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  1. WarpVisit is an insitu simulation application that integrates the Warp laser plasma accelerator simulation framework with Visit a parallel visualization application. WarpVisit is written in python and supports interactive or live mode where user can connect to Warp with the Visit GUI and batch mode for batch for non-interactive use on high-performance computing resources.
  2. The United Nations Framework Convention on Climate Change (UNFCCC) invited the scientific community to explore the impacts of a world in which anthropogenic global warming is stabilized at only 1.5°C above preindustrial average temperatures. In this paper, we present a projection of future tropical cyclone statistics for both 1.5 and 2.0°C stabilized warming scenarios with direct numerical simulation using a high-resolution global climate model. As in similar projections at higher warming levels, we find that even at these low warming levels the most intense tropical cyclones become more frequent and more intense, while simultaneously the frequency of weaker tropical stormsmore » is decreased. We also conclude that in the 1.5°C stabilization, the effect of aerosol forcing changes complicates the interpretation of greenhouse gas forcing changes.« less
  3. The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not.more » We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.« less
  4. Fibers provide exceptional strength-to-weight ratio capabilities when woven into ceramic composites, transforming them into materials with exceptional resistance to high temperature, and high strength combined with improved fracture toughness. Microcracks are inevitable when the material is under strain, which can be imaged using synchrotron X-ray computed micro-tomography (mu-CT) for assessment of material mechanical toughness variation. An important part of this analysis is to recognize fibrillar features. This paper presents algorithms for detecting and quantifying composite cracks and fiber breaks from high-resolution image stacks. First, we propose recognition algorithms to identify the different structures of the composite, including matrix cracks andmore » fibers breaks. Second, we introduce our package F3D for fast filtering of large 3D imagery, implemented in OpenCL to take advantage of graphic cards. Results show that our algorithms automatically identify micro-damage and that the GPU-based implementation introduced here takes minutes, being 17x faster than similar tools on a typical image file.« less
  5. 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 amore » $256^3$ 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.« less
  6. The SENSEI generic in situ interface is an API that promotes code portability and reusability. From the simulation view, a developer can instrument their code with the SENSEI API and then make make use of any number of in situ infrastructures. From the method view, a developer can write an in situ method using the SENSEI API, then expect it to run in any number of in situ infrastructures, or be invoked directly from a simulation code, with little or no modification. This paper presents the design principles underlying the SENSEI generic interface, along with some simplified coding examples.
  7. The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less
  8. A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. Our paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: Scalability, overhead,more » performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.« less

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"Loring, Burlen"

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