A task scheduling algorithm for HPC applications using colored stochastic Petri Net models

The increase in demand for High Performance Computing (HPC) scientific applications motivates the efforts to reduce costs of running these applications. The problem to solve is that of dynamical multi-criterial optimal scheduling of an application on a HPC platform with a high number of heterogeneous nodes. The solution proposed by the authors is a HPC hardware-software architecture that includes the infrastructure for two level (node and inter-node level) adaptive load balancing. The article presents the development of an Coloured Petri Net(CPN) for such an architecture. The model was used for the development of a dynamic distributed algorithm for the scheduling problem. The CPN allowed a holistic hardware-software formal verification and analysis. Some simple properties were formally proofed. Simulations were performed to assess performance and the results were in the performance range of other load balancing algorithms with significant benefits in reducing the optimization's complexity.