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.

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.