One frequently cited reason for the lack of wide deployment of cryptographic protocols is the (perceived) poor performance of the algorithms they employ and their impact on the rest of the system. Although high-performance dedicated cryptographic accelerator cards have been commercially available for some time, market penetration remains low. We take a different approach, seeking to exploit existing system resources, such as Graphics Processing Units (GPUs) to accelerate cryptographic processing.

Non-linear filtering is an important task for volume analysis. This paper presents hardware-based implementations of various nonlinear filters for volume smoothing with edge preservation. The Cg high-level shading language is used in combination with latest PC consumer graphics hardware. Filtering is divided into pervertex and per-fragment stages. In both stages we propose techniques to increase the filtering performance. The vertex program pre-computes texture coordinates in order to address all contributing input samples of the operator mask. Thus additional computations are avoided in the fragment program. The presented fragment programs preserve cache coherence, exploit 4D vector arithmetic, and internal fixed point arithmetic to increase performance. We show the applicability of non-linear filters as part of a GPU-based segmentation pipeline. The resulting binary mask is compressed and decompressed in the graphics memory on-the-fly.

Data-parallel programs are both growing in importance and increasing in diversity, resulting in specialized processors targeted at specific classes of these programs. This paper presents a classification scheme for data-parallel program attributes, and proposes micro-architectural mechanisms to support applications with diverse behavior using a single reconfigurable architecture. We focus on the following four broad kinds of data-parallel programs --- DSP/multimedia, scientific, networking, and real-time graphics workloads. While all of these programs exhibit high computational intensity, coarse-grain regular control behavior, and some regular memory access behavior, they show wide variance in the computation requirements, fine grain control behavior, and the frequency of other types of memory accesses. Based on this study of application attributes, this paper proposes a set of general micro-architectural mechanisms that enable a baseline architecture to be dynamically tailored to the demands of a particular application. These mechanisms provide efficient execution across a spectrum of data-parallel applications and can be applied to diverse architectures ranging from vector cores to conventional superscalar cores. Our results using a baseline TRIPS processor show that the configurability of the architecture to the application demands provides harmonic mean performance improvement of 5%--55% over scalable yet less flexible architectures, and performs competitively against specialized architectures.

Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. This paper describes how fine grained parallel genetic algorithms can be mapped to programmable graphics hardware found in commodity PC. Our approach stores chromosomes and their fitness values in texture memory on graphics card. Both fitness evaluation and genetic operations are implemented entirely with fragment programs executed on graphics processing unit in parallel. We demonstrate the effectiveness of our approach by comparing it with compatible software implementation. The presented approach allows us benefit from the advantages of parallel genetic algorithms on low-cost platform.

Abstract. Software that covertly monitors user actions, also known as spyware, has become a first-level security threat due to its ubiquity and the difficulty of detecting and removing it. Such software may be inadvertently installed by a user that is casually browsing the web, or may be purposely installed by an attacker or even the owner of a system. This is particularly problematic in the case of utility computing, early manifestations of which are Internet cafes and thin-client computing. Traditional trusted computing approaches offer a partial solution to this by significantly increasing the size of the trusted computing base (TCB) to include the operating system and other software. We examine the problem of protecting a user accessing specific services in such an environment. We focus on secure video broadcasts and remote desktop access when using any convenient, and often untrusted, terminal as two example applications. We posit that, at least for such applications, the TCB can be confined to a suitably modified graphics processing unit (GPU). Specifically, to prevent spyware on untrusted clients from accessing the user’s data, we restrict the boundary of trust to the client’s GPU by moving image decryption into GPUs. We use the GPU in order to leverage existing capabilities as opposed to designing a new component from scratch. We discuss the applicability of GPU-based decryption in these two sample scenarios and identify the limitations of the current generation of GPUs. We propose straightforward modifications to future GPUs that will allow the realization of the full approach. 1

Assistant Professor: Marcus Hudritsch

Computer-based simulation is an important tool for surgical skills training and assessment. In general, the degree of realism experienced by the trainees is determined by the visual and biomechanical fidelity of the simulator. In minimally invasive surgery, specular reflections provide an important visual cue for tissue deformation, depth and orientation. This paper describes a novel image-based lighting technique that is particularly suitable for modeling mucous-covered tissue surfaces. We describe how noise functions can be used to control the shape of the specular highlights, and how texture noise is generated and encoded in image-based structure at a pre-processing stage. The proposed technique can be implemented at run-time by using the graphics processor to efficiently attain pixel-level control and photo-realism. The practical value of the technique is assessed with detailed visual scoring and cross comparison experiments by two groups of observers.

Abstract: Computer-based surgical simulations are being increasingly used for training and skills assessment. They provide an efficient and cost effective alternative to traditional training methods. To allow for both basic and advanced skills assessment, the required perceptual fidelity is essential to capturing the natural behavior of the operator. The level of realism in terms of object and scene appearance determines the faithfulness and hence the degree of immersion experienced by the trainee in the virtual world. This paper presents a novel photo-realistic rendering approach based on real-time per-pixel effects by using the graphics hardware. Improved realism is achieved by a combined use of specular reflectance and refractance maps to model the effect of surface details and mucous layer on the overall visual appearance of the tissue. The key steps involved in the proposed technique are described, and quantitative performance assessment results demonstrate the practical advantages of the proposed technique. 1

Abstract: With this document we will present an overview of artificial intelligence in general and artificial intelligence in the context of its use in modern computer games in particular. To this end we will firstly provide an introduction to the terminology of artificial intelligence, followed by a brief history of this field of computer science and finally we will discuss the impact which this science has had on the development of computer games. This will be further illustrated by a number of case studies, looking at how artificially intelligent behaviour has been achieved in selected games.

Realistic visualizations of 3D city models require the availability of detailed geometric descriptions of the visible buildings. Especially, if virtual viewpoints from a pedestrian perspective have to be generated, texture images have to be additionally available. For this purpose geo-referenced terrestrial images have to be captured and mapped against the corresponding elements of the building model. By these means the large scale structure and the material of the building faces can be visually represented. In our approach this texture mapping is realized using a programmable graphics processing unit. In contrast to the application of standard viewers, this technique allows to model even complex geometric effects like self-occlusion or lens distortion. This allows for a very fast and flexible on-the-fly generation of façade texture using real world imagery. Our approach was implemented within a project aiming on the real-time visualization of urban landscapes, which will be discussed in the final part of the paper.