Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning write by . This book was released on 2012. Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning available in PDF, EPUB and Kindle. Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. And, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.
Parallel Volume Rendering on a Shared-memory Multiprocessor
Parallel Volume Rendering on a Shared-memory Multiprocessor - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Parallel Volume Rendering on a Shared-memory Multiprocessor write by Judith A. Challinger. This book was released on 1992. Parallel Volume Rendering on a Shared-memory Multiprocessor available in PDF, EPUB and Kindle. Abstract: "Volume rendering is a powerful, but computationally intensive, computer graphics technique for visualizing volumetric datasets. This paper presents results of investigations into techniques for volume rendering using parallel processing on a shared-memory, multiple- instruction, multiple-data (MIMD) architecture. In particular, two widely used algorithms for volume rendering, raycasting and projection, have been parallelized on a BBN TC2000, and their performance has been measured and analyzed. Preliminary results indicate that the raycasting approach to volume rendering has some advantages for parallelization on this type of architecture."
High Performance Visualization
High Performance Visualization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook High Performance Visualization write by E. Wes Bethel. This book was released on 2012-10-25. High Performance Visualization available in PDF, EPUB and Kindle. Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientifi
Hybrid Parallelism for Volume Rendering on Large, Multi- and Many-core Systems
Hybrid Parallelism for Volume Rendering on Large, Multi- and Many-core Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Parallelism for Volume Rendering on Large, Multi- and Many-core Systems write by . This book was released on 2011. Hybrid Parallelism for Volume Rendering on Large, Multi- and Many-core Systems available in PDF, EPUB and Kindle. With the computing industry trending towards multi- and many-core processors, we study how a standard visualization algorithm, ray-casting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the cores within each node ensures that each node performs its portion of the larger calculation as efficiently as possible. We demonstrate results from weak and strong scaling studies, at levels of concurrency ranging up to 216,000, and with datasets as large as 12.2 trillion cells. The greatest benefit from hybrid parallelism lies in the communication portion of the algorithm, the dominant cost at higher levels of concurrency. We show that reducing the number of participants with a hybrid approach significantly improves performance.
Topological Methods in Data Analysis and Visualization III
Topological Methods in Data Analysis and Visualization III - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Topological Methods in Data Analysis and Visualization III write by Peer-Timo Bremer. This book was released on 2014-04-22. Topological Methods in Data Analysis and Visualization III available in PDF, EPUB and Kindle. This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The volume also features material on core research challenges such as the representation of large and complex datasets and integrating numerical methods with robust combinatorial algorithms. Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made on finding experimental solutions to open problems in the sector. They provide an inclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for future progress. With papers by some of the world’s leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range from engineering to medicine.
