A typical parameter sweep application (PSA) is a parameterized application which has to be executed independently large number of times, to locate a particular point in the parameter space that satisfies certain criteria.??Albeit simple in terms of computational model, parameter sweep studies occurs frequently in scientific computation across a broad range of scientific disciplines cite(Olabarriaga2007, ADDA, Stankovski2007, Sudholt2005). Including human knowledge in the runtime loop of parameter sweep application is essential to improve the efficiency of performing parameter sweep experiments. However, existing frameworks for performing parameter sweep such as Nimrod-G focuses mainly on the scheduling and the management of the computing resources required for the execution of PSAs. We argued that the batch based execution in existing frameworks hampers the inclusion of human expertise in runtime loop of parameter sweep, and we propose a new framework for interactive parameter sweep.