Scalarm supports the data farming methodology, which is gaining more and more popularity recently in the context of studying complex phenomena. Data farming organizes scientific research in experiments with a well defined worklow as depicted in Fig. 1. It is similar to parameter studies as the same application is executed many times with different input parameters but data farming focuses more on experiment design and results analysis. More on data farming can be found here.
Scalarm is a platform for conducting data farming experiments with heterogeneous computational infrastructure. For end users, e.g. analysts, Scalarm provides a complete solution, which can be used to prepare an experiment, monitor the progress of computations and analyze results with different statistical methods. Moreover, Scalarm makes it very easy to run a given application on different types of resources, starting with private physical machines, through computer clusters, to grid environmnets and compute clouds. The platform consists of loosely coupled services as depicted in Fig. 2. It follows the 'master-worker' design pattern, where each part intends to be a self-scaleble service. More on the Scalarm internal structure can be found here.
To demonstrate how Scalarm works in practice, we prepared a quick start demonstration. It shows how you can install Scalarm on your own machine and start using it with an example application.