Virtualizing the Stampede2 Supercomputer with Applications to HPC in the Cloud

Methods developed at the Texas Advanced Computing Center (TACC) are described and demonstrated for automating the construction of an elastic, virtual cluster emulating the Stampede2 high performance computing (HPC) system. The cluster can be built and/or scaled in a matter of minutes on the Jetstream self-service cloud system and shares many properties of the original Stampede2, including: i) common identity management, ii) access to the same file systems, iii) equivalent software application stack and module system, iv) similar job scheduling interface via Slurm. We measure time-to-solution for a number of common scientific applications on our virtual cluster against equivalent runs on Stampede2 and develop an application profile where performance is similar or otherwise acceptable. For such applications, the virtual cluster provides an effective form of "cloud bursting" with the potential to significantly improve overall turnaround time, particularly when Stampede2 is experiencing long queue wait times. In addition, the virtual cluster can be used for test and debug without directly impacting Stampede2. We conclude with a discussion of how science gateways can leverage the TACC Jobs API web service to incorporate this cloud bursting technique transparently to the end user.Comment: 6 pages, 0 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US

Dynamic Reconfigurable Component for Cloud Computing Resources

In recent years a new concept of IT organization emerged, the Cloud Computing. With This new concept, the resources are dynamically scalable, virtualized and provided to users as a service on the Internet. It is primarily intended to meet the demands of users and allow them access to virtually unlimited resources. This model motivates many academic institutions and non-academics as well to develop open-source solutions to improve performance. Among these techniques, dynamic reconfiguration of cloud resources has to take an interest. In this paper an approach for optimization resources is presented, based on dynamic reconfiguration techniques. In fact, a Dynamic Reconfigurable Component (DRC) is proposed to be added to the cloud system, that optimize the use of cloud resources and enable dynamic resource allocation. Then, the implementation of this DRC component is provided