AdaPNet: Adapting process networks in response to resource variations

A widely considered strategy to prevent interference issues on multi-processor systems is to isolate the execution of the individual applications by running each of them on a dedicated virtual guest machine. The amount of computing power available to a single application, however, depends on the other applications running on the system and may change over time. A promising approach to maximize the performance under such conditions is to adapt the application's degree of parallelism when the resources allocated to the application are changed. This enables an application to exploit not more parallelism than required, thereby reducing inter-process communication and scheduling overheads. In this paper, we introduce AdaPNet, a run-time system to execute streaming applications, which are modeled as process networks, efficiently on platforms with dynamic resource al-location. AdaPNet responds to changes in the available resources by first calculating a process network that maximizes the performance of the application on the new resources. Then, AdaPNet transparently transforms the application into the alternative network without discarding the program state. Targeting two many-core systems, we demonstrate that AdaPNet outperforms comparable run-time systems, which do not adapt the degree of parallelism, in terms of speed-up and memory usage.