Rendering Falling Leaves on Graphics Hardware

There is a growing interest in simulating natural phenomena in computer graphics applications. Animating natural scenes in real time is one of the most challenging problems due to the inherent complexity of their structure, formed by millions of geometric entities, and the interactions that happen within. An example of natural scenario that is needed for games or simulation programs are forests. Forests are difficult to render because the huge amount of geometric entities and the large amount of detail to be represented. Moreover, the interactions between the objects (grass, leaves) and external forces such as wind are complex to model. In this paper we concentrate in the rendering of falling leaves at low cost. We present a technique that exploits graphics hardware in order to render thousands of leaves with different falling paths in real time and low memory requirements.

Hardware accelerated ray cast of volume data and volume gradient for an optimized splines-based multi-resolution 2D-3D registration

This paper describes a method for DRR generation as well as for volume gradients projection using hardware accelerated 2D texture mapping and accumulation buffering and demonstrates its application in 2D-3D registration of X-ray fluoroscopy to CT images. The robustness of the present registration scheme are guaranteed by taking advantage of a coarse-to-fine processing of the volume/image pyramids based on cubic B-splines. A human cadaveric spine specimen together with its ground truth was used to compare the present scheme with a purely software-based scheme in three aspects: accuracy, speed, and capture ranges. Our experiments revealed an equivalent accuracy and capture ranges but with much shorter registration time with the present scheme. More specifically, the results showed 0.8 mm average target registration error, 55 second average execution time per registration, and 10 mm and 10° capture ranges for the present scheme when tested on a 3.0 GHz Pentium 4 computer.

Fourier transform convolution integrals applied to generalized Born molecular volume.

Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

A Co-Processor Approach for Efficient Java Execution in Embedded Systems

This thesis deals with a hardware accelerated Java virtual machine, named REALJava. The REALJava virtual machine is targeted for resource constrained embedded systems. The goal is to attain increased computational performance with reduced power consumption. While these objectives are often seen as trade-offs, in this context both of them can be attained simultaneously by using dedicated hardware. The target level of the computational performance of the REALJava virtual machine is initially set to be as fast as the currently available full custom ASIC Java processors. As a secondary goal all of the components of the virtual machine are designed so that the resulting system can be scaled to support multiple co-processor cores. The virtual machine is designed using the hardware/software co-design paradigm. The partitioning between the two domains is flexible, allowing customizations to the resulting system, for instance the floating point support can be omitted from the hardware in order to decrease the size of the co-processor core. The communication between the hardware and the software domains is encapsulated into modules. This allows the REALJava virtual machine to be easily integrated into any system, simply by redesigning the communication modules. Besides the virtual machine and the related co-processor architecture, several performance enhancing techniques are presented. These include techniques related to instruction folding, stack handling, method invocation, constant loading and control in time domain. The REALJava virtual machine is prototyped using three different FPGA platforms. The original pipeline structure is modified to suit the FPGA environment. The performance of the resulting Java virtual machine is evaluated against existing Java solutions in the embedded systems field. The results show that the goals are attained, both in terms of computational performance and power consumption. Especially the computational performance is evaluated thoroughly, and the results show that the REALJava is more than twice as fast as the fastest full custom ASIC Java processor. In addition to standard Java virtual machine benchmarks, several new Java applications are designed to both verify the results and broaden the spectrum of the tests.

Gesture-Based, Touch-Free Multi-User Gaming on Wall-Sized, High-Resolution Tiled Displays

Having to carry input devices can be inconvenient when interacting with wall-sized, high-resolution tiled displays. Such displays are typically driven by a cluster of computers. Running existing games on a cluster is non-trivial, and the performance attained using software solutions like Chromium is not good enough. This paper presents a touch-free, multi-user, humancomputer interface for wall-sized displays that enables completely device-free interaction. The interface is built using 16 cameras and a cluster of computers, and is integrated with the games Quake 3 Arena (Q3A) and Homeworld. The two games were parallelized using two different approaches in order to run on a 7x4 tile, 21 megapixel display wall with good performance. The touch-free interface enables interaction with a latency of 116 ms, where 81 ms are due to the camera hardware. The rendering performance of the games is compared to their sequential counterparts running on the display wall using Chromium. Parallel Q3A’s framerate is an order of magnitude higher compared to using Chromium. The parallel version of Homeworld performed on par with the sequential, which did not run at all using Chromium. Informal use of the touch-free interface indicates that it works better for controlling Q3A than Homeworld.

Comparison of accelerated T1-weighted whole-brain structural-imaging protocols.

Imaging in neuroscience, clinical research and pharmaceutical trials often employs the 3D magnetisation-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images with high spatial resolution of the human brain. Typical research and clinical routine MPRAGE protocols with ~1mm isotropic resolution require data acquisition time in the range of 5-10min and often use only moderate two-fold acceleration factor for parallel imaging. Recent advances in MRI hardware and acquisition methodology promise improved leverage of the MR signal and more benign artefact properties in particular when employing increased acceleration factors in clinical routine and research. In this study, we examined four variants of a four-fold-accelerated MPRAGE protocol (2D-GRAPPA, CAIPIRINHA, CAIPIRINHA elliptical, and segmented MPRAGE) and compared clinical readings, basic image quality metrics (SNR, CNR), and automated brain tissue segmentation for morphological assessments of brain structures. The results were benchmarked against a widely-used two-fold-accelerated 3T ADNI MPRAGE protocol that served as reference in this study. 22 healthy subjects (age=20-44yrs.) were imaged with all MPRAGE variants in a single session. An experienced reader rated all images of clinically useful image quality. CAIPIRINHA MPRAGE scans were perceived on average to be of identical value for reading as the reference ADNI-2 protocol. SNR and CNR measurements exhibited the theoretically expected performance at the four-fold acceleration. The results of this study demonstrate that the four-fold accelerated protocols introduce systematic biases in the segmentation results of some brain structures compared to the reference ADNI-2 protocol. Furthermore, results suggest that the increased noise levels in the accelerated protocols play an important role in introducing these biases, at least under the present study conditions.

FPGA BASED DESIGN FOR ACCELERATED FAULT-TESTING OF INTEGRATED CIRCUITS

In the past few decades, integrated circuits have become a major part of everyday life. Every circuit that is created needs to be tested for faults so faulty circuits are not sent to end-users. The creation of these tests is time consuming, costly and difficult to perform on larger circuits. This research presents a novel method for fault detection and test pattern reduction in integrated circuitry under test. By leveraging the FPGA's reconfigurability and parallel processing capabilities, a speed up in fault detection can be achieved over previous computer simulation techniques. This work presents the following contributions to the field of Stuck-At-Fault detection: We present a new method for inserting faults into a circuit net list. Given any circuit netlist, our tool can insert multiplexers into a circuit at correct internal nodes to aid in fault emulation on reconfigurable hardware. We present a parallel method of fault emulation. The benefit of the FPGA is not only its ability to implement any circuit, but its ability to process data in parallel. This research utilizes this to create a more efficient emulation method that implements numerous copies of the same circuit in the FPGA. A new method to organize the most efficient faults. Most methods for determinin the minimum number of inputs to cover the most faults require sophisticated softwareprograms that use heuristics. By utilizing hardware, this research is able to process data faster and use a simpler method for an efficient way of minimizing inputs.

OCTAVIS: Optimization Techniques for Multi-GPU Multi-View Rendering

We present a high performance-yet low cost-system for multi-view rendering in virtual reality (VR) applications. In contrast to complex CAVE installations, which are typically driven by one render client per view, we arrange eight displays in an octagon around the viewer to provide a full 360° projection, and we drive these eight displays by a single PC equipped with multiple graphics units (GPUs). In this paper we describe the hardware and software setup, as well as the necessary low-level and high-level optimizations to optimally exploit the parallelism of this multi-GPU multi-view VR system.

A novel FPGA-based evolvable hardware system based on multiple processing arrays

In this paper, an architecture based on a scalable and flexible set of Evolvable Processing arrays is presented. FPGA-native Dynamic Partial Reconfiguration (DPR) is used for evolution, which is done intrinsically, letting the system to adapt autonomously to variable run-time conditions, including the presence of transient and permanent faults. The architecture supports different modes of operation, namely: independent, parallel, cascaded or bypass mode. These modes of operation can be used during evolution time or during normal operation. The evolvability of the architecture is combined with fault-tolerance techniques, to enhance the platform with self-healing features, making it suitable for applications which require both high adaptability and reliability. Experimental results show that such a system may benefit from accelerated evolution times, increased performance and improved dependability, mainly by increasing fault tolerance for transient and permanent faults, as well as providing some fault identification possibilities. The evolvable HW array shown is tailored for window-based image processing applications.

Advances in characterisation, calibration and data processing speed of optical coherence tomography systems

This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

Rheological behavior, zeta potential, and accelerated stability tests of Buriti oil (Mauritia flexuosa) emulsions containing lyotropic liquid crystals

Background: It is well known that the Amazon region presents a huge biodiversity; therefore, countless natural resources are being employed in the production of phytocosmetics and phytomedicines. Objective: The purpose of this work was to obtain emulsions produced with Buriti oil and nonionic surfactants. Methods: Two surfactant systems were employed (Steareth-2 associated to Ceteareth-5 and to Ceteareth-20) to produce the emulsions using phase diagram method. Emulsions were obtained by echo-planar imaging method at 75 degrees C. Rheological behavior and zeta potential were evaluated, and accelerated stability tests were performed. Results: All emulsions analyzed presented pseudoplastic behavior. Zeta potential values were obtained between -14.2 and -53.3 mV. The formulations did not show changes in either physical stability, pH, or rheological behavior after accelerated stability tests. Significant differences were observed only after temperature cycling test. Conclusion: Based on these results, the emulsions obtained could be considered as promising delivery systems.

Accelerated Stability and Moisturizing Capacity of Emulsions Presenting Lamellar Gel Phase Obtained from Brazilian Natural Raw Material

Oil-in-water (O/W) emulsions containing gel phase were developed with cupuassu and/or cocoa butter from Brazilian ecosystem. They were subjected to storage advanced stability tests (SAST) and to in vivo corneometry evaluation. The evaluated emulsions showed great performance in the evaluated conditions considering that no significant variation was observed. The moisturizing potential was advantageous even without the moisturizing active. The formulation was considered a good cosmetic moisturizing cream and a promise as a drug carrier.

Teleportation with a uniformly accelerated partner

In this work, we give a description of the process of teleportation between Alice in an inertial frame, and Rob who is in uniform acceleration with respect to Alice. The fidelity of the teleportation is reduced due to Davies-Unruh radiation in Rob's frame. In so far as teleportation is a measure of entanglement, our results suggest that quantum entanglement is degraded in noninertial frames.