System-Level Support for Composition of Applications

ABSTRACT Current HPC system software lacks support for emerging application deployment scenarios that combine one or more simulations with in situ analytics, sometimes called multi-component or multi-enclave applications. This paper presents an initial design study, implementation, and evaluation of mechanisms supporting composite multi-enclave applications in the Hobbes exascale operating system. These mechanisms include virtualization techniques isolating application custom enclaves while using the vendor-supplied host operating system and high-performance inter-VM communication mechanisms. Our initial single-node performance evaluation of these mechanisms on multi-enclave science applications, both real and proxy, demonstrate the ability to support multi-enclave HPC job composition with minimal performance overhead

Scheduling Heterogeneous HPC Applications in Next-Generation Exascale Systems

Next generation HPC applications will increasingly time-share system resources with emerging workloads such as in-situ analytics, resilience tasks, runtime adaptation services and power management activities. HPC systems must carefully schedule these co-located codes in order to reduce their impact on application performance. Among the techniques traditionally used to mitigate the performance effects of time- share systems is gang scheduling. This approach, however, leverages global synchronization and time agreement mechanisms that will become hard to support as systems increase in size. Alternative performance interference mitigation approaches must be explored for future HPC systems. This dissertation evaluates the impacts of workload concurrency in future HPC systems. It uses simulation and modeling techniques to study the performance impacts of existing and emerging interference sources on a selection of HPC benchmarks, mini-applications, and applications. It also quantifies the cost and benefits of different approaches to scheduling co-located workloads, studies performance interference mitigation solutions based on gang scheduling, and examines their synchronization requirements. To do so, this dissertation presents and leverages a new Extreme Value Theory- based model to characterize interference sources, and investigate their impact on Bulk Synchronous Parallel (BSP) applications. It demonstrates how this model can be used to analyze the interference attenuation effects of alternative fine-grained OS scheduling approaches based on periodic real time schedulers. This analysis can, in turn, guide the design of those mitigation techniques by providing tools to understand the tradeoffs of selecting scheduling parameters