Grant Wallace

Scalable alignment of large-format multi-projector displays using camera homography trees

This paper presents a vision-based geometric alignment system for aligning the projectors in an arbitrarily large display wall. Existing algorithms typically rely on a single camera view and degrade in accuracy as the display resolution exceeds the camera resolution by several orders of magnitude. Naive approaches to integrating multiple zoomed camera views fail since small errors in aligning adjacent views propagate quickly over the display surface to create glaring discontinuities. Our algorithm builds and refines a camera homography tree to automatically register any number of uncalibrated camera images; the resulting system is both faster and significantly more accurate than competing approaches, reliably achieving alignment errors of 0.55 pixels on a 24-projector display in under 9 minutes. Detailed experiments compare our system to two recent display wall alignment algorithms, both on our 18 Megapixel display wall and in simulation. These results indicate that our approach achieves sub-pixel accuracy even on displays with hundreds of projectors.

WAN-optimized replication of backup datasets using stream-informed delta compression

Replicating data off site is critical for disaster recovery reasons, but the current approach of transferring tapes is cumbersome and error prone. Replicating across a wide area network (WAN) is a promising alternative, but fast network connections are expensive or impractical in many remote locations, so improved compression is needed to make WAN replication truly practical. We present a new technique for replicating backup datasets across a WAN that not only eliminates duplicate regions of files (deduplication) but also compresses similar regions of files with delta compression, which is available as a feature of EMC Data Domain systems. Our main contribution is an architecture that adds stream-informed delta compression to already existing deduplication systems and eliminates the need for new, persistent indexes. Unlike techniques based on knowing a files version or that use a memory cache, our approach achieves delta compression across all data replicated to a server at any time in the past. From a detailed analysis of datasets and statistics from hundreds of customers using our product, we achieve an additional 2X compression from delta compression beyond deduplication and local compression, which enables customers to replicate data that would otherwise fail to complete within their backup window.

Tools and applications for large-scale display walls

Increased processor and storage capacities have supported the computational sciences, but have simultaneously unleashed a data avalanche on the scientific community. As a result, scientific research is limited by data analysis and visualization capabilities. These new bottlenecks have been the driving motivation behind the Princeton scalable display wall project. To create a scalable and easy-to-use large-format display system for collaborative visualization, the authors have developed various techniques, software tools, and applications.

Software environments for cluster-based display systems

An inexpensive way to construct a scalable display wall system is to use a cluster of PCs with commodity graphics accelerators to drive an array of projectors. A challenge is to bring off-the-shelf sequential applications to run on such a display wall efficiently without using expensive, high-performance interconnects. We study two execution models for a scalable display wall system: master-slave and synchronized execution models. We have designed and implemented four software tools, two for each execution model, including VDD (Virtual Display Driver), GLP (GL-DLL Replacement), SSE (System-level Synchronized Execution), and ASE (Application-level Synchronized Execution). In order to support the synchronized execution model, we have also designed a broadcast, speculative file cache to provide scalable I/O performance. We report our experimental results with several 3D applications on the display wall to understand the performance implications and tradeoffs of these methods.

Color gamut matching for tiled display walls

This paper presents a non-parametric full-gamut color matching algorithm. Color matching is important for the seamless appearance of tiled displays. In particular we address the case where the tiled display is composed of different types of projectors or DLP projectors with white enhancement. White enhancement produces a non-additive color space that is difficult to model. We perform our calibration using an inexpensive colorimeter as opposed to a highly accurate spectroradiometer. Our results show that we can achieve good color balance with 1.47% variance between projectors. We present a method for applying this color gamut mapping in real-time on the newest commodity graphics cards.

Data distribution strategies for high-resolution displays

Abstract Large-scale and high-resolution displays are increasingly being used for next-generation interactive 3D graphics applications, including large-scale data visualization, immersive virtual environments, and collaborative design. These systems must include a very high-performance and scalable 3D rendering subsystem in order to generate high-resolution images at real-time frame rates. We are investigating how to build such a system using only inexpensive commodity components in a PC cluster. The main challenge is to develop scalable algorithms to partition and distribute rendering tasks effectively under the bandwidth, processing, and storage constraints of a distributed system. In this paper, we compare three different approaches that differ in the type of data transmitted from client to display servers: control, primitives, or pixels. For each approach, we describe our initial experiments with a working prototype system driving a multi-projector display wall with a PC cluster. We find that different approaches are suitable for different system architectures, with the best choice depending on the communication bandwidth, storage capacity, and processing power of the clients and display servers.

Viewing the Larger Context of Genomic Data through Horizontal Integration

Genomics is an important emerging scientific field that relies on meaningful data visualization as a key step in analysis. Specifically, most investigation of gene expression microarray data is performed using visualization techniques. However, as microarrays become more ubiquitous, researchers must analyze their own data within the context of previously published work in order to gain a more complete understanding. No current method for microarray visualization and analysis enables biology researchers to observe the greater context of data that surrounds their own results, which severely limits the ability of researchers draw novel conclusions. Here we present a system, called HIDRA, that visually integrates the simultaneous display of multiple microarray datasets to identify important parallels and dissimilarities. We demonstrate the power of our approach through examples of real-world biological insights that can be observed using HIDRA that are not apparent using other techniques.

Dynamic scalable visualization for collaborative scientific applications

Science disciplines are experiencing a data avalanche. As a result, scientific research is limited by data analysis and visualization capabilities. We have been working closely with genomic and plasma physics researchers on effective data visualization software tools. This paper reports our research on developing software tools for high-resolution display walls to alleviate the current limitation on visualization resolution and single-user window system. In the first case, we developed a novel data visualization tools for genomic data visualization that is dynamic and scale free. In the second case, we have developed a multi-cursor window system for shared data visualization for a collaborative environment. We have deployed both software tools to the scientific researchers. Our initial feedbacks show that these approaches have made significant impact on their productivity.

Pannier: A Container-based Flash Cache for Compound Objects

Classic caching algorithms leverage recency, access count, and/or other properties of cached blocks at per-block granularity. However, for media such as flash which have performance and wear penalties for small overwrites, implementing cache policies at a larger granularity is beneficial. Recent research has focused on buffering small blocks and writing in large granularities, called containers, but it has not explored the ramifications and best strategies for caching compound blocks consisting of logically distinct, but physically co-located, blocks. Containers may have highly diverse blocks, with mixtures of frequently accessed, infrequently accessed, and invalidated blocks. We propose and evaluate Pannier, a flash cache middleware that provides high performance while extending flash lifespan. Pannier uses three main techniques: (1) leveraging block access counts to manage cache containers, (2) incorporating block liveness as a property to improve flash cache space efficiency, and (3) designing a multi-step feedback controller to ensure a flash cache does not wear out in its lifespan while maintaining performance. Our evaluation shows that Pannier improves flash cache performance and extends lifespan beyond previous per-block and container-aware caching policies. More fundamentally, our investigation highlights the importance of creating new policies for caching compound blocks in flash.

Systems support for remote visualization of genomics applications over wide area networks

Microarray experiments can provide molecular-level insight into a variety of biological processes, from yeast cell cycle to tumorogenesis. However, analysis of both genomic and protein microarray data requires interactive collaborative investigation by biology and bioinformatics researchers. To assist collaborative analysis, remote collaboration tools for integrative analysis and visualization of microarray data are necessary. Such tools should: (i) provide fast response times when used with visualization-intensive genomics applications over a low-bandwidth wide area network, (ii) eliminate transfer of large and often sensitive datasets, (iii) work with any analysis software, and (iv) be platform-independent. Existing visualization systems do not satisfy all requirements. We have developed a remote visualization system called Varg that extends the platform-independent remote desktop system VNC with a novel global compression method. Our evaluations show that the Varg system can support interactive visualization-intensive genomic applications in a remote environment by reducing bandwidth requirements from 30:1 to 289:1.