Managing Heterogeneous Resources in HPC Systems

To sustain performance while facing always tighter power and energy envelopes, High Performance Computing (HPC) is increasingly leveraging heterogeneous architectures. This poses new challenges: to efficiently exploit the available resources, both in terms of hardware and energy, resource management must support a wide range of different heterogeneous devices and programming models that target different application domains. We present a strategy for resource management and programming model support for heterogeneous accelerators for HPC systems with requirements targeting performance, power and predictability. We show how resource management can, in addition to allowing multiple applications to share a set of resources, reduce the burden on the application developer and improve the efficiency of resource allocation.