  High intensive computation applications can usually take days to months to
finish an execution. During this time, it is common to have variations of the
available resources when considering that such hardware is usually shared among
a plurality of researchers/departments within an organization. On the other
hand, High Performance Clusters can take advantage of Cloud Computing bursting
techniques for the execution of applications together with the on-premise
resources. In order to meet deadlines, high intensive computational
applications can use the Cloud to boost their performance when they are data
and task parallel. This article presents an ongoing work towards the use of
extended resources of an HPC execution platform together with Cloud. We propose
an unified view of such heterogeneous environments and a method that monitors,
predicts the application execution time, and dynamically shifts part of the
domain -- previously running in local HPC hardware -- to be computed on the
Cloud, meeting then a specific deadline. The method is exemplified along with a
seismic application that, at runtime, adapts itself to move part of the
processing to the Cloud (in a movement called bursting) and also auto-scales
(the moved part) over cloud nodes. Our preliminary results show that there is
an expected overhead for performing this movement and for synchronizing
results, but our outcomes demonstrate it is an important feature for meeting
deadlines in the case an on-premise cluster is overloaded or cannot provide the
capacity needed for a particular project.
