Zeroing memory deallocator to reduce checkpoint sizes in virtualized HPC environments

Virtualization has become an indispensable tool in data centers and cloud environments to flexibly assign virtual machines (VMs) to resources. Virtualization also becomes more and more attractive for high-performance computing (HPC). This is mainly due to the strong isolation of VMs which enables: (1) the sharing of cluster nodes and optimization of the system’s overall utilization; (2) load balancing by means of migrations due to the reduction of residual dependencies; and (3) the creation of system-level checkpoints increasing the fault tolerance in an application-transparent way. On the downside, the additional virtualization layer conceals information that is only available on the process level. This information has a direct influence on the checkpoint size which should be kept as small as possible. In this paper, we propose a novel technique for checkpoint size reduction in virtualized environments. We exploit the fact that the hypervisor detects zero pages which are omitted when capturing a checkpoint. Moreover, compression techniques are applied for a further reduction of the checkpoint size. We therefore fill freed memory regions with zeros supporting both the zero-page detection and the compression. We evaluate our approach by taking the example of HPC applications. The results reveal a reduction of the checkpoint size by up to 9% when compression is disabled in the hypervisor and up to 49% with compression enabled. Furthermore, memory zeroing is able to reduce VM migration time by up to 10% when compression is disabled and by up to 60% when compression is enabled

Virtualization as an enabler for dynamic resource allocation in HPC

This dissertation explores the viability of virtualization techniques to address the challenges that arise from current developments in High Performance Computing (HPC). In doing so, it follows a system-level approach enabling a more flexible utilization of the resources in supercomputers. It presents a state-of-the-art analysis of virtualization in HPC and derives a set of requirements for its efficient support in this domain. These requirements build the foundation for the virtualization-aware communication stack that has been developed as part of this work. Firstly, the communication stack enables the seamless migration of Message-Passing Interface (MPI) processes in HPC clusters while meeting the performance demands of the HPC domain. And secondly, it supports locality-awareness and topology-awareness in virtual clusters. Its viability is demonstrated by taking the example of co-scheduling. In doing so, this dissertation presents an extension to the prototype co-scheduler ``Poor Man's Co-Scheduler'' (poncos). This extension has been developed to investigate the feasibility of dynamic co-scheduling based on the applications' main memory bandwidth consumption. The concepts proposed by this dissertation support a more flexible assignment of the resources. This allows cluster maintainers to improve the overall system utilization

MPI Benchmarks: First release

Collection of MPI benchmark