Engineering topics

Patchett, John

Publications and source records attributed to Patchett, John.

3 records

DOE OSTI2024

The ECP ALPINE project: In situ and post hoc visualization infrastructure and analysis capabilities for exascale

A significant challenge on an exascale computer is the speed at which we compute results exceeds by many orders of magnitude the speed at which we save these results. Therefore the Exascale Computing Project (ECP) ALPINE project focuses on providing exascale-ready visualization solutions including in situ processing. In situ visualization and analysis runs as the simulation is run, on simulations results are they are generated avoiding the need to save entire simulations to storage for later analysis. The ALPINE project made post hoc visualization tools, ParaView and VisIt, exascale ready and developed in situ algorithms and infrastructures. The suite of ALPINE algorithms developed under ECP includes novel approaches to enable automated data analysis and visualization to focus on the most important aspects of the simulation. Many of the algorithms also provide data reduction benefits to meet the I/O challenges at exascale. ALPINE developed a new lightweight in situ infrastructure, Ascent.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A terminology for in situ visualization and analysis systems

The term "in situ processing" has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and analysis scientists to communicate with each other and with their stakeholders. To address this problem, a group of over 50 experts convened with the goal of standardizing terminology. This paper summarizes their findings and proposes a new terminology for describing in situ systems. An important finding from this group was that in situ systems are best described via multiple, distinct axes: integration type, proximity, access, division of execution, operation controls, and output type. This paper discusses these axes, evaluates existing systems within the axes, and explores how currently used terms relate to the axes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2013

Ultrascale Visualization of Climate Data

Fueled by exponential increases in the computational and storage capabilities of high-performance computing platforms, climate simulations are evolving toward higher numerical fidelity, complexity, volume, and dimensionality. These technological breakthroughs are coming at a time of exponential growth in climate data, with estimates of hundreds of exabytes by 2020. To meet the challenges and exploit the opportunities that such explosive growth affords, a consortium of four national laboratories, two universities, a government agency, and two private companies formed to explore the next wave in climate science. Working in close collaboration with domain experts, the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) project aims to provide high-level solutions to a variety of climate data analysis and visualization problems.

analysis tools↗