From Bare Metal to Virtual: Lessons Learned when a Supercomputing Institute Deploys its First Cloud

As primary provider for research computing services at the University of Minnesota, the Minnesota Supercomputing Institute (MSI) has long been responsible for serving the needs of a user-base numbering in the thousands. In recent years, MSI---like many other HPC centers---has observed a growing need for self-service, on-demand, data-intensive research, as well as the emergence of many new controlled-access datasets for research purposes. In light of this, MSI constructed a new on-premise cloud service, named Stratus, which is architected from the ground up to easily satisfy data-use agreements and fill four gaps left by traditional HPC. The resulting OpenStack cloud, constructed from HPC-specific compute nodes and backed by Ceph storage, is designed to fully comply with controls set forth by the NIH Genomic Data Sharing Policy. Herein, we present twelve lessons learned during the ambitious sprint to take Stratus from inception and into production in less than 18 months. Important, and often overlooked, components of this timeline included the development of new leadership roles, staff and user training, and user support documentation. Along the way, the lessons learned extended well beyond the technical challenges often associated with acquiring, configuring, and maintaining large-scale systems.Comment: 8 pages, 5 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US

Recovering Residual Forensic Data from Smartphone Interactions with Cloud Storage Providers

There is a growing demand for cloud storage services such as Dropbox, Box, Syncplicity and SugarSync. These public cloud storage services can store gigabytes of corporate and personal data in remote data centres around the world, which can then be synchronized to multiple devices. This creates an environment which is potentially conducive to security incidents, data breaches and other malicious activities. The forensic investigation of public cloud environments presents a number of new challenges for the digital forensics community. However, it is anticipated that end-devices such as smartphones, will retain data from these cloud storage services. This research investigates how forensic tools that are currently available to practitioners can be used to provide a practical solution for the problems related to investigating cloud storage environments. The research contribution is threefold. First, the findings from this research support the idea that end-devices which have been used to access cloud storage services can be used to provide a partial view of the evidence stored in the cloud service. Second, the research provides a comparison of the number of files which can be recovered from different versions of cloud storage applications. In doing so, it also supports the idea that amalgamating the files recovered from more than one device can result in the recovery of a more complete dataset. Third, the chapter contributes to the documentation and evidentiary discussion of the artefacts created from specific cloud storage applications and different versions of these applications on iOS and Android smartphones

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

A heuristic approach for the allocation of resources in large-scale computing infrastructures

An increasing number of enterprise applications are intensive in their consumption of IT, but are infrequently used. Consequently, organizations either host an oversized IT infrastructure or they are incapable of realizing the benefits of new applications. A solution to the challenge is provided by the large-scale computing infrastructures of Clouds and Grids which allow resources to be shared. A major challenge is the development of mechanisms that allow efficient sharing of IT resources. Market mechanisms are promising, but there is a lack of research in scalable market mechanisms. We extend the Multi-Attribute Combinatorial Exchange mechanism with greedy heuristics to address the scalability challenge. The evaluation shows a trade-off between efficiency and scalability. There is no statistical evidence for an influence on the incentive properties of the market mechanism. This is an encouraging result as theory predicts heuristics to ruin the mechanism’s incentive properties. Copyright © 2015 John Wiley & Sons, Ltd

The potential for diagnosing high blood pressure at the dentist: an examination of periodontal disease and the oral microbiome in raised blood pressure.

Background: Hypertension is increasingly linked to periodontitis. However, the nature and specific mechanistic relationship of this remains unclear, however may involve reduced oral and systemic nitric oxide (NO) availability. There remains limited research on the oral microbiome during hypertension that could support such a causative mechanism involving NO.Aims: This project aimed to examine links between periodontal disease, the oral microbiome, and raised blood pressure, while establishing a cardiovascular risk case-finding clinic with a GP referral pathway.Methods: The project comprised three studies: Study I established and identified cardiovascular risk case-finding in a dental environment (n=200). Study II evaluated clinical markers and diagnoses of periodontitis obtained in dental clinics, against blood pressure readings (n=91). Study III collected oral saliva samples to measure the composition of bacterial populations, and bacterial activity (n=75). Results: Study I: 71.4% return rate for case-finding (n=200). Undiagnosed hypertension detected in 31.5% of participants. 4.5% of the population were confirmed with undiagnosed hypertension by their GP. Study II: Increased systolic blood pressure (SBP) demonstrated a positive association with the presence of periodontitis and deeper periodontal pocket depths (PPD ≥ 6mm) (Adjusted model: F[12,43]=3.085, P=0.003). Study III: Saliva in R-BP had a significantly higher oral nitrate reducing activity (ONRA) compared to N-BP (N-BP=322.7µM±233.8µM; R-BP=484.6µM±438.5µM; P=0.027). The abundance of oral nitrate reducing bacteria (ONRB) was also increased in R-BP (P\u3c0.0001), differences maintained when controlling for poor oral health. Increased abundance of Neisseria flavascens and Neisseria subflava were identified in R-BP. R-BP showed significantly lower ammonia levels (N-BP=63.4mg/L±41.0mg/L; R-BP=42.7mg/L±36.4mg/L; P=0.005). Conclusions: This project shows primary care dental clinics can effectively identify cardiovascular risk, whilst supporting literature linking periodontitis to R-BP, and suggests future studies on increased ONRA/ONRB as compensatory mechanisms in R-BP patients

Distributed Model-to-Model Transformation with ATL on MapReduce

International audienceEfficient processing of very large models is a key requirement for the adoption of Model-Driven Engineering (MDE) in some industrial contexts. One of the central operations in MDE is rule-based model transformation (MT). It is used to specify manipulation operations over structured data coming in the form of model graphs. However, being based on com-putationally expensive operations like subgraph isomorphism, MT tools are facing issues on both memory occupancy and execution time while dealing with the increasing model size and complexity. One way to overcome these issues is to exploit the wide availability of distributed clusters in the Cloud for the distributed execution of MT. In this paper, we propose an approach to automatically distribute the execution of model transformations written in a popular MT language, ATL, on top of a well-known distributed programming model, MapReduce. We show how the execution semantics of ATL can be aligned with the MapReduce computation model. We describe the extensions to the ATL transformation engine to enable distribution, and we experimentally demonstrate the scalability of this solution in a reverse-engineering scenario

The Clinical Importance of the Heterogeneity of HER2 neu

We report on a patient with breast cancer in whom there were areas of the tumor that were 3+ positive and negative for HER2 neu by immunohistochemistry, adjacent to each other. Depending on the area tested the results were completely different. The clinical implications are important. We recommend retesting a large portion of the tumor in all cases of initially negative test results

New Digital Ways of Delivering Sex Education: A Practice Perspective

This article explores new, under-researched genres of sex education for adolescents in sub-Saharan Africa resulting from access to the internet through mobile phones. It examines the history of developing online health information platforms tailored for youth through the experiences of digital developers and the reflections of users. Unlike traditional sources of sex education, the internet offers portability, anonymity, informality, ‘personalised’ responses, and the ability to interact with peers who are not local or part of face-to-face networks. This article draws on a literature review, complemented by qualitative and quantitative material generated by Every1Mobile in its production of online health communities for young people. We found massive enthusiasm for online sex education in Africa but little knowledge about how young people use, perceive and respond to this. We recommend that practitioners, funders and researchers invest more in understanding not only the many fantastic opportunities associated with digital sexual and reproductive health and rights (SRHR) information, but also the interwoven contradictions, challenges and potential for misuse