Technology have long been a partner of workplace meeting facilitation. The recent outbreak of COVID-19 and the cautionary measures to reduce its spread have made it more prevalent than ever before in the form of online-meetings. In this paper, we recount our experiences during weekly meetings in three modalities: using SAGE2 - a collaborative sharing software designed for large displays - for co-located meetings, using a conventional projector for co-located meetings, and using the Zoom video-conferencing tool for distributed meetings. We view these meetings through the lens of effective meeting attributes and share ethnographic observations and attitudinal survey conducted in our research lab. We discuss patterns of content sharing, either sequential, parallel, or semi-parallel, and the potential advantages of creating complex canvases of content. We see how the SAGE2 tool affords parallel content sharing to create complex canvases, which represent queues of ideas and contributions (past, present, and future) using the space on a large display to suggest the progression of time through the meeting.

SAGE (the Scalable Adaptive Graphics Environment) and its successor SAGE2 (the Scalable Amplified Group Environment) are operating systems for managing content across wideband display environments. This paper documents the prevalent usage patterns of SAGE-enabled display walls in support of the e-Science enterprise, based on nearly 15 years of observations of the SAGE community. These patterns will help guide e-Science users and cyberinfrastructure developers on how best to leverage large tiled display walls, and the types of software services that could be provided in the future.

In today's Big Data era, data scientists require new computational instruments in order to quickly analyze large-scale datasets using complex codes and quicken the rate of scientific progress. While Federally-funded computer resources, from supercomputers to clouds, are beneficial, they are often limiting - particularly for deep learning and visualization - as they have few Graphics Processing Units (GPUs). GPUs are at the center of modern high-performance computing and artificial intelligence, efficiently performing mathematical operations that can be massively parallelized, speeding up codes used for deep learning, visualization and image processing, more so than general-purpose microprocessors, or Central Processing Units (CPUs). The University of Illinois at Chicago is acquiring a much-in-demand GPU-based instrument, COMPaaS DLV - COMposable Platform as a Service Instrument for Deep Learning & Visualization, based on composable infrastructure, an advanced architecture that disaggregates the underlying compute, storage, and network resources for scaling needs, but operates as a single cohesive infrastructure for management and workload purposes. We are experimenting with a small system and learning a great deal about composability, and we believe COMPaaS DLV users will benefit from the varied workflow that composable infrastructure allows.

Mixed presence collaboration involves remote collaboration between multiple collocated groups. This paper presents the design and results of a user study that focused on mixed presence collaboration using large-scale tiled display walls. The research was conducted in order to compare data synchronization schemes for multi-user visualization applications. Our study compared three techniques for sharing data between display spaces with varying constraints and affordances. The results provide empirical evidence that using data sharing techniques with continuous synchronization between the sites lead to improved collaboration for a search and analysis task between remotely located groups. We have also identified aspects of synchronized sessions that result in increased remote collaborator awareness and parallel task coordination. It is believed that this research will lead to better utilization of large-scale tiled display walls for distributed group work.

Real world group-to-group collaboration often occurs between partially distributed interdisciplinary teams, with each discipline working in a unique environment suited for its needs. Groupware must be flexible so that it can be incorporated into a variety of workspaces in order to successfully facilitate this type of mixed presence collaboration. We have developed two new techniques for sharing and synchronizing multi-user applications between heterogeneous large-scale shared displays. The first new technique partitions displays into a perfectly mirrored public space and a local private space. The second new technique enables user-controlled partial synchronization, where different attributes of an application can be synchronized or controlled independently. This paper presents two main contributions of our work: 1) identifying deficiencies in current groupware for interacting with data during mixed presence collaboration, and 2) developing two multi-user data synchronization techniques to address these deficiencies and extend current collaborative infrastructure for large-scale shared displays.

Current web-based collaboration systems, such as Google Hangouts, WebEx, and Skype, primarily enable single users to work with remote collaborators through video conferencing and desktop mirroring. The original SAGE software, developed in 2004 and adopted at over one hundred international sites, was

In the domain of large-scale visualization instruments, hybrid reality environments (HREs) are a recent innovation that combines the best-in-class capabilities of immersive environments, with the best-in-class capabilities of ultra-high-resolution display walls. HREs create a seamless 2D/3D environment that supports both information-rich analysis as well as virtual reality simulation exploration at a resolution matching human visual acuity. Co-located research groups in HREs tend to work on a variety of tasks during a research session (sometimes in parallel), and these tasks require 2D data views, 3D views, linking between them and the ability to bring in (or hide) data quickly as needed. In this paper we present Omegalib, a software framework that facilitates application development on HREs. Omegalib is designed to support dynamic reconfigurability of the display environment, so that areas of the display can be interactively allocated to 2D or 3D workspaces as needed. Compared to existing frameworks and toolkits, Omegalib makes it possible to have multiple immersive applications running on a cluster-controlled display system, have different input sources dynamically routed to applications, and have rendering results optionally redirected to a distributed compositing manager. Omegalib supports pluggable front-ends, to simplify the integration of third-party libraries like OpenGL, OpenSceneGraph, and the Visualization Toolkit (VTK). We present examples of applications developed with Omegalib for the 74-megapixel, 72-tile CAVE2™ system, and show how a Hybrid Reality Environment proved effective in supporting work for a co-located research group in the environmental sciences.

This video describes the CAVE2 Hybrid Reality Environment developed by the Electronic Visualization Laboratory (EVL) at the University of Illinois at Chicago (UIC). CAVE2 is a near-seamless flat-panel-based, surround-screen immersive system that can simultaneously display both 2D and 3D information, providing more flexibility for mixed media applications and more opportunities for groups of researchers to work together with large heterogeneous datasets [1]. CAVE2 is a cylindrical system of 24 feet in diameter and 8 feet tall, and consists of 72 near-seamless, off-axis-optimized passive-stereo LCD panels, creating a 320-degree panoramic environment for displaying information at 37 Megapixels (in stereoscopic 3D) or 74 Megapixels in 2D and at a horizontal visual acuity of 20/20 [2]. Custom LCD panels with shifted polarizers were built so the images in the top and bottom rows of LCDs are optimized for vertical off-center viewing, allowing viewers to come closer to the displays while minimizing ghosting. EVL's Omegalib middleware supports fully immersive OpenGL, OpenSceneGraph and VTK applications, as well as EVL's SAGE middleware to achieve a hybrid 2D/3D environment. CAVE2 also supports CalVR (developed at the Calit2 Qualcomm Institute at University of California, San Diego), Electro (by Robert Kooima, currently at Louisiana State University) and Google Earth.

This article will describe the progress since 2000 on research and development in 2-D and 3-D scalable resolution display walls that are built from tiling individual lower resolution flat panel displays. The article will describe approaches and trends in display hardware construction, middleware architecture, and user-interaction design. The article will also highlight examples of use cases and the benefits the technology has brought to their respective disciplines.

Ultra-high-resolution tiled-display walls are typically driven by a cluster of computers. Each computer may drive one or more displays. Synchronization between the computers is necessary to ensure that animated imagery displayed on the wall appears seamless. Most tiled-display middleware systems are designed around the assumption that only a single application instance is running in the tiled display at a time. Therefore synchronization can be achieved with a simple solution such as a networked barrier. When a tiled display has to support multiple applications at the same time, however, the simple networked barrier approach does not scale. In this paper we propose and experimentally validate two synchronization algorithms to achieve low-latency, intertile synchronization for multiple applications with independently varying frame rates. The two-phase algorithm is more generally applicable to various highresolution tiled display systems. The one-phase algorithm provides superior results but requires support for the Network Time Protocol and is more CPU-intensive.

We present a novel rails approach so that future e-Science applications can effectively exploit future system architectures, including multi-core and many-core architectures, multiple network cards, multiple graphical processing units and hybrid hierarchical memory architectures. We define "rail" as the co-scheduling of two or more of these resources. This approach enables creation of parallel multi-rails through every aspect of an end system: from processing on the multi- and many cores, to generation of multiple data flows and streaming over multi-lane network interface card (NIC) connected via a parallel interconnect. We describe a novel open-source multi-rail toolkit and the evaluation of end-system parameters that impact the efficiency of such multi-rail systems, including Interrupt, Memory, Thread and Core Affinities -- key properties for achieving scalable performance.

LambdaGrid applications as typified by data-intensive collaborative visualization are likely to be the first users of terabit-level networking. This paper features a main enabler of collaborative visualization over LambdaGrid, the Scalable Adaptive Graphics Environment (SAGE) in particular, and anticipates the future needs of LambdaGrid applications in general. We present a scalable architecture called LambdaBridge to 'bridge' LambdaGrid applications with the terabit optical core networks. LambdaBridge will provision and control predictable- performance networks for end-systems (i.e. Grid clusters) using on-demand lambda/VLAN provisioning and end-system traffic shaping. The chief contribution of LambdaBridge is a deep understanding of how to synergistically bridge provisionable networks, end-systems, and future generation distributed terabit applications. This paper also introduces Scalable Visualcasting - a multicasting service for LambdaGrid that incorporates IP multicasting and optical multicasting.

The Scalable Adaptive Graphics Environment (SAGE) is specialized middleware for enabling data, high-definition video and extremely high-resolution graphics to be streamed in real-time from remotely distributed rendering and storage clusters to scalable display walls over ultra-high-speed networks. In this paper, we present the SAGE architecture, focusing on its dynamic graphics streaming capability. In the SAGE framework, multiple visualization applications can be streamed to large tiled displays and viewed at the same time. The application windows can be moved, resized and overlapped like any standard desktop window manager. Every window movement or resize operation requires dynamic and non-trivial reconfiguration of the involved graphics streams. This approach has been successfully shown to scale to support streaming on the LambdaVision 100 Megapixel display wall. SAGE is now being extended to support distance collaboration with multiple endpoints by streaming visualization to all the participants.

JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive prefetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization.

In electronically mediated distance collaborations involving scientific data, there is often the need to stream the graphical output of individual computers or entire visualization clusters to remote displays. This work presents TeraVision as a scalable platform-independent solution which is capable of transmitting multiple synchronized high-resolution video streams between single workstations and/or clusters without requiring any modifications to be made to the source or destination machines. Issues addressed include: how to synchronize individual video streams to form a single larger stream; how to scale and route streams generated by an array of M/spl times/N nodes to fit a X/spl times/Y display; and how TeraVision exploits a variety of transport protocols. Results from experiments conducted over gigabit local-area networks and wide-area networks (between Chicago and Amsterdam), are presented. Finally, we propose the scalable adaptive graphics environment (SAGE) - an architecture to support future collaborative visualization environments with potentially billions of pixels.

We present the current state of Vol-a-Tile, an interactive tool for exploring large volumetric data on scalable tiled displays. Vol-a-Tile presents a variety of features employed by scientists at the Scripps Institution of Oceanography on data collected from the Anatomy of a Ridge-Axis Discontinuity seismic experiment. Hardware texture mapping and level-of-detail techniques provide interactivity. A high-performance network protocol is used to connect remote data sources over high-bandwidth photonic networks.

We present the CAVEStudy system that enables scientists to interactively steer a simulation from a virtual reality (VR) environment. No modification to the source code is necessary. CAVEStudy allows interactive and immersive analysis of a simulation running on a remote computer. Using a high-level description of the simulation, the system generates the communication layer (based on CAVERN-Soft) needed to control the execution and to gather data at runtime. We describe three case-studies implemented with CAVEStudy: soccer simulation, diode laser simulation and molecular dynamics.

We discuss the use of virtual reality (VR) techniques for interaction between humans and a multi-agent system in the context of RoboCup. The goal of RoboCup is to let teams of cooperating autonomous agents play a soccer match, using either robots or simulated players. We use RoboCup to study distributed collaborative applications, which allow multiple users at different geographic locations to cooperate, by interacting in real time through a shared simulation program. Our objective is to construct a VR environment in which humans at different locations can play along with a running RoboCup simulation in a natural way. The simulation system consists of the Soccer Server and a set of processes modeling the players. The server keeps track of the state of the game: provides the players with information on the game, and enforces the rules. The players request state information and autonomously calculate a behavior, sending the server commands that consist of accelerations, turns and kicks. The server discretizes time into slots, only one command is executed per time slot. We have developed a 3D visualization system that allows a user in a CAVE to interact with the soccer simulation software.