docs.it4i/software/viz/openfoam.md

+# OpenFOAM
+
+OpenFOAM is a free, open source CFD software package.
+
+## Introduction
+
+[OpenFOAM][a] is a free, open source CFD software package developed by [OpenCFD Ltd][b] at [ESI Group][c] and distributed by the [OpenFOAM Foundation][d]. It has a large user base across most areas of engineering and science from both commercial and academic organizations.
+
+### Installed Version
+
+Currently, several versions are available compiled by GCC/ICC compilers in single/double precision with several versions of OpenMPI.
+
+The naming convention of the installed versions is:
+
+`openfoam/<VERSION>-<COMPILER>-<openmpiVERSION>-<PRECISION>`
+
+* `VERSION` - version of openfoam
+* `COMPILER` - version of used compiler
+* `openmpiVERSION` - version of used openmpi/impi
+* `PRECISION` - DP/SP – double/single precision
+
+Example of the available OpenFOAM modules syntax is `openfoam/2.2.1-icc-openmpi1.6.5-DP`
+
+This means OpenFOAM version 2.2.1 compiled by the ICC compiler with openmpi1.6.5 in double precision.
+
+### Available OpenFOAM Modules
+
+To check the available modules, use:
+
+```console
+$ ml av
+```
+
+In /opt/modules/modulefiles/engineering, you can see the installed engineering softwares:
+
+```console
+    ------------------------------------ /opt/modules/modulefiles/engineering -------------------------------------------------------------
+    ansys/14.5.x               matlab/R2013a-COM                                openfoam/2.2.1-icc-impi4.1.1.036-DP
+    comsol/43b-COM             matlab/R2013a-EDU                                openfoam/2.2.1-icc-openmpi1.6.5-DP
+    comsol/43b-EDU             openfoam/2.2.1-gcc481-openmpi1.6.5-DP            paraview/4.0.1-gcc481-bullxmpi1.2.4.1-osmesa10.0
+    lsdyna/7.x.x               openfoam/2.2.1-gcc481-openmpi1.6.5-SP
+```
+
+For information on how to use modules, look [here][1].
+
+## Getting Started
+
+To create OpenFOAM environment, use the commands:
+
+```console
+$ ml openfoam
+$ source $FOAM_BASHRC
+```
+
+!!! note
+    Load the correct module with your requirements “compiler - GCC/ICC, precision - DP/SP”.
+
+Create a project directory within the $HOME/OpenFOAM directory named `<USER>-<OFversion>` and create a directory named `run` within it:
+
+```console
+$ mkdir -p $FOAM_RUN
+```
+
+The project directory is now available by typing:
+
+```console
+$ cd /home/<USER>/OpenFOAM/<USER>-<OFversion>/run
+```
+
+`<OFversion>` - for example `2.2.1`
+
+or
+
+```console
+$ cd $FOAM_RUN
+```
+
+Copy the tutorial examples directory in the OpenFOAM distribution to the run directory:
+
+```console
+$ cp -r $FOAM_TUTORIALS $FOAM_RUN
+```
+
+Now you can run the first case, for example incompressible laminar flow in a cavity.
+
+## Running Serial Applications
+
+Create a test.sh Bash script:
+
+```bash
+#!/bin/bash
+
+ml openfoam/2.2.1-icc-openmpi1.6.5-DP
+source $FOAM_BASHRC
+
+# source to run functions
+. $WM_PROJECT_DIR/bin/tools/RunFunctions
+
+cd $FOAM_RUN/tutorials/incompressible/icoFoam/cavity
+
+runApplication blockMesh
+runApplication icoFoam
+```
+
+Job submission (example for Karolina):
+
+```console
+$ sbatch -A PROJECT_ID -p qcpu --nodes=1 --ntasks=128 --time=03:00:00 test.sh
+```
+
+For information about job submission, look [here][2].
+
+## Running Applications in Parallel
+
+Run the second case, for example external incompressible turbulent flow - case - motorBike.
+
+First we must run the serial application bockMesh and decomposePar for preparation of parallel computation.
+
+!!! note
+    Create a test.sh Bash scrip:
+
+```bash
+#!/bin/bash
+
+ml openfoam/2.2.1-icc-openmpi1.6.5-DP
+source $FOAM_BASHRC
+
+# source to run functions
+. $WM_PROJECT_DIR/bin/tools/RunFunctions
+
+cd $FOAM_RUN/tutorials/incompressible/simpleFoam/motorBike
+
+runApplication blockMesh
+runApplication decomposePar
+```
+
+Job submission
+
+```console
+$ sbatch -A PROJECT_ID -p qcpu --nodes=1 --ntasks=16 --time=03:00:00 test.sh
+```
+
+This job creates a simple block mesh and domain decomposition. Check your decomposition and submit parallel computation:
+
+!!! note
+    Create a testParallel.slurm script:
+
+```bash
+#!/bin/bash
+#SBATCH --job-name=motorBike
+#SBATCH --nodes=2
+#SBATCH --ntasks-per-node=16
+#SBATCH --time=01:00:00
+#SBATCH --partition=qcpu
+#SBATCH --account=ACCOUNT_ID
+
+ml openfoam/2.2.1-icc-openmpi1.6.5-DP
+source $FOAM_BASHRC
+
+cd $FOAM_RUN/tutorials/incompressible/simpleFoam/motorBike
+
+nproc = 32
+
+mpirun -hostfile ${$SLURM_JOB_NODELIST} -np $nproc snappyHexMesh -overwrite -parallel | tee snappyHexMesh.log
+
+mpirun -hostfile ${$SLURM_JOB_NODELIST} -np $nproc potentialFoam -noFunctionObject-writep -parallel | tee potentialFoam.log
+
+mpirun -hostfile ${$SLURM_JOB_NODELIST} -np $nproc simpleFoam -parallel | tee simpleFoam.log
+```
+
+`nproc` – the number of subdomains
+
+Job submission
+
+```console
+$ srun testParallel.slurm
+```
+
+## Compile Your Own Solver
+
+Initialize the OpenFOAM environment before compiling your solver:
+
+```console
+$ ml openfoam/2.2.1-icc-openmpi1.6.5-DP
+$ source $FOAM_BASHRC
+$ cd $FOAM_RUN/
+```
+
+Create the applications/solvers directory in the user directory:
+
+```console
+$ mkdir -p applications/solvers
+$ cd applications/solvers
+```
+
+Copy icoFoam solver’s source files:
+
+```console
+$ cp -r $FOAM_SOLVERS/incompressible/icoFoam/My_icoFoam
+$ cd My_icoFoam
+```
+
+Rename icoFoam.C to My_icoFOAM.C:
+
+```console
+$ mv icoFoam.C My_icoFoam.C
+```
+
+Edit the _files_ file in the _Make_ directory:
+
+```bash
+    icoFoam.C
+    EXE = $(FOAM_APPBIN)/icoFoam
+```
+
+and change to:
+
+```bash
+    My_icoFoam.C
+    EXE = $(FOAM_USER_APPBIN)/My_icoFoam
+```
+
+In the My_icoFoam directory, use the compilation command:
+
+```console
+$ wmake
+```
+
+[1]: ../../environment-and-modules.md
+[2]: ../../general/job-submission-and-execution.md
+
+[a]: http://www.openfoam.com/
+[b]: http://www.openfoam.com/about
+[c]: http://www.esi-group.com/
+[d]: http://www.openfoam.org/

docs.it4i/software/viz/ovito.md

+# Ovito
+
+[OVITO][a] is a visualization and analysis software for output data generated in molecular dynamics, atomistic Monte-Carlo and other particle-based simulations.
+
+## Introduction
+
+A central aim of OVITO as a data visualization and analysis solution is to provide a maximum of flexibility – and, at the same time, ease-of-use – to support you in extracting meaningful information from simulation outputs.  To achieve this goal, OVITO is based on a powerful data pipeline technology depicted below. The software offers a wide range of basic visualization and analysis functions (building blocks), which you can assemble to a sequence of processing steps. These operations, which are all configurable, will then be applied to the simulation data in real-time by the software. The outcome of the data pipeline is finally displayed on screen, may be rendered to an output image for publication, or exported to output data files.
+
+![](../../img/ovito_data_pipeline.png)
+
+The dynamic pipeline concept makes it possible for you to change and adjust the sequence of applied operations at any time. In other words, OVITO enables you to work in a non-destructive manner with a dataset as all manipulation steps can easily be revoked. You can adjust the order of filter and manipulation operations, their parameters, and also the input data itself –the program will re-evaluate the pipeline and update the display in real-time. Thanks to intelligent data caching and parallelization techniques implemented in OVITO, this all happens without interrupting your workflow.
+
+For more information, see the [User Manual][b]
+
+### Installed Version
+
+For the list of installed versions, use:
+
+```console
+$ ml av ovito
+```
+
+## Getting Started
+
+The visualization software requires [graphical user interface][1] or [virtual network computing][2] software.
+
+[1]: ../../general/accessing-the-clusters/graphical-user-interface/x-window-system.md
+[2]: ../../general/accessing-the-clusters/graphical-user-interface/vnc.md
+
+[a]: https://www.ovito.org/
+[b]: https://www.ovito.org/docs/current/

docs.it4i/software/viz/paraview.md

+# ParaView
+
+An open-source, multi-platform data analysis and visualization application.
+
+## Introduction
+
+[ParaView][a] is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.
+
+ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of exascale size as well as on laptops for smaller data.
+
+## Installed Version
+
+Currently, version 5.1.2 compiled with Intel/2017a against the Intel MPI library and OSMesa 12.0.2 is installed on the clusters.
+
+## Usage
+
+On the clusters, ParaView is to be used in the client-server mode. A parallel ParaView server is launched on compute nodes by the user and the client is launched on your desktop PC to control and view the visualization. Download the ParaView client application for your OS [here][b].
+
+!!!Warning
+    Your version must match the version number installed on the cluster.
+
+### Launching Server
+
+To launch the server, you must first allocate compute nodes, for example:
+
+```console
+$ salloc -p qprod -A PROJECT_ID --nodes=2 --time=01:00:00 --x11
+```
+
+to launch an interactive session on 2 nodes. For details, refer to [Job Submission and Execution][1] section.
+
+After the interactive session is opened, load the ParaView module:
+
+```console
+$ ml ParaView/5.1.2-intel-2017a-mpi
+```
+
+Now launch the parallel server, with the number of processes equal to the number of nodes times 24:
+
+```console
+$ mpirun -np 48 pvserver --use-offscreen-rendering
+    Waiting for client...
+    Connection URL: cs://r37u29n1006:11111
+    Accepting connection(s): r37u29n1006:11111i
+```
+
+Note that in this case, the server is listening on the compute node r37u29n1006, we will use this information later.
+
+### Client Connection
+
+Because a direct connection is not allowed to compute nodes on clusters, you must establish an SSH tunnel to connect to the server. Choose a port number on your PC to be forwarded to ParaView server, for example 12345. If your PC is running Linux, use this command to establish an SSH tunnel:
+
+```console
+Barbora: $ ssh -TN -L 12345:r37u29n1006:11111 username@barbora.it4i.cz
+```
+
+Replace username with your login and r37u29n1006 with the name of the compute node on which your ParaView server is running (see the previous step).
+
+If you use PuTTY on Windows, load Barbora connection configuration, then go to *Connection* -> *SSH* -> *Tunnels* to set up the port forwarding.
+
+Fill the Source port and Destination fields. **Do not forget to click the Add button.**
+
+![](../../img/paraview_ssh_tunnel_salomon.png "SSH Tunnel in PuTTY")
+
+Now launch ParaView client installed on your desktop PC. Select *File* -> *Connect...* and fill in the following :
+
+![](../../img/paraview_connect_salomon.png "ParaView - Connect to server")
+
+The configuration is now saved for later use. Now click Connect to connect to the ParaView server. In your terminal where you have the interactive session with the ParaView server launched, you should see:
+
+```console
+Client connected.
+```
+
+You can now use Parallel ParaView.
+
+### Close Server
+
+Remember to close the interactive session after you finish working with the ParaView server, as it will remain launched and continue consuming resources even after your client is disconnected.
+
+[1]: ../../general/job-submission-and-execution.md
+
+[a]: http://www.paraview.org/
+[b]: http://paraview.org/paraview/resources/software.php

docs.it4i/software/viz/qtiplot.md

+# QtiPlot
+
+A cross-platform scientific application for data analysis and visualisation.
+
+## Introduction
+
+[QtiPlot][1] is a cross-platform scientific application for data analysis and visualisation.
+QtiPlot can be used to present 2D and 3D data and has various data analysis functions like curve fitting.
+The program is also extensible to a considerable degree via muParser and Python scripting language,
+which allows adding the arbitrary user-defined functions with access to graphs, matrices and data tables.
+
+## Installed Versions
+
+For the current list of installed versions, use:
+
+```console
+$ ml av QtiPlot
+```
+
+## Running QtiPlot
+
+!!! important
+    You must first enable the [VNC][a] or [X Window System][b] GUI environment.
+
+To run QtiPlot, use:
+
+```console
+$ ml QtiPlot; qtiplot
+```
+
+[1]: https://www.qtiplot.com/index.html
+
+[a]: ../../../general/accessing-the-clusters/graphical-user-interface/vnc/
+[b]: ../../../general/accessing-the-clusters/graphical-user-interface/x-window-system/

docs.it4i/software/viz/vesta.md

+# Vesta
+
+## Introduction
+
+VESTA (Visualization for Electronic and Structural Analysis) is a 3D visualization program for structural models, volumetric data such as electron/nuclear densities, and crystal morphologies. Some of the novel features of VESTA include:
+
+* Deal with multiple structural models, volumetric data, and crystal morphologies in the same window;
+* Support multiple tabs corresponding to files;
+* Support multiple windows with more than two tabs in the same process;
+* Deal with virtually unlimited number of objects such as atoms, bonds polyhedra, and polygons on isosurfaces (theoretical limit on 32bit operating  system is 1,073,741,823);
+* Support lattice transformation from conventional to non-conventional lattice by using matrix. The transformation matrix is also used to create superlattice and sublattice;
+* Visualize interatomic distances and bond angles that are restrained in Rietveld analysis with RIETAN-FP;
+* Transparent isosurfaces can be overlap with structural models;
+* Isosurface can be colored on the basis of another physical quantity;
+* Arithmetic operations among multiple volumetric data files;
+* High quality smooth rendering of isosurfaces and sections;
+* Export high-resolution graphic images exceeding Video card limitation.
+
+For the full list of features and supported file formats, see the [official page][1].
+
+## Manual
+
+The VESTA manual can be found [here][2].
+
+## Installed Versions
+
+For the current list of installed versions, use:
+
+```console
+$ ml av vesta
+```
+
+!!!note Module Availability
+    This module is currently availble on the Barbora cluster only.
+
+[1]: https://jp-minerals.org/vesta/en/
+[2]: https://jp-minerals.org/vesta/archives/VESTA_Manual.pdf

docs.it4i/software/viz/vgl.md

+# VirtualGL
+
+VirtualGL is an open source program that redirects the 3D rendering commands from Unix and Linux OpenGL applications to 3D accelerator hardware in a dedicated server and displays the rendered output interactively to a thin client located elsewhere on the network.
+
+See the documentation [here][a].
+
+!!! info
+    VirtualGL is available on Barbora and Karolina.
+
+## How to Use
+
+**Run VNC**
+
+* VNC Server
+
+Read our documentation on [VNC server][1].
+
+```console
+Warning: No xauth data; using fake authentication data for X11 forwarding.
+Last login: Tue Mar  3 14:20:18 2020 from vpn-kru0052.it4i.cz
+                  ____             _
+                 |  _ \           | |
+                 | |_) | __ _ _ __| |__   ___  _ __ __ _
+                 |  _ < / _` | '__| '_ \ / _ \| '__/ _` |
+                 | |_) | (_| | |  | |_) | (_) | | | (_| |
+                 |____/ \__,_|_|  |_.__/ \___/|_|  \__,_|
+
+
+                  ...running on Red Hat Enterprise Linux 7.x
+
+kru0052@login1:~$ vncserver :99
+
+New 'login1.barbora.it4i.cz:99 (kru0052)' desktop is login1.barbora.it4i.cz:99
+
+Starting applications specified in /home/kru0052/.vnc/xstartup
+Log file is /home/kru0052/.vnc/login1.barbora.it4i.cz:99.log
+
+kru0052@login1:~$
+```
+
+* VNC Client (your local machine)
+
+```console
+root@toshiba:~# ssh -L 5999:localhost:5999 kru0052@login1.barbora.it4i.cz -X
+```
+
+* Connect to a VNC server from a VNC client (your local machine)
+
+```console
+vncviewer localhost:99
+
+```
+
+Or via GUI.
+
+![](../../img/vnc.jpg)
+
+!!! tip
+    To resize the window scale, use the `xrandr -s 1920x1200` command.
+
+**Run vglclient on the login server (use the terminal in the local machine VNC window)**
+
+```console
+kru0052@login1:~$ ml VirtualGL
+kru0052@login1:~$ vglclient
+
+VirtualGL Client 64-bit v2.6.1 (Build 20200228)
+Listening for unencrypted connections on port 4242
+
+```
+
+![](../../img/client.jpg)
+
+**Execute an interactive job on vizserv (use another terminal in the local machine VNC window)**
+
+```console
+[kru0052@login1.barbora ~]$ salloc -p qviz -A PROJECT_ID --x11
+salloc: Granted job allocation 694741
+salloc: Waiting for resource configuration
+salloc: Nodes vizserv1 are ready for job
+
+[kru0052@vizserv1.barbora ~]$
+```
+
+![](../../img/job.jpg)
+
+**New SSH connection on vizserv - elimination of the Slurm setting (use another terminal in the local machine VNC window)**
+
+```console
+kru0052@login1:~$ ssh vizserv1 -X
+Last login: Tue Mar  3 13:54:33 2020 from login1.barbora.it4i.cz
+kru0052@vizserv1:~$
+```
+
+![](../../img/ssh.jpg)
+
+**Run the graphical application**
+
+```console
+kru0052@vizserv1:~$ vglrun /apps/easybuild/glxgears
+[VGL] NOTICE: Automatically setting VGL_CLIENT environment variable to
+[VGL]    10.32.2.1, the IP address of your SSH client.
+libGL error: unable to load driver: swrast_dri.so
+libGL error: failed to load driver: swrast
+17128 frames in 5.0 seconds = 3425.573 FPS
+17251 frames in 5.0 seconds = 3450.128 FPS
+...
+```
+
+![](../../img/glxgears.jpg)
+
+## Examples for Remote Visualization on Barbora Cluster
+
+<div align="center">
+  <iframe  width="854" height="480" src="https://www.youtube.com/embed/BArIbIC_-24"></iframe>
+</div>
+
+[1]: ../../../general/accessing-the-clusters/graphical-user-interface/vnc/
+
+[a]: https://www.virtualgl.org/

docs.it4i/src/css.css

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+<script type="text/javascript">var RadarChart = {
+  draw: function(id, d, options){
+    var cfg = {
+     radius: 5,
+     w: 600,
+     h: 600,
+     factor: .95,
+     factorLegend: 1,
+     levels: 3,
+     maxValue: 0,
+     radians: 2 * Math.PI,
+     opacityArea: 0.5,
+     color: d3.scale.category10(),
+     fontSize: 10
+    };
+    if('undefined' !== typeof options){
+      for(var i in options){
+        if('undefined' !== typeof options[i]){
+          cfg[i] = options[i];
+        }
+      }
+    }
+    cfg.maxValue = Math.max(cfg.maxValue, d3.max(d, function(i){return d3.max(i.map(function(o){return o.value;}))}));
+    var allAxis = (d[0].map(function(i, j){return i.axis}));
+    var total = allAxis.length;
+    var radius = cfg.factor*Math.min(cfg.w/2, cfg.h/2);
+    d3.select(id).select("svg").remove();
+    var g = d3.select(id).append("svg").attr("width", cfg.w).attr("height", 0.75 * cfg.h).append("g");
+
+    var tooltip;
+    function getPosition(i, range, factor, func){
+      factor = typeof factor !== 'undefined' ? factor : 1;
+      return range * (1 - factor * func(i * cfg.radians / total));
+    }
+    function getHorizontalPosition(i, range, factor){
+      return getPosition(i, range, factor, Math.sin);
+    }
+    function getVerticalPosition(i, range, factor){
+      return getPosition(i, range, factor, Math.cos);
+    }
+
+    for(var j=0; j<cfg.levels; j++){
+      var levelFactor = radius*((j+1)/cfg.levels);
+      g.selectAll(".levels").data(allAxis).enter().append("svg:line")
+       .attr("x1", function(d, i){return getHorizontalPosition(i, levelFactor);})
+       .attr("y1", function(d, i){return getVerticalPosition(i, levelFactor);})
+       .attr("x2", function(d, i){return getHorizontalPosition(i+1, levelFactor);})
+       .attr("y2", function(d, i){return getVerticalPosition(i+1, levelFactor);})
+       .attr("class", "line").style("stroke", "grey").style("stroke-width", "0.5px").attr("transform", "translate(" + (cfg.w/2-levelFactor) + ", " + (cfg.h/2-levelFactor) + ")");
+
+    }
+
+    series = 0;
+
+    var axis = g.selectAll(".axis").data(allAxis).enter().append("g").attr("class", "axis");
+
+    axis.append("line")
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+        .attr("y1", cfg.h/2)
+        .attr("x2", function(j, i){return getHorizontalPosition(i, cfg.w/2, cfg.factor);})
+        .attr("y2", function(j, i){return getVerticalPosition(i, cfg.h/2, cfg.factor);})
+        .attr("class", "line").style("stroke", "grey").style("stroke-width", "1px");
+
+    axis.append("text").attr("class", function(d){ return "legend_" + d.replace("/", "") })
+        .text(function(d){return d})
+        .style("font-size", cfg.fontSize + "px")
+        .style("text-anchor", function(d, i){
+          var p = getHorizontalPosition(i, 0.5);
+          return (p < 0.4) ? "start" : ((p > 0.6) ? "end" : "middle");
+        })
+        .attr("transform", function(d, i){
+          var p = getVerticalPosition(i, cfg.h / 2);
+          return p < cfg.fontSize ? "translate(0, " + (cfg.fontSize - p) + ")" : "";
+        })
+        .attr("x", function(d, i){return getHorizontalPosition(i, cfg.w / 2, cfg.factorLegend);})
+        .attr("y", function(d, i){return getVerticalPosition(i, cfg.h / 2, cfg.factorLegend);});
+ 
+    d.forEach(function(y, x){
+      dataValues = [];
+      g.selectAll(".nodes")
+        .data(y, function(j, i){
+          dataValues.push([
+            getHorizontalPosition(i, cfg.w/2, (parseFloat(Math.max(j.value, 0))/cfg.maxValue)*cfg.factor),
+            getVerticalPosition(i, cfg.h/2, (parseFloat(Math.max(j.value, 0))/cfg.maxValue)*cfg.factor)
+          ]);
+        });
+      dataValues.push(dataValues[0]);
+      g.selectAll(".area")
+                     .data([dataValues])
+                     .enter()
+                     .append("polygon")
+                     .attr("class", "radar-chart-serie"+series)
+                     .style("stroke-width", "2px")
+                     .style("stroke", cfg.color(series))
+                     .attr("points",function(d) {
+                         var str="";
+                         for(var pti=0;pti<d.length;pti++){
+                             str=str+d[pti][0]+","+d[pti][1]+" ";
+                         }
+                         return str;
+                      })
+                     .style("fill", function(j, i){return cfg.color(series)})
+                     .style("fill-opacity", cfg.opacityArea)
+                     .on('mouseover', function (d){
+                                        z = "polygon."+d3.select(this).attr("class");
+                                        g.selectAll("polygon").transition(200).style("fill-opacity", 0.1); 
+                                        g.selectAll(z).transition(200).style("fill-opacity", .7);
+                                      })
+                     .on('mouseout', function(){
+                                        g.selectAll("polygon").transition(200).style("fill-opacity", cfg.opacityArea);
+                     });
+      series++;
+    });
+    series=0;
+
+
+    d.forEach(function(y, x){
+      g.selectAll(".nodes")
+        .data(y).enter()
+        .append("svg:circle").attr("class", "radar-chart-serie"+series)
+        .attr('r', cfg.radius)
+        .attr("alt", function(j){return Math.max(j.value, 0)})
+        .attr("cx", function(j, i){
+          dataValues.push([
+            getHorizontalPosition(i, cfg.w/2, (parseFloat(Math.max(j.value, 0))/cfg.maxValue)*cfg.factor),
+            getVerticalPosition(i, cfg.h/2, (parseFloat(Math.max(j.value, 0))/cfg.maxValue)*cfg.factor)
+          ]);
+          return getHorizontalPosition(i, cfg.w/2, (Math.max(j.value, 0)/cfg.maxValue)*cfg.factor);
+        })
+        .attr("cy", function(j, i){
+          return getVerticalPosition(i, cfg.h/2, (Math.max(j.value, 0)/cfg.maxValue)*cfg.factor);
+        })
+        .attr("data-id", function(j){return j.axis})
+        .style("fill", cfg.color(series)).style("fill-opacity", .9)
+        .on('mouseover', function (d){
+                    newX =  parseFloat(d3.select(this).attr('cx')) - 10;
+                    newY =  parseFloat(d3.select(this).attr('cy')) - 5;
+                    tooltip.attr('x', newX).attr('y', newY).text(d.value).transition(200).style('opacity', 1);
+                    z = "polygon."+d3.select(this).attr("class");
+                    g.selectAll("polygon").transition(200).style("fill-opacity", 0.1); 
+                    g.selectAll(z).transition(200).style("fill-opacity", .7);
+                  })
+        .on('mouseout', function(){
+                    tooltip.transition(200).style('opacity', 0);
+                    g.selectAll("polygon").transition(200).style("fill-opacity", cfg.opacityArea);
+                  })
+        .append("svg:title")
+        .text(function(j){return Math.max(j.value, 0)});
+
+      series++;
+    });
+    //Tooltip
+    tooltip = g.append('text').style('opacity', 0).style('font-family', 'sans-serif').style('font-size', '13px');
+  }
+}
+
+</script>
+<script type="text/javascript">window.onload = function() {
+    var cpu = 88.6;
+    var mpi = 11.4;
+    var io = 0.0;
+
+    // Draw radar chart, choose its color based on application classification
+    var radar_data = [[ { axis: "CPU", value: cpu },
+                        { axis: "MPI", value: mpi },
+                        { axis: "I/O", value: io } ]];
+    var radar_options = { w: 200, h: 200, factor: 0.7, fontSize: 16, radius: 0, 
+                          opacityArea: 0.64, maxValue: 100, 
+                          color: function() {
+                              if ("cpu" == "io")  return "#ed8140";
+                              if ("cpu" == "cpu") return "#4fd32e";
+                              if ("cpu" == "mpi") return "#409ded";
+                              else return "#bb58d6";
+                          }
+                        };
+    RadarChart.draw("#time_radar", radar_data, radar_options);
+
+    // Wrap the exe path on slashes if necessary
+    var exe_path = document.getElementById("exe_path");
+    exe_path.innerHTML = exe_path.innerHTML.replace(/\//g, '/&#x200b;'); // insert a zero width space after slashes as a word wrap hint
+
+    // Format our byte value numbers to show at most 2 decimal places, but only if required to attain 3 digits of precision
+    // 1234.56 -> "1234"
+    // 12.3456 -> "12.3"
+    // 1.23456 -> "1.23"
+    // 0.00000 -> "0.00"
+    var formatNumber = function(num) {
+        if (num > 100) return new Number(num).toFixed(0); // 1234.56 -> 1234
+        if (num > 10)  return new Number(num).toFixed(1); // 12.3456 -> 12.3
+        else           return new Number(num).toFixed(2); // 1.23456 -> 1.23 and 0 -> 0.00
+    }
+
+    // Parse a number, but return 0 for invalid numbers, not NaN
+    var toNumber = function(num_str) {
+        var num = Number(num_str)
+        return isNaN(num) ? 0 : num;
+    }
+
+    // Scale byte values to bytes, kB, MB or GB as appropriate
+    var fillBytes = function(base_name, bytes_str, per_second) {
+        var units = "bytes";
+        var scale = 1.0;
+        var bytes = Number(bytes_str)
+        if      (isNaN(bytes)      ) { units = ""  ;                           }
+        else if (bytes > 1000000000) { units = "GB"; scale = 1*1000*1000*1000; }
+        else if (bytes > 1000000   ) { units = "MB"; scale = 1*1000*1000       }
+        else if (bytes > 1000      ) { units = "kB"; scale = 1*1000            }
+        var num = isNaN(bytes) ? bytes_str : formatNumber(bytes / scale);
+        var elementNum = document.getElementById(base_name + "_num");
+        elementNum.innerHTML = num;
+        var elementUnits = document.getElementById(base_name + "_units");
+        elementUnits.innerHTML = units + (per_second && !isNaN(bytes) ? "/s" : "");
+    };
+
+    // Fill all the byte numbers and their units with the scaled values
+    fillBytes("mpi_colrate", "1.65e+02", true);
+    fillBytes("mpi_p2prate", "0.00e+00", true);
+    fillBytes("io_readrate", "0.00e+00", true);
+    fillBytes("io_writerate", "0.00e+00", true);
+    fillBytes("ram_mean", "2.33e+07", false);
+    fillBytes("ram_peak", "2.35e+07", false);
+
+    // Set widths for all graphs
+    var bar = function(name, width) {
+        var rounded = Math.round(width);
+        if (!isFinite(rounded) || rounded < 1)
+            document.getElementById(name).style.width = "1px"
+        else
+            document.getElementById(name).style.width = rounded + "px";
+    };
+    bar("cpu_bar", cpu * 2);
+    bar("mpi_bar", mpi * 2);
+    bar("io_bar", io * 2);
+
+    bar("cpu_num_bar", toNumber("50.0") / 2);
+    bar("cpu_vec_bar", toNumber("50.0") / 2);
+    bar("cpu_mem_bar", toNumber("0.0") / 2);
+    bar("cpu_other_bar", toNumber("0.0") / 2);
+
+    bar("mpi_col_bar", toNumber("100.0") / 2);
+    bar("mpi_p2p_bar", toNumber("0.0") / 2);
+    var mpi_scale = Math.max(toNumber("1.65e+02"), toNumber("0.00e+00"));
+    bar("mpi_colrate_bar", 50 * toNumber("1.65e+02") / mpi_scale);
+    bar("mpi_p2prate_bar", 50 * toNumber("0.00e+00") / mpi_scale);
+
+    bar("io_read_bar", toNumber("0.0") / 2);
+    bar("io_write_bar", toNumber("0.0") / 2);
+    var io_scale = Math.max(toNumber("0.00e+00"), toNumber("0.00e+00"));
+    bar("io_readrate_bar", 50 * toNumber("0.00e+00") / io_scale);
+    bar("io_writerate_bar", 50 * toNumber("0.00e+00") / io_scale);
+
+    bar("ram_mean_bar", 50 * toNumber("2.33e+07") / toNumber("2.35e+07"));
+    bar("ram_peak_bar", 50);
+    bar("ram_node_bar", toNumber("2.8") / 2);
+
+    // Formatting replacement helper function
+    var replaceIn = function(elementId, re, new_text) {
+        element = document.getElementById(elementId);
+        element.innerHTML = element.innerHTML.replace(re, new_text);
+    };
+
+    // Add formatting for the overview advice section
+    replaceIn('overview_advice', /CPU/g,  '<span class="cpu_span">CPU</span>');
+    replaceIn('overview_advice', /MPI/g,  '<span class="mpi_span">MPI</span>');
+    replaceIn('overview_advice', /I\/O/g, '<span class="io_span">I\/O</span>');
+
+    // Add formatting for the CPU advice section
+    if ( 88.6 < 0.05 )
+        replaceIn('cpu_explanation', /application code/g, '<span class="cpu_span">application code</span>');
+    replaceIn('cpu_explanation', /vectorized instructions/g, '<span class="cpu_vec_span">vectorized instructions</span>');
+    replaceIn('cpu_explanation', /memory accesses/g,         '<span class="cpu_mem_span">memory accesses</span>');
+    replaceIn('cpu_explanation', /memory-bound/g,            '<span class="cpu_mem_span">memory-bound</span>');
+    replaceIn('cpu_explanation', /arithmetic-bound/g,        '<span class="cpu_num_span">arithmetic-bound</span>');
+    replaceIn('cpu_explanation', /numerical computation/g,   '<span class="cpu_num_span">numerical computation</span>');
+
+    // Add formatting for the MPI advice section
+    if ( 11.4 < 0.05 )
+        replaceIn('mpi_explanation', /MPI/g, '<span class="mpi_span">MPI</span>');
+    replaceIn('mpi_explanation', /collective calls/g, '<span class="mpi_col_span">collective calls</span>');
+    replaceIn('mpi_explanation', /point-to-point calls/g, '<span class="mpi_p2p_span">point-to-point calls</span>');
+    replaceIn('mpi_explanation', / very low/g,  ' <span class="mpi_colrate_span">very low</span>');
+    replaceIn('mpi_explanation', / low/g,       ' <span class="mpi_colrate_span">low</span>');
+    replaceIn('mpi_explanation', / average/g,   ' <span class="mpi_colrate_span">average</span>');
+    replaceIn('mpi_explanation', / very high/g, ' <span class="mpi_colrate_span">very high</span>');
+    replaceIn('mpi_explanation', / high/g,      ' <span class="mpi_colrate_span">high</span>');
+
+    // Add formatting for the I/O advice section
+    if ( 0.0 < 0.05 )
+        replaceIn('io_explanation', /I\/O/g, '<span class="io_span">I/O</span>');
+    replaceIn('io_explanation', /read operations/g, '<span class="io_read_span">read operations</span>');
+    replaceIn('io_explanation', /write operations/g, '<span class="io_write_span">write operations</span>');
+    replaceIn('io_explanation', / very low/g,  ' <span class="io_readrate_span">very low</span>');
+    replaceIn('io_explanation', / low/g,       ' <span class="io_readrate_span">low</span>');
+    replaceIn('io_explanation', / average/g,   ' <span class="io_readrate_span">average</span>');
+    replaceIn('io_explanation', / very high/g, ' <span class="io_readrate_span">very high</span>');
+    replaceIn('io_explanation', / high/g,      ' <span class="io_readrate_span">high</span>');
+
+    // Add formatting for the RAM advice section
+    replaceIn('ram_explanation', /high/g, ' <span class="ram_node_span">high</span>');
+    replaceIn('ram_explanation', /well-balanced/g, '<span class="ram_peak_span">well-balanced</span>');
+    replaceIn('ram_explanation', /significant variation/g, '<span class="ram_peak_span">significant variation</span>');
+    replaceIn('ram_explanation', /peak node memory usage/g, '<span class="ram_node_span">peak node memory usage</span>');
+
+    // Hide the error warning if the script got this far
+    document.getElementById('error').style.display = 'none';
+};
+</script>
+</head>
+
+<body>
+<div id="content">
+
+<div class="header">
+    <div class="logo"><img src="http://content.allinea.com/downloads/performance-report-logo.png" alt="Allinea Performance Reports" /></div>
+    <div class="header_left">
+        <div class="application_details">
+            <table>
+                <tr><td class="details_key">Executable:</td><td id="exe_name">mympiprog.x</td></tr>
+                <tr><td class="details_key">Resources:</td><td id="num_procs">32 processes, 2 nodes</td></tr>
+                <tr><td class="details_key">Machine:</td><td id="machine_name">cn182</td></tr>
+                <tr><td class="details_key">Start time:</td><td id="start_date">Wed Oct 15 16:56:23 2014</td></tr>
+                <tr><td class="details_key">Total time:</td><td id="time_string">7 seconds (0 minutes)</td></tr>
+                <tr><td class="details_key">Full path:</td><td id="exe_path">/home/user</td></tr>
+                <tr><td class="details_key">Notes:</td><td id="notes"></td></tr>
+            </table>
+        </div>
+    </div>
+    <div id="time_radar"></div>
+    <div class="clear"></div>
+</div>
+<hr />
+<div id="error">
+<p><strong>Error: javascript is not running</strong></p>
+<p>The graphs in this Performance Report require <strong>javascript</strong>, which is disabled or not working.</p>
+<p>Check whether your javascript support is enabled or try another browser.<p>
+<p>Remember, you can always contact <a href="mailto:support@allinea.com">support@allinea.com</a>, we're very nice!</p>
+</div>
+<div class="summary">
+    <div class="heading">Summary: mympiprog.x is <span class="cpu_span">CPU-bound</span> in this configuration</div>
+    <div>The total wallclock time was spent as follows:</div>
+    <table class="summary_table">
+        <tr><td class="heading_cpu">CPU</td><td class="percent">88.6%</td><td class="bar_graph"><div id="cpu_bar" /></td>
+            <td class="details"><p>Time spent running application code. High values are usually good.</p><p>This is <span id="summary_cpu_class">high</span>; check the CPU performance section for optimization advice.</p></td></tr>
+        <tr><td class="heading_mpi">MPI</td><td class="percent">11.4%</td><td class="bar_graph"><div id="mpi_bar" /></td>
+            <td class="details"><p>Time spent in MPI calls. High values are usually bad.</p><p>This is <span id="summary_mpi_class">very low</span>; this code may benefit from increasing the process count.</p></td></tr>
+        <tr><td class="heading_io">I/O</td><td class="percent">0.0%</td><td class="bar_graph"><div id="io_bar" /></td>
+            <td class="details"><p>Time spent in filesystem I/O. High values are usually bad.</p><p>This is <span id="summary_io_class">negligible</span>; there's no need to investigate I/O performance.</p></td></tr>
+    </table>
+    <div class="overview_general_advice"><p>This application run was <span class="cpu_span">CPU-bound</span>. A breakdown of this time and advice for investigating further is in the <span class="cpu_span">CPU</span> section below.</p><p id="overview_advice">As very little time is spent in MPI calls, this code may also benefit from running at larger scales.</p></div>
+</div>
+<hr />
+<div class="subsections">
+    <div class="ltcol">
+        <div class="heading_cpu">CPU</div>
+        <div>A breakdown of how the <span class="cpu_span">88.6</span>% total CPU time was spent:</div>
+        <table id="cpu_chart">
+            <tr><td>Scalar numeric ops</td><td class="right_cell"><span class="cpu_num_span">50.0</span>%</td><td class="mini_bar_graph"><div id="cpu_num_bar" /></td></tr>
+            <tr><td>Vector numeric ops</td><td class="right_cell"><span class="cpu_vec_span">50.0</span>%</td><td class="mini_bar_graph"><div id="cpu_vec_bar" /></td></tr>
+            <tr><td>Memory accesses</td><td class="right_cell"><span class="cpu_mem_span">0.0</span>%</td><td class="mini_bar_graph"><div id="cpu_mem_bar" /></td></tr>
+            <tr><td>Other</td><td class="right_cell"><span class="cpu_other_span">0.0</span>%</td><td class="mini_bar_graph"><div id="cpu_other_bar" /></td></tr>
+        </table>
+        <div id="cpu_explanation">
+            <div class="explanation">The per-core performance is arithmetic-bound. Try to increase the amount of time spent in vectorized instructions by analyzing the compiler's vectorization reports.</div>
+            <div class="explanation"></div>
+        </div>
+    </div>
+    <div class="rtcol">
+        <div class="heading_mpi">MPI</div>
+        <div>Of the <span class="mpi_span">11.4</span>% total time spent in MPI calls:</div>
+        <table id="mpi_chart">
+            <tr><td>Time in collective calls</td><td class="right_cell"><span class="mpi_col_span">100.0</span>%</td><td class="mini_bar_graph"><div id="mpi_col_bar" /></td></tr>
+            <tr><td>Time in point-to-point calls</td><td class="right_cell"><span class="mpi_p2p_span">0.0</span>%</td><td class="mini_bar_graph"><div id="mpi_p2p_bar" /></td></tr>
+            <tr><td>Effective process collective rate</td><td class="right_cell"><span class="mpi_colrate_span"><span id="mpi_colrate_num">1.65e+02</span></span>&nbsp;<span id="mpi_colrate_units"></span></td><td class="mini_bar_graph"><div id="mpi_colrate_bar" /></td></tr>
+            <tr><td>Effective process point-to-point rate</td><td class="right_cell"><span class="mpi_p2prate_span"><span id="mpi_p2prate_num">0.00e+00</span></span>&nbsp;<span id="mpi_p2prate_units"></span></td><td class="mini_bar_graph"><div id="mpi_p2prate_bar" /></td></tr>
+        </table>
+        <div id="mpi_explanation">
+            <div class="explanation">Most of the time is spent in collective calls with a very low transfer rate. This suggests load imbalance is causing synchonization overhead; use an MPI profiler to investigate further.</div>
+            <div class="explanation"></div>
+        </div>
+    </div>
+    <div class="clear"></div>
+</div>
+<div class="subsections">
+    <div class="ltcol">
+        <div class="heading_io">I/O</div>
+        <div>A breakdown of how the <span class="io_span">0.0</span>% total I/O time was spent:</div>
+        <table id="io_chart">
+            <tr><td>Time in reads</td><td class="right_cell"><span class="io_read_span">0.0</span>%</td><td class="mini_bar_graph"><div id="io_read_bar" /></td></tr>
+            <tr><td>Time in writes</td><td class="right_cell"><span class="io_write_span">0.0</span>%</td><td class="mini_bar_graph"><div id="io_write_bar" /></td></tr>
+            <tr><td>Effective process read rate</td><td class="right_cell"><span class="io_readrate_span"><span id="io_readrate_num">0.00e+00</span></span>&nbsp;<span id="io_readrate_units"></span></td><td class="mini_bar_graph"><div id="io_readrate_bar" /></td></tr>
+            <tr><td>Effective process write rate</td><td class="right_cell"><span class="io_writerate_span"><span id="io_writerate_num">0.00e+00</span></span>&nbsp;<span id="io_writerate_units"></span></td><td class="mini_bar_graph"><div id="io_writerate_bar" /></td></tr>
+        </table>
+        <div id="io_explanation">
+            <div class="explanation">No time is spent in I/O operations. There's nothing to optimize here!</div>
+            <div class="explanation"></div>
+        </div>
+    </div>
+    <div class="rtcol">
+        <div class="heading_ram">Memory</div>
+        <div>Per-process memory usage may also affect scaling:</div>
+        <table id="ram_chart">
+            <tr><td>Mean process memory usage</td><td class="right_cell"><span class="ram_mean_span"><span id="ram_mean_num">2.33e+07</span></span>&nbsp;<span id="ram_mean_units"></span></td><td class="mini_bar_graph"><div id="ram_mean_bar" /></td></tr>
+            <tr><td>Peak process memory usage</td><td class="right_cell"><span class="ram_peak_span"><span id="ram_peak_num">2.35e+07</span></span>&nbsp;<span id="ram_peak_units"></span></td><td class="mini_bar_graph"><div id="ram_peak_bar" /></td></tr>
+            <tr><td>Peak node memory usage</td><td class="right_cell"><span class="ram_node_span">2.8</span>%</td><td class="mini_bar_graph"><div id="ram_node_bar" /></td></tr>
+        </table>
+        <div id="ram_explanation">
+            <div class="explanation">The peak node memory usage is very low. You may be able to reduce the amount of allocation time used by running with fewer MPI processes and more data on each process.</div>
+            <div class="explanation"></div>
+        </div>
+    </div>
+    <div class="clear"></div>
+</div>
+</div> <!-- content -->
+</body>
+</html>

docs.it4i/src/mympiprog_32p_2014-10-15_16-56.txt

+Executable:	mympiprog.x
+Resources:	32 processes, 2 nodes
+Machine:	cn182
+Started on:	Wed Oct 15 16:56:23 2014
+Total time:	7 seconds (0 minutes)
+Full path:	/home/user
+Notes:		
+
+Summary: mympiprog.x is CPU-bound in this configuration
+CPU:				  88.6% |========|
+MPI:				  11.4% ||
+I/O:				   0.0% |
+This application run was CPU-bound. A breakdown of this time and advice for investigating further is found in the CPU section below.
+As very little time is spent in MPI calls, this code may also benefit from running at larger scales.
+
+CPU:
+A breakdown of how the 88.6% total CPU time was spent:
+Scalar numeric ops:		   50.0% |====|
+Vector numeric ops:		   50.0% |====|
+Memory accesses:		    0.0% |
+Other:				    0.0% |
+The per-core performance is arithmetic-bound. Try to increase the amount of time spent in vectorized instructions by analyzing the compiler's vectorization reports.
+
+
+MPI:
+A breakdown of how the 11.4% total MPI time was spent:
+Time in collective calls:	  100.0% |=========|
+Time in point-to-point calls:	    0.0% |
+Effective collective rate:	1.65e+02 bytes/s
+Effective point-to-point rate:	0.00e+00 bytes/s
+Most of the time is spent in collective calls with a very low transfer rate. This suggests load imbalance is causing synchonization overhead; use an MPI profiler to investigate further.
+
+
+I/O:
+A breakdown of how the 0.0% total I/O time was spent:
+Time in reads:			    0.0% |
+Time in writes:			    0.0% |
+Effective read rate:		0.00e+00 bytes/s
+Effective write rate:		0.00e+00 bytes/s
+No time is spent in I/O operations. There's nothing to optimize here!
+
+
+Memory:
+Per-process memory usage may also affect scaling:
+Mean process memory usage:	2.33e+07 bytes
+Peak process memory usage:	2.35e+07 bytes
+Peak node memory usage:		    2.8% |
+The peak node memory usage is very low. You may be able to reduce the amount of allocation time used by running with fewer MPI processes and more data on each process.
+
+

docs.it4i/src/ompi/Hello.java

+/*
+    Licensed under the Apache License, Version 2.0 (the "License");
+    you may not use this file except in compliance with the License.
+    You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+    Unless required by applicable law or agreed to in writing, software
+    distributed under the License is distributed on an "AS IS" BASIS,
+    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+    See the License for the specific language governing permissions and
+    limitations under the License.
+*/
+/*
+ * Author of revised version: Franklyn Pinedo
+ *
+ * Adapted from Source Code in C of Tutorial/User's Guide for MPI by
+ * Peter Pacheco.
+ */
+/*
+ * Copyright (c) 2011      Cisco Systems, Inc.  All rights reserved.
+ *
+ */
+
+import mpi.*;
+
+class Hello {
+    static public void main(String[] args) throws MPIException {
+
+
+	MPI.Init(args);
+
+	int myrank = MPI.COMM_WORLD.getRank();
+	int size = MPI.COMM_WORLD.getSize() ;
+	System.out.println("Hello world from rank " + myrank + " of " + size);
+
+	MPI.Finalize();
+    }
+}

docs.it4i/src/ompi/Ring.java

+/*
+ * Copyright (c) 2011      Cisco Systems, Inc.  All rights reserved.
+ *
+ * Simple ring test program
+ */
+
+import mpi.* ;
+
+class Ring {
+    static public void main(String[] args) throws MPIException {
+
+
+	MPI.Init(args) ;
+
+	int source;  // Rank of sender
+	int dest;    // Rank of receiver
+	int tag=50;  // Tag for messages
+	int next;
+	int prev;
+	int message[] = new int [1];
+
+	int myrank = MPI.COMM_WORLD.getRank() ;
+	int size = MPI.COMM_WORLD.getSize() ;
+
+	/* Calculate the rank of the next process in the ring.  Use the
+	   modulus operator so that the last process "wraps around" to
+	   rank zero. */
+
+	next = (myrank + 1) % size;
+	prev = (myrank + size - 1) % size;
+
+	/* If we are the "master" process (i.e., MPI_COMM_WORLD rank 0),
+	   put the number of times to go around the ring in the
+	   message. */
+
+	if (0 == myrank) {
+	    message[0] = 10;
+
+	    System.out.println("Process 0 sending " + message[0] + " to rank " + next + " (" + size + " processes in ring)");
+	    MPI.COMM_WORLD.send(message, 1, MPI.INT, next, tag);
+	}
+
+	/* Pass the message around the ring.  The exit mechanism works as
+	   follows: the message (a positive integer) is passed around the
+	   ring.  Each time it passes rank 0, it is decremented.  When
+	   each processes receives a message containing a 0 value, it
+	   passes the message on to the next process and then quits.  By
+	   passing the 0 message first, every process gets the 0 message
+	   and can quit normally. */
+
+	while (true) {
+	    MPI.COMM_WORLD.recv(message, 1, MPI.INT, prev, tag);
+
+	    if (0 == myrank) {
+		--message[0];
+		System.out.println("Process 0 decremented value: " + message[0]);
+	    }
+
+	    MPI.COMM_WORLD.send(message, 1, MPI.INT, next, tag);
+	    if (0 == message[0]) {
+		System.out.println("Process " + myrank + " exiting");
+		break;
+	    }
+	}
+
+	/* The last process does one extra send to process 0, which needs
+	   to be received before the program can exit */
+
+	if (0 == myrank) {
+	    MPI.COMM_WORLD.recv(message, 1, MPI.INT, prev, tag);
+	}
+
+	MPI.Finalize();
+    }
+}