High-resolution Display Walls Research Articles

2023 IEEE Scientific Visualization Contest Winner: VisAnywhere: Developing Multi-platform Scientific Visualization Applications.

Scientists often explore and analyze large-scale scientific simulation data by leveraging two- and three-dimensional visualizations. The data and tasks can be complex and therefore best supported using myriad display technologies, from mobile devices to large high-resolution display walls to virtual reality headsets. Using a simulation of neuron connections in the human brain provided for the 2023 IEEE Scientific Visualization Contest, we present our work leveraging various web technologies to create a multi-platform scientific visualization application. Users can spread visualization and interaction across multiple devices to support flexible user interfaces and both co-located and remote collaboration. Drawing inspiration from responsive web design principles, this work demonstrates that a single codebase can be adapted to develop scientific visualization applications that operate everywhere.

Research on Human-Computer Interaction Technology of Large-Scale High-Resolution Display Wall System

As an effective solution for data visualization and analysis, the large-scale high-resolution display wall system has been widely used in various scientific research fields. On the basis of investigating existing system cases and research results, this paper introduces the SHU-VAS system (60 screens, 120 megapixels) for data visualization and analysis. In order to improve the efficiency of human-computer interaction in large-scale high-definition display wall systems, we propose an interaction framework based on gesture and double-precision pointing technology. During the interaction process, an adaptive mode switching method based on user action features is used to switch between rough and precise control modes. In the evaluation experiments, we analyzed the characteristics of different interaction methods in movement and navigation interaction tasks, and verified the effectiveness of the gesture-based interaction framework proposed in this paper.

Virtual Machine Based High-Resolution Display Wall: Experiments on Proof of Concept

Virtual Machine Based High-Resolution Display Wall: Experiments on Proof of Concept

Visualizing potential energy curves and conformations on ultra high-resolution display walls

In this contribution, we examine how visualization on an ultra high-resolution display wall can augment force-field research in the field of molecular modeling. Accurate force fields are essential for producing reliable simulations, and subsequently important for several fields of applications (e.g. rational drug design and biomolecular modeling). We discuss how using HORNET, a recently constructed specific ultra high-resolution tiled display wall, enhances the visual analytics that are necessary for conformational-based interpretation of the raw data from molecular calculations. Simultaneously viewing multiple potential energy graphs and conformation overlays leads to an enhanced way of evaluating force fields and in their optimization. Consequently, we have integrated visual analytics into our existing Wolf2Pack workflow. We applied this workflow component to analyze how major AMBER force fields (Parm14SB, Gaff, Lipid14, Glycam06j) perform at reproducing the quantum mechanics relative energies and geometries of saturated hydrocarbons. Included in this comparison are the 1996 OPLS force field and our newly developed ExTrM force field. While we focus on atomistic force fields the ideas presented herein are generalizable to other research areas, particularly those that involve numerous representations of large data amounts and whose simultaneous visualization enhances the analysis.

Multiuser-centered resource scheduling for collaborative display wall environments

The popularity of large-scale, high-resolution display walls, as visualization endpoints in eScience infrastructure, is rapidly growing. These displays can be connected to distributed computing resources over high-speed network, providing effective means for researchers to visualize, interact with, and understand large volumes of datasets. Typically large display walls are built by tiling multiple physical displays together and running a tiled display wall required a cluster of computers. With the advent of advanced graphics hardware, a single computer can now drive over a dozen displays, thereby greatly reducing the cost of ownership and maintenance of a tiled display wall system. This in turn enables a broader user base to take advantage of such technologies. Since tiled display walls are also well suited to collaborative work, users tend to launch and operate multiple applications simultaneously. To ensure that applications maintain a high degree of responsiveness to the users even under heavy use loads, the display wall must now ensure that the limited system resources are prioritized to maximize interactivity rather than thread-level fair sharing or overall job-completion throughput. In this paper, we present a new resource scheduling scheme that is specifically designed to prioritize responsiveness in collaborative large display wall environments where multiple users can interact with multiple applications simultaneously. We evaluate our scheduling scheme with a user study involving groups of users interacting simultaneously on a tiled display wall with multiple applications. Results show that our scheduling framework provided a higher frame-rate for applications, which led to a significantly higher user performance (approx. 25%) in a target acquisition test when compared against traditional operating system scheduling scheme.

Special section: OptIPlanet — The OptIPuter global collaboratory

The popularity of large-scale, high-resolution display walls, as visualization endpoints in eScience infrastructure, is rapidly growing. These displays can be connected to distributed computing resources over high-speed network, providing effective means for researchers to visualize, interact with, and understand large volumes of datasets. Typically large display walls are built by tiling multiple physical displays together and running a tiled display wall required a cluster of computers. With the advent of advanced graphics hardware, a single computer can now drive over a dozen displays, thereby greatly reducing the cost of ownership and maintenance of a tiled display wall system. This in turn enables a broader user base to take advantage of such technologies. Since tiled display walls are also well suited to collaborative work, users tend to launch and operate multiple applications simultaneously. To ensure that applications maintain a high degree of responsiveness to the users even under heavy use loads, the display wall must now ensure that the limited system resources are prioritized to maximize interactivity rather than thread-level fair sharing or overall job-completion throughput. In this paper, we present a new resource scheduling scheme that is specifically designed to prioritize responsiveness in collaborative large display wall environments where multiple users can interact with multiple applications simultaneously. We evaluate our scheduling scheme with a user study involving groups of users interacting simultaneously on a tiled display wall with multiple applications. Results show that our scheduling framework provided a higher frame-rate for applications, which led to a significantly higher user performance (approx. 25%) in a target acquisition test when compared against traditional operating system scheduling scheme.

Display Wall Empowered Visual Mining for CEOP Data Archive

A large display space potentially improves data exploration, especially when where there are several types of data sets to control. To better understand the feasibility of a large display space, we implemented a display wall assisted visual mining system. A 5 m × 2.5 m display allows users to simultaneously visualize various types of data. The system also has a very high resolution of 15 XGA displays (each XGA display has 1024 pixel × 768 pixel resolution). With these attributes, the user can easily examine and visualize a dense data set in detail. To our knowledge, few systems of this type that are easy to use have been realized. A number of systems are now functional (e.g., the NASA AMES Hyperwall, http://www.nas.nasa.gov/Groupsl/VisTech/hyperwall/). However, these systems require much knowledge and power of the user. Most users of such systems have to use some special application, which can be difficult for earth environmental researchers. Although the proposed system has had limited testing by some researchers, we believe that our experience would be helpfu1 for users who are trying to develop similar systems. The proposed system is more efficient as it allows for simultaneous multi-dimensional visualization of complex data products, and various mining functions, such as two-dimensional correlation, are also prepared for the Coordinated Enhanced Observing Period (CEOP) data archive. By using these functions, various advanced analyses that are not easily utilized with conventional mining tools are attained. Moreover, several scenarios using the powerful capability of this tool are also presented. Finally, the process of data analysis in the proposed system becomes much more efficient through the use of a large-scale high-resolution display wall.

Visualization of multi-scale dynamics of hydrous cold plumes at subduction zones

Recent increases in the computational power of high-performance computing systems have led to a large gap between the high-resolution runs of numerical simulations—typically approaching 50–100 million tracers and 1–5 million grid points in two dimensions—and the modest resolution of 1–2 million pixels for conventional display devices. This technical problem is further compounded by the variety of fields produced by numerical simulations and the limited bandwidth available through the Internet in the course of collaborative ventures. We have developed a visualization system using the paradigm of web-based inquiry to address these mounting problems. We have employed, as a case study, a problem involving two-dimensional multi-scale dynamics of hydrous cold plumes at subduction zones. A Lagrangian marker method, in which the number of markers varies dynamically, is used to delineate the many different fields, such as temperature, viscosity, strain, and chemical composition. We found commercially available software to be insufficient for our visualization needs and so we were driven to develop a new set of tools tailored to high-resolution, multi-aspect, multi-scale simulations, and adaptable to many other applications in which large datasets involving tens of millions of tracers with many different fields are prevalent. In order to address this gap in visualization techniques, we have developed solutions for remote visualization and for local visualization. Our remote visualization solution is a web-based, zoomable image service (WEB-IS) that requires minimal bandwidth while allowing the user to explore our data through time, across many thermo–physical properties, and through different spatial scales. For local visualization, we found it optimal to use bandwidth-intensive, high-resolution display walls for performing parallel visualization in order to best comprehend the causal and temporal relationships between the multiple physical and chemical properties in a simulation.