Efficient data processing is critical for interactive visualization of analytic data sets. Inspired by the large amount of recent research on column-oriented stores, we have developed a new specialized analytic data engine tightly-coupled with the Tableau data visualization system. The Tableau Data Engine ships as an integral part of Tableau 6.0 and is intended for the desktop and server environments. This paper covers the main requirements of our project, system architecture and query-processing pipeline. We use real-life visualization scenarios to illustrate basic concepts and provide experimental evaluation.

We describe WireGL, a system for scalable interactive rendering on a cluster of workstations. WireGL provides the familiar OpenGL API to each node in a cluster, virtualizing multiple graphics accelerators into a sort-first parallel renderer with a parallel interface. We also describe techniques for reassembling an output image from a set of tiles distributed over a cluster. Using flexible display management, WireGL can drive a variety of output devices, from standalone displays to tiled display walls. By combining the power of virtual graphics, the familiarity and ordered semantics of OpenGL, and the scalability of clusters, we are able to create time-varying visualizations that sustain rendering performance over 70,000,000 triangles per second at interactive refresh rates using 16 compute nodes and 16 rendering nodes.

Clusters of PCs are increasingly popular as cost-effective platforms for supercomputer-class applications. Given recent performance improvements in graphics accelerators, clusters are similarly attractive for demanding graphics applications. We describe the design and implementation of Lightning-2, a display subsystem for such a cluster. The system scales in both the number of rendering nodes and the number of displays supported, and allows any pixel data generated from any node to be dynamically mapped to any location on any display. A number of image-compositing functions are supported, including color-keying and depth-compositing. A distinguishing feature of the system is its platform independence: it connects to graphics accelerators via an industry-standard digital video port and requires no modifications to accelerator hardware or device drivers. As a result, rendering clusters that utilize Lightning-2 can be upgraded across multiple generations of graphics accelerators with little effort. We demonstrate a renderer that achieves 106 Mtri/s on an 8-node cluster using Lightning-2 to perform sort-last depth compositing.

We describe a novel distributed graphics system that allows an application to render to a large tiled display. Our system, called WireGL, uses a cluster of off-the-shelf PCs connected with a high-speed network. WireGL allows an unmodified existing application to achieve scalable output resolution on such a display. This paper presents an efficient sorting algorithm which minimizes the network traffic for a scalable display. We will demonstrate that for most applications, our system provides scalable output resolution with minimal performance impact.

Pomegranate is a parallel hardware architecture for polygon rendering that provides scalable input bandwidth, triangle rate, pixel rate, texture memory and display bandwidth while maintaining an immediate-mode interface. The basic unit of scalability is a single graphics pipeline, and up to 64 such units may be combined. Pomegranate's scalability is achieved with a novel “sort-everywhere” architecture that distributes work in a balanced fashion at every stage of the pipeline, keeping the amount of work performed by each pipeline uniform as the system scales. Because of the balanced distribution, a scalable network based on high-speed point-to-point links can be used for communicating between the pipelines.