Introduction
============

This manual describes what the TARDIS is and provides some basic examples and
useful code snippets for various software packages that can be used on LIP's
cluster environment. We are trying to update the documentation every time we
successfully test a new use case. It is meant to be a guideline and if you need
help at any point we will be glad to assist you. We appreciate all of your
feedback so please contact us: `grid-admin@mpib-berlin.mpg.de
<grid-admin@mpib-berlin.mpg.de>`_

Specs
-----

Tardis
   **T**\ardis, **A** **R**\apid **D**\istributed **I**\nformation **S**\ystem

.. image:: ../img/tardis_real.png
   :width: 60%

Some technical facts:
    + **608** Intel® Xeon® CPU E5-2670 CPU cores inside 32 Dell m620 blade servers
    + **R**:sub:`max` = 5.1 TFlops, **R**:sub:`peak` = 12.6 TFlops
    + **3.2TB** total amount of memory
    + **256 GB** RAM on 6 of those nodes
    + **32 TB** of attached NFS storage
    + simple 2-level fat tree network with a theoretical bisection bandwidth of **40GB/s**


Workflows
---------

**Sequential**

The simplest and very typical processing workflow consist of 3 steps.

+ data download from file servers
+ sequential data processing
+ result upload to file servers

.. image:: ../img/WF-seq.svg
   :width: 80%

Obviously this is not very efficient and with data processing on the Tardis we
would want to do something more efficient. Also this approach requires desktop
machines in a shared working environment to be always on. This procudes
excessive noise and heat. It is also not very nice considering other colleagues
might want to use your machine as well. But most importantly it is **slow**.

**Parallel**

With the Tardis you can login from your laptop or workstation with SSH (see:
:doc:`login`) to a single head node called ``tardis``. On that node users can
prepare and test their code and analysis and then submit it to a queue (see:
:doc:`Torque`). Jobs will then **eventually** be submitted to one of the
computing nodes to get a guaranteed set of processing resources. Afterwards
users can collect the results and copy them back to the file servers.

.. image:: ../img/WF-par.svg
   :width: 80%
