Computation on Programmable Graphics Hardware
GPUs have evolved into powerful and flexible streaming processors with fully programmable floating-point pipelines and tremendous aggregate computational power and memory bandwidth. With these advances, modern GPUs can now perform more functions than the specific graphics computations for which they were designed. This article describes approaches to using GPU processing power to accelerate traditionally CPU-based tasks. We discuss some important characteristics of algorithms that make them good candidates for GPU acceleration. We discuss a specific GPU image-processing application that is a common postprocess for many physically based rendering systems.

title: Efficient reconstruction of indoor scenes with color
abstract: We present an efficient and general approach to computing and integrating 3D distance fields directly from multiple range images. We compute normal and confidence values directly from a 2D range image. We then approximate 3D Euclidean distance by correcting the line-of-sight distance. To integrate multiple scans, we efficiently transform voxels of the target distance field to each scan's local coordinate system, then update voxels with computed distance and confidence values. Finally, we extract an iso-surface from the weighted distance field using the marching cubes algorithm. We extend the same idea to the assignment of weighted colors or texture coordinates to the reconstructed model. Experiments show that our approach is fast, has reasonable storage requirements, and can produce high-quality surfaces from multiple range scans.

title: All-frequency interactive relighting of translucent objects with single and multiple scattering
abstract: We present a technique, based on precomputed light transport, for interactive rendering of translucent objects under all-frequency environment maps. We consider the complete BSSRDF model proposed by Jensen et al. [2001]. which includes both single and diffuse multiple scattering components. The challenge is how to efficiently precompute all-frequency light transport functions due to subsurface scattering. We apply the two-pass hierarchical technique by Jensen et al. [2002] in the space of non-linearly approximated transport vectors, which allows us to efficiently evaluate transport vectors due to diffuse multiple scattering. We then include an approximated single scattering term in the precomputation, which previous interactive systems have ignored. For an isotropic phase function, this approximation produces a diffuse transport vector per vertex, and is combined with the multiple scattering component. For a general phase function, we introduce a technique from BRDF rendering to factor the phase function using a separable decomposition to allow for view-dependent rendering. We show that our rendering results qualitatively match the appearance of translucent objects, achieving a high level of realism at interactive rates.

title: All-Frequency Relighting of Non-Diffuse Objects using Separable BRDF Approximation
abstract: This paper presents a technique, based on pre-computed light transport and separable BRDF approximation, for interactive rendering of non-diffuse objects under all-frequency environment illumination. Existing techniques using spherical harmonics to represent environment maps and transport functions are limited to low-frequency light transport effects. Non-linear wavelet lighting approximation is able to capture all-frequency illumination and shadows for geometry relighting, but interactive rendering is currently limited to diffuse objects. Our work extends the wavelet-based approach to relighting of non-diffuse objects. We factorize the BRDF using separable decomposition and keep only a few low-order approximation terms, each consisting of a 2D light map paired with a 2D view map. We then pre-compute light transport matrices corresponding to each BRDF light map, and compress the data with a non-linear wavelet approximation. We use modern graphics hardware to accelerate precomputation. At run-time, a sparse light vector is multiplied by the sparse transport matrix at each vertex, and the results are further combined with texture lookups of the view direction into the BRDF view maps to produce view-dependent color. Using our technique, we demonstrate rendering of objects with several non-diffuse BRDFs under all-frequency, dynamic environment lighting at interactive rates.

title: Interactive Time-Dependent Tone Mapping Using Programmable Graphics Hardware

title: All-frequency relighting of glossy objects
abstract: We present a technique for interactive rendering of glossy objects in complex and dynamic lighting environments that captures interreflections and all-frequency shadows. Our system is based on precomputed radiance transfer and separable BRDF approximation. We factor glossy BRDFs using a separable decomposition and keep only a few low-order approximation terms, each consisting of a purely view-dependent and a purely light-dependent component. In the precomputation step, for every vertex, we sample its visibility and compute a direct illumination transport vector corresponding to each BRDF term. We use modern graphics hardware to accelerate this step and further compress the data using a nonlinear wavelet approximation. The direct illumination pass is followed by one or more interreflection passes, each of which gathers compressed transport vectors from the previous pass to produce global illumination transport vectors. To render at run time, we dynamically sample the lighting to produce a light vector, also represented in a wavelet basis. We compute the inner product of the light vector with the precomputed transport vectors, and the results are further combined with the BRDF view-dependent components to produce vertex colors. We describe acceleration of the rendering algorithm using programmable graphics hardware and discuss the limitations and trade-offs imposed by the hardware.

title: Online B-tree merging
abstract: Many scenarios involve merging of two B-tree indexes, both covering the same key range. Increasing demand for continuous availability and high performance requires that such merging be done online, with minimal interference to normal user transactions. In this paper we present an online B-tree merging method, in which the merging of leaf pages in two B-trees are piggybacked lazily with normal user transactions, thus making the merging I/O efficient and allowing user transactions to access only one index instead of both. The concurrency control mechanism is designed to interfere as little as possible with ongoing user transactions. Merging is made forward recoverable by following a conventional logging protocol, with a few extensions. Should a system failure occur, both indexes being merged can be recovered to a consistent state and no merging work is lost. Experiments and analysis show the I/O savings and the performance, and compare variations on the basic algorithm.

title: Mixed Reality-Mediated Collaborative Design System: Concept, Prototype, and Experimentation
abstract: This paper introduces a Mixed Reality-mediated Collaborative design system, named MR-Collab, which combines Mixed Reality (MR), Augmented Reality (AR) and various channels of communication technologies. The concept and system of MR-Collabare developed based on the Benford's Mixed-Reality boundaries theory. This paper presents how this theory is used as a tool to analyze the system framework and guide the design of the MR-Collabsystem. The technique details of prototype and application scenario of this system are also elaborated in the paper. The system, MR-Collab, is designed in the purpose of facilitating collaboration between distributed users through the Mixed Reality environment. Experimentation that can measure the correlations between the design performance/behaviors with the increased degree of co-presence is also planned in this paper.

title: Precomputed Radiance Transfer Field for Rendering Interreflections in Dynamic Scenes
abstract: In this paper, we introduce a new representation – radiance transfer fields (RTF) – for rendering interreflections in dynamic scenes under low frequency illumination. The RTF describes the radiance transferred by an individual object to its surrounding space as a function of the incident radiance. An important property of RTF is its independence of the scene configuration, enabling interreflection computation in dynamic scenes. Secondly, RTFs naturally fit in with the rendering framework of precomputed shadow fields, incurring negligible cost to add interreflection effects. In addition, RTFs can be used to compute interreflections for both diffuse and glossy objects. We also show that RTF data can be highly compressed by clustered principal component analysis (CPCA), which not only reduces the memory cost but also accelerates rendering. Finally, we present some experimental results demonstrating our techniques.

title: Recognizing Textual Entailment Using a Subsequence Kernel Method
abstract: We present a novel approach to recognizing Textual Entailment. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic dependency trees. These features are then applied in a subsequence-kernel-based classifier to learn whether an entailment relation holds between two texts. Our method makes use of machine learning techniques using a limited data set, no external knowledge bases (e.g. WordNet), and no handcrafted inference rules. We achieve an accuracy of 74.5% for text pairs in the Information Extraction and Question Answering task, 63.6% for the RTE-2 test data, and 66.9% for the RET-3 test data.

title: Privacy-preserving genomic computation through program specialization
abstract: In this paper, we present a new approach to performing important classes of genomic computations (e.g., search for homologous genes) that makes a significant step towards privacy protection in this domain. Our approach leverages a key property of the human genome, namely that the vast majority of it is shared across humans (and hence public), and consequently relatively little of it is sensitive. Based on this observation, we propose a privacy-protection framework that partitions a genomic computation, distributing the part on sensitive data to the data provider and the part on the pubic data to the user of the data. Such a partition is achieved through program specialization that enables a biocomputing program to perform a concrete execution on public data and a symbolic execution on sensitive data. As a result, the program is simplified into an efficient query program that takes only sensitive genetic data as inputs. We prove the effectiveness of our techniques on a set of dynamic programming algorithms common in genomic computing. We develop a program transformation tool that automatically instruments a legacy program for specialization operations. We also demonstrate that our techniques can greatly facilitate secure multi-party computations on large biocomputing problems.