Browsing by Subject "Volume rendering"

Now showing 1 - 6 of 6

Open Access
BilKristal 4.0: A tool for crystal parameters extraction and defect quantification
(Elsevier, 2015) Okuyan, E.; Okuyan, C.
In this paper, we present a revised version of BilKristal 3.0 tool. Raycast screenshot functionality is added to provide improved visual analysis. We added atomic distance analysis functionality to assess crystalline defects. We improved visualization capabilities by adding high level cut function definitions. Discovered bugs are fixed and small performance optimizations are made. © 2015 Elsevier B.V. All rights reserved.
Open Access
Comparison of two image-space subdivision algorithms for direct volume rendering on distributed-memory multicomputers
(Springer, 1995-08) Tanin, Egemen; Kurç, Tahsin M.; Aykanat, Cevdet; Özgüç, Bülent
Direct Volume Rendering (DVR) is a powerful technique for visualizing volumetric data sets. However, it involves intensive computations. In addition, most of the volumetric data sets consist of large number of 3D sampling points. Therefore, visualization of such data sets also requires large computer memory space. Hence, DVR is a good candidate for parallelization on distributed-memory multicomputers. In this work, image-space parallelization of Raycasting based DVR for unstructured grids on distributed-memory multicomputers is presented and discussed. In order to visualize unstructured volumetric datasets where grid points of the dataset are irregularly distributed over the 3D space, the underlying algorithms should resolve the point location and view sort problems of the 3D grid points. In this paper, these problems are solved using a Scanline Z-buffer based algorithm. Two image space subdivision heuristics, namely horizontal and recursive rectangular subdivision heuristics, are utilized to distribute the computations evenly among the processors in the rendering phase. The horizontal subdivision algorithm divides the image space into horizontal bands composed of consecutive scanlines. In the recursive subdivision algorithm, the image space is divided into rectangular subregions recursively. The experimental performance evaluation of the horizontal and recursive subdivision algorithms on an IBM SP2 system are presented and discussed. © Springer-Verlag Berlin Heidelberg 1996.
Open Access
Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP
(2014) Okuyan, E.; Güdükbay, Uğur
Direct volume visualization is an important method in many areas, including computational fluid dynamics and medicine. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multicore parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm supports progressive rendering. Wecompared the GPU implementation with the serial and multicore implementations.We observed significant speed-ups that, together with progressive rendering, enables reaching interactive rates for large datasets. © Springer Science+Business Media New York 2013.
Open Access
Fast direct volume rendering of unstructured grids
(1997-09) Berk, Hakan
Scientific computing has become more and more important with the evolving technology. The vast amount of data that the scientific computing applications produce need new ways to be processed and interpreted by scientists. The large amount of data makes it very difficult for scientists to extract useful information from the data, and interpret it to reach a useful conclusion. Thus. visualization of such numerical data as an image, which is known as Scientific Visualization, is an indispensable tool for researchers. Volume Rendering is a very important branch of Scientific Visualization and makes it possible for scientists to visualize the 3-dimensional (3D) volumetric datasets. Volume Rendering algorithms can be classified into two categories: Indirect and Direct methods. Indirect methods are faster, but direct methods are more flexible and acurate. Direct methods can be classified into three categories: image-space (ray-casting), object-space (projection) and hybrid. The efficiency of a direct volume rendering (DVR) algorithm is strongly related to the way that it solves the underlying point location and view sort problems. Although these problems are almost trivial ones to solve in structured grids, they become more complex ones to deal with for unstructured grids. Researchers have tried to speed up the volume rendering of unstructured grids by using special graphics hardware, and parallel architectures, but the need for software solutions to these problems will always exist. These thesis is involved in solving those problems in unstructured grids via software methods. It investigates three distinct categories, namely image-space methods, object-space methods and hybrid methods for fast direct volume rendering of unstructured grids. The main objective of the thesis is to identify the relative superiorities and inferiorities of the algorithms in these three categories. A survey of existing methods is enriched by a discussion of their merits and shortcomings. Three new and fast algorithms to overcome the existing inefficiencies are proposed, and one existing algorithm is investigated in detail for better comparision. All of the proposed algorithms are aimed at producing correct, high quality images. Two of the proposed algorithms are pure ray-casting based solutions that support early ray termination and can handle cyclic grids. The relative performances of the proposed algorithms are experimented on a wide range of benchmark grids in a common framework for software methods and they are found to be faster than the existing best DVR algorithms.
Open Access
Image-space decomposition algorithms for sort-first parallel volume rendering of unstructured grids
(1997) Kutluca, Hüseyin
In this thesis, image-space decomposition algorithms are proposed and utilized for parallel implementation of a direct volume rendering algorithm. Screen space bounding box of a primitive is used to approximate the coverage of the primitive on the screen. Number of bounding boxes in a region is used as a workload of the region. Exact model is proposed as a new workload array scheme to find exact number of bounding boxes in a rectangular region in O(1) time. Chains-on-chains partitioning algorithms are exploited for load balancing in some of the proposed decomposition schemes. Summed area table scheme is utilized to achieve more efficient optimal jagged decomposition and iterative rectilinear decomposition algorithms. These two 2D decomposition algorithms are utilized for image-space decomposition using the exact model. Also, new algorithms that use inverse area heuristic are implemented for image-space decomposition. Orthogonal recursive bisection algorithm with medians of medians scheme is applied on regular mesh and quadtree superimposed on the screen. Hilbert space filling curve is also exploited for image-space decomposition. 12 image-space decomposition algorithms are experimentally evaluated on a common framework with respect to the load balance performance, the number of shared primitives, and execution time of the decomposition algorithms.
Open Access
Quick clusters: a GPU-Parallel partitioning for efficient path tracing of unstructured volumetric grids
(Institute of Electrical and Electronics Engineers, 2022-09-22) Morrical, Nate; Şahistan, Alper; Uğur, Güdükbay; Wald, Ingo; Pascucci, Valerio
We propose a simple yet effective method for clustering finite elements to improve preprocessing times and rendering performance of unstructured volumetric grids without requiring auxiliary connectivity data. Rather than building bounding volume hierarchies (BVHs) over individual elements, we sort elements along with a Hilbert curve and aggregate neighboring elements together, improving BVH memory consumption by over an order of magnitude. Then to further reduce memory consumption, we cluster the mesh on the fly into sub-meshes with smaller indices using a series of efficient parallel mesh re-indexing operations. These clusters are then passed to a highly optimized ray tracing API for point containment queries and ray-cluster intersection testing. Each cluster is assigned a maximum extinction value for adaptive sampling, which we rasterize into non-overlapping view-aligned bins allocated along the ray. These maximum extinction bins are then used to guide the placement of samples along the ray during visualization, reducing the number of samples required by multiple orders of magnitude (depending on the dataset), thereby improving overall visualization interactivity. Using our approach, we improve rendering performance over a competitive baseline on the NASA Mars Lander dataset from 6× (1 frame per second (fps) and 1.0 M rays per second (rps) up to now 6 fps and 12.4 M rps , now including volumetric shadows) while simultaneously reducing memory consumption by 3× (33 GB down to 11 GB) and avoiding any offline preprocessing steps, enabling high-quality interactive visualization on consumer graphics cards. Then by utilizing the full 48 GB of an RTX 8000, we improve the performance of Lander by 17 × (1 fps up to 17 fps, 1.0 M rps up to 35.6 M rps) .