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Resource-Elasticity Support for Distributed Memory HPC Applications

Large simulations are executed in HPC systems. These systems are shared among users with a resource manager. There are ranges of resource allocations where simulations perform efficiently, but are usually unknown before execution. Unfortunately, resource allocations cannot be modified at runtime in current systems. A resource manager and MPI library combination is proposed in this work. These allow for changes in the resource allocations of running applications. Changes are made continuously based on performance feedback to optimize system-wide efficiency metrics.