOBID}_spark_master"
 	#
         "$SPARK_ROOT/bin/spark-class" org.apache.spark.deploy.master.Master \
             --ip $SPARK_MASTER_IP                                           \
             --port $SPARK_MASTER_PORT                                       \
             --webui-port $SPARK_MASTER_WEBUI_PORT
     else
         # $(scontrol show hostname) is used to convert e.g. host20[39-40]
         # to host2039 this step assumes that SLURM_PROCID=0 corresponds to 
         # the first node in SLURM_NODELIST !
         MASTER_NODE=spark://$(scontrol show hostname $SLURM_NODELIST | head -n 1):7077
         "$SPARK_ROOT/bin/spark-class" org.apache.spark.deploy.worker.Worker $MASTER_NODE
     fi
 fi