To restrict users from accessing the system using Centriy free can be easily managed by using the following files
1. You have to manually create the the files accordingly and place it at /etc/centifydc. Next you have to line 273 and uncomment the line
If you are blocking by groups, you can likewise uncomment the
2. Flush and Reload Centrify-Free
3. Add users you wish to have access into the system into /etc/centrifydc/users.allow
Here is my simple script to setup shared SSH keys on Cluster. You can put this script called ssh-shared-keys.sh into /etc/skel/.bash_profile so that the new users have their keys shared between all the compute nodes.
# Exit script on Error
# Check for SSH Directory
if [ ! -d ~/.ssh ]; then
mkdir -p ~/.ssh/
# Check for existence of passphrase
if [ ! -f ~/.ssh/id_rsa.pub ]; then
ssh-keygen -t rsa -N "" -f ~/.ssh/id_rsa
echo "Execute ssh-keygen --[done]"
# Check for existence of authorized_keys and append the shared ssh keys
if [ ! -f ~/.ssh/authorized_keys ]; then
echo "Create ~/.ssh/authorized_keys --[done]"
chmod 700 ~/.ssh/authorized_keys
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
echo "Append the public keys id_rsa into authorized keys --[done]"
chmod 400 ~/.ssh/authorized_keys
chmod 700 ~/.ssh/
# Create user's ssh config it not exist
if [ ! -f ~/.ssh/config ]; then
echo "StrictHostKeyChecking no" > ~/.ssh/config
echo "StrictHostKeyChecking no --[done]"
chmod 644 ~/.ssh/config
# Unset error on exit or it will affect after bash command 🙂
- Helping users to SSH without password into the Compute Nodes manually
I wanted to install the packages using pip3. Before you can successfully install the python packages, do note that you have to make sure the following packages are found in your CentOS 6.
# yum install blas blas-devel lapack lapack-devel numpy
After you install according to Compiling and Configuring Python 3.4.1 on CentOS
The packages that I want to install are numpy scipy matplotlib ipython ipython[notebook] pandas sympy nose
# /usr/local/python-3.4.1/bin/pip install numpy
# /usr/local/python-3.4.1/bin/pip install scipy
# /usr/local/python-3.4.1/bin/pip install matplotlib
# /usr/local/python-3.4.1/bin/pip install ipython
# /usr/local/python-3.4.1/bin/pip install ipython[notebook]
# /usr/local/python-3.4.1/bin/pip install pandas
# /usr/local/python-3.4.1/bin/pip install sympy
# /usr/local/python-3.4.1/bin/pip install nose
The variables are as followed:
LSB_JOBID: LSF assigned job ID
LSB_BATCH_JID: Array job ID. Includes job ID and array index number
LSB_JOBINDEX: Job array index
- Accessing LSF batch job ID and array ID within job environment
The IPoIB driver supports two modes of operation: Unreliable Datagram (UD) and Connected Mode.
In Unreliable datagram mode, the IB UD (Unreliable Datagram) transport is used and so the interface MTU has is equal to the IB L2 MTU minus the IPoIB encapsulation header (4 bytes). In QDR, the default NTU value is 2044. In FDR onwards, the default MTU value for Unreliable Datagram is 4096.
In Connected Mode, the IB RC (Reliable Connected) transport is used.Connected mode takes advantage of the connected nature of the IB transport and allows an MTU up to the maximal IP packet size of 64K, which reduces the number of IP packets needed for handling large UDP datagrams, TCP segments, etc and increases the performance for large messages. Default MTU will be 65000. Performance will be better
To verify what modes you are working on, just do a
# cat /sys/class/net/ib0/mode