Numerical and adaptive grid methods for ideal magnetohydrodynamics

In this thesis numerical finite difference methods for ideal magnetohydrodynamics (MHD) are investigated. A review of the relevant physics, essential for interpreting the results of numerical solutions and constructing validation cases, is presented. This review includes a discusion of the propagation of small amplitude waves in the MHD system as well as a thorough discussion of MHD shocks, contacts and rarefactions and how they can be pieced together to obtain a solutions to the MHD Riemann problem. Numerical issues relevant to the MHD system such as: the loss of nonlinear numerical stability in the presence of discontinuous solutions, the introduction of spurious forces due to the growth of the divergence of the magnetic flux density, the loss of pressure positivity, and the effects of non-conservative numerical methods are discussed, along with the practical approaches which can be used to remedy or minimize the negative consequences of each. The use of block structured adaptive mesh refinement is investigated in the context of a divergence free MHD code. A new method for conserving magnetic flux across AMR grid interfaces is developed and a detailed discussion of our implementation of this method using the CHOMBO AMR framework is given. A preliminary validation of the new method for conserving magnetic flux density across AMR grid interfaces illustrates that the method works. Finally a number of code validation cases are examined spurring a discussion of the strengths and weaknesses of the numerics employed

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved

Epidemiology and outcomes of gastroparesis, as documented in general practice records, in the United Kingdom

Objective To generate real-world evidence for the epidemiology of gastroparesis in the UK, we evaluated the prevalence, incidence, patient characteristics and outcomes of gastroparesis in the Clinical Practice Research Datalink (CPRD) database. Design This was a retrospective, cross-sectional study. Prevalence and incidence of gastroparesis were evaluated in the CPRD database, with linkage to Hospital Episodes Statistics Admitted Patient Care and Office for National Statistics mortality data. Prevalence and incidence were age and sex standardised to mid-2017 UK population estimates. Descriptive analyses of demographics, aetiologies, pharmacological therapies and mortality were conducted. Results Standardised prevalence of gastroparesis, as documented in general practice records, was 13.8 (95% CI 12.6 to 15.1) per 100 000 persons in 2016, and standardised incidence of gastroparesis rose from 1.5 (95% CI 1.1 to 1.8) per 100 000 person-years in 2004 to 1.9 (95% CI 1.4 to 2.3) per 100 000 person-years in 2016. The most common disease aetiologies were idiopathic (39.4%) and diabetic gastroparesis (37.5%), with a similar distribution of type 1 and type 2 diabetes among the 90% who had type of diabetes documented. Patients with diabetic gastroparesis had a significantly higher risk of mortality than those with idiopathic gastroparesis after diagnosis (adjusted HR 1.9, 95% CI 1.2 to 3.0). Of those with gastroparesis, 31.6% were not offered any recognised pharmacological therapy after diagnosis. Conclusion This is, to our knowledge, the first population-based study providing data on epidemiology and outcomes of gastroparesis in Europe. Further research is required to fully understand the factors influencing outcomes and survival of patients with gastroparesis

The Ets-1 transcription factor controls the development and function of natural regulatory T cells

Regulatory T cells (T reg cells) constitute a population of CD4+ T cells that limits immune responses. The transcription factor Foxp3 is important for determining the development and function of T reg cells; however, the molecular mechanisms that trigger and maintain its expression remain incompletely understood. In this study, we show that mice deficient for the Ets-1 transcription factor (Ets-1−/−) developed T cell–mediated splenomegaly and systemic autoimmunity that can be blocked by functional wild-type T reg cells. Spleens of Ets-1−/− mice contained mostly activated T cells, including Th2-polarized CD4+ cells and had reduced percentages of T reg cells. Splenic and thymic Ets-1−/− T reg cells expressed low levels of Foxp3 and displayed the CD103 marker that characterizes antigen-experienced T reg cells. Thymic development of Ets-1−/− T reg cells appeared intrinsically altered as Foxp3-expressing cells differentiate poorly in mixed fetal liver reconstituted chimera and fetal thymic organ culture. Ets-1−/− T reg cells showed decreased in vitro suppression activity and did not protect Rag2−/− hosts from naive T cell–induced inflammatory bowel disease. Furthermore, in T reg cells, Ets-1 interacted with the Foxp3 intronic enhancer and was required for demethylation of this regulatory sequence. These data demonstrate that Ets-1 is required for the development of natural T reg cells and suggest a role for this transcription factor in the regulation of Foxp3 expression

Rendering and Compositing Infrastructure Improvements to VisIt for Insitu Rendering:

Compared to posthoc rendering, insitu rendering often generates larger numbers of images, as a result rendering performance and scalability are critical in the insitu setting. In this work we present improvements to VisIt's rendering and compositing infrastructure that deliver increased performance and scalability in both posthoc and insitu settings. We added the capability for alpha blend compositing and use it with ordered compositing when datasets have disjoint block domain decomposition to optimize the rendering of transparent geometry. We also made improvements that increase overall efficiency by reducing communication and data movement and have addressed a number of performance issues. We structured our code to take advantage of SIMD parallelization and use threads to overlap communication and compositing. We tested our improvements on a 20 core workstation using 8 cores to render geometry generated from a $256^3$ cosmology dataset and on a Cray XC31 using 512 cores to render geometry generated from a $2000^2 \times 800$ plasma dataset. Our results show that ordered compositing provides a speed up of up to $4 \times$ over the current sort first strategy. The other improvements resulted in modest speed up with one notable exception where we achieve up to $40 \times$ speed up of rendering and compositing of opaque geometry when both opaque and transparent geometry are rendered together. We also investigated the use of depth peeling, but found that the implementation provided by VTK is substantially slower,both with and without GPU acceleration, than a local camera order sort

Rendering and Compositing Infrastructure Improvements to VisIt for Insitu Rendering:

Compared to posthoc rendering, insitu rendering often generates larger numbers of images, as a result rendering performance and scalability are critical in the insitu setting. In this work we present improvements to VisIt's rendering and compositing infrastructure that deliver increased performance and scalability in both posthoc and insitu settings. We added the capability for alpha blend compositing and use it with ordered compositing when datasets have disjoint block domain decomposition to optimize the rendering of transparent geometry. We also made improvements that increase overall efficiency by reducing communication and data movement and have addressed a number of performance issues. We structured our code to take advantage of SIMD parallelization and use threads to overlap communication and compositing. We tested our improvements on a 20 core workstation using 8 cores to render geometry generated from a $256^3$ cosmology dataset and on a Cray XC31 using 512 cores to render geometry generated from a $2000^2 \times 800$ plasma dataset. Our results show that ordered compositing provides a speed up of up to $4 \times$ over the current sort first strategy. The other improvements resulted in modest speed up with one notable exception where we achieve up to $40 \times$ speed up of rendering and compositing of opaque geometry when both opaque and transparent geometry are rendered together. We also investigated the use of depth peeling, but found that the implementation provided by VTK is substantially slower,both with and without GPU acceleration, than a local camera order sort