The goal of this tutorial is to give an understanding of how to run sample workflows shipped with Airavata. Please refer to the quick start tutorials for basic understanding on how to construct and execute workflows.

These examples demonstrate using existing workflows and to provide some of the workflow capabilities. A simple and a complex math workflows and a Levenshtein distance examples are included with the binary distribution.

Start Airavata Server and Launch GUI

Before following the next instructions, make sure Airavata Server is up and running XBaya GUI is launched and Airavata Registry is configured from XBaya. Instructions are provided at Quick Start Tutorials introduction Page.

Import the workflow samples

  • Click the Xbaya tab and open up an Airavata workflow file (.xwf) from file system.
  • Sample workflows shipped in with Airavata can be found in $AIRAVATA_SERVER_HOME/samples/workflows.
  • Example load the SimpleMath workflow
    • Luanch the workflow by clicking on run button (red colored play).
    • After the workflow is executed the results are displayed in the monitoring panel.
    • The above steps can be repeated for other sample workflows as well.

Description of the sample workfllows

  • Simple math workflow: This workflow illustrates an example with multiple nodes which can be executed in parallel. After the first 4 parallel nodes are executes, the results are passed to the next set of 2 nodes. This example also illustartes how multiple instances of the same application can be used. All nodes in the workflow are doing addition operations.


  • Complex math workflow: This workflow is very similar to the simple math examples, except that there are a mix of both adder and multiplication operations. The goal of this example is to illustrate how to use different operations in a web service as each node in a workflow.


  • Levenshtein distance workflow: The goal of this example is to illustrate the parametric sweep capabilities to utilize iterations within a workflow. The number of iterations are determined at run time based on the array size of the for-each node. Both Cartesian and Dot product of inputs are suppported. This example calculates the Levenshtein Distance of strings. The workflow uses cross product to calculate the distance.