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Author : Dipakkumar Pravinkant Doctor
Publisher :
ISBN 13 :
Total Pages : 194 pages
Book Rating : 4.:/5 (394 download)
Download or read book Parallel Algorithms for Spatial Data written by Dipakkumar Pravinkant Doctor and published by . This book was released on 1997 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Alberto Belussi
Publisher : MDPI
ISBN 13 : 3039367501
Total Pages : 170 pages
Book Rating : 4.0/5 (393 download)
Download or read book Distributed and Parallel Architectures for Spatial Data written by Alberto Belussi and published by MDPI. This book was released on 2021-01-20 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims at promoting new and innovative studies, proposing new architectures or innovative evolutions of existing ones, and illustrating experiments on current technologies in order to improve the efficiency and effectiveness of distributed and cluster systems when they deal with spatiotemporal data.
Author : Alok N. Choudary
Publisher : Springer Science & Business Media
ISBN 13 : 1461315395
Total Pages : 170 pages
Book Rating : 4.4/5 (613 download)
Download or read book Parallel Architectures and Parallel Algorithms for Integrated Vision Systems written by Alok N. Choudary and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas such as image and signal processing, advanced mathematics, graph theory, databases and artificial intelligence. Hence, not only are the comput ing requirements for solving vision problems tremendous but they also demand computers that are efficient to solve problems exhibiting vastly dif ferent characteristics. With recent advances in VLSI design technology, Single Instruction Multiple Data (SIMD) massively parallel computers have been proposed and built. However, such architectures have been shown to be useful for solving a very limited subset of the problems in vision. Specifically, algorithms from low level vision that involve computations closely mimicking the architec ture and require simple control and computations are suitable for massively parallel SIMD computers. An Integrated Vision System (IVS) involves com putations from low to high level vision to be executed in a systematic fashion and repeatedly. The interaction between computations and information dependent nature of the computations suggests that architectural require ments for computer vision systems can not be satisfied by massively parallel SIMD computers.
Author : Joshua Selvan
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Parallel Algorithms for Querying Spatial Properties in the Protein Data Bank written by Joshua Selvan and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Andrzej Marian Goscinski
Publisher : World Scientific
ISBN 13 : 9814545341
Total Pages : 792 pages
Book Rating : 4.8/5 (145 download)
Download or read book Algorithms And Architectures For Parallel Processing - Proceedings Of The 1997 3rd International Conference written by Andrzej Marian Goscinski and published by World Scientific. This book was released on 1997-11-15 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: The IEEE Third International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP-97) will be held in Melbourne, Australia from December 8th to 12th, 1997. The purpose of this important conference is to bring together developers and researchers from universities, industry and government to advance science and technology in distributed and parallel systems and processing.
Author : Richard Healey
Publisher : CRC Press
ISBN 13 : 1000124053
Total Pages : 479 pages
Book Rating : 4.0/5 (1 download)
Download or read book Parallel Processing Algorithms For GIS written by Richard Healey and published by CRC Press. This book was released on 2020-11-25 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last fifteen years GIS has become a fully-fledged technology, deployed across a range of application areas. However, although computer advances in performance appear to continue unhindered, data volumes and the growing sophistication of analysis procedures mean that performance will increasingly become a serious concern in GIS. Parallel computing offers a potential solution. However, traditional algorithms may not run effectively in a parallel environment, so utilization of parallel technology is not entirely straightforward. This groundbreaking book examines some of the current strategies facing scientists and engineers at this crucial interface of parallel computing and GIS.; The book begins with an introduction to the concepts, terminology and techniques of parallel processing, with particular reference to GIS. High level programming paradigms and software engineering issues underlying parallel software developments are considered and emphasis is given to designing modular reusable software libraries. The book continues with problems in designing parallel software for GIS applications, potential vector and raster data structures and details the algorithmic design for some major GIS operations. An implementation case study is included, based around a raster generalization problem, which illustrates some of the principles involved. Subsequent chapters review progress in parallel database technology in a GIS environment and the use of parallel techniques in various application areas, dealing with both algorithmic and implementation issues.; "Parallel Processing Algorithms for GIS" should be a useful text for a new generation of GIS professionals whose principal concern is the challenge of embracing major computer performance enhancements via parallel computing. Similarly, it should be an important volume for parallel computing professionals who are increasingly aware that GIS offers a major application domain for their technology.
Author : Feng Ni (Ph.D.)
Publisher :
ISBN 13 :
Total Pages : 236 pages
Book Rating : 4.:/5 (13 download)
Download or read book High Performance Computing with Remotely Sensed Spatial Big Data Using the Many-core Graphics Processing Unit (GPU) written by Feng Ni (Ph.D.) and published by . This book was released on 2016 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances in remote sensing technologies have led to the dramatic enlargement of the spatial data repositories and the formation of remotely sensed Spatial Big Data, which include hyperspectral imagery with hundreds of spectral bands, hyper-spatial imagery with sub-meter pixel sizes, and LiDAR (Light Detection And Ranging) data with dense 3D point cloud, and massive waveform curves. The traditional serial computing paradigm became extremely or prohibitively time-consuming when involving complex spatial analysis algorithms and large volumes of remotely sensed Spatial Big Data. High-performance computing (HPC) based on parallel processors, especially the many-core Graphics Processing Unit (GPU), is beginning to be utilized in many research areas involving data-intensive and computationally complex tasks. However, the GPU-based parallel processing of remotely sensed Spatial Big Data is still at its infantry. Most of the current research is mostly based on ad hoc parallelization solutions, and the comprehensive parallelization strategy for different kinds of spatial analysis is still missing. The size of the data that can be processed in these studies was still relatively small, not considered to be real Spatial Big Data. To overcome these limitations, a comprehensive parallelization strategy for different kinds of spatial analysis with remotely sensed spatial data of different sizes and types was proposed in this research. Specifically, data partitioning strategies inside GPU for the three major types of spatial analysis including local, focal and zonal analysis were designed to utilize the parallel computing power of the many-core GPU; data partitioning strategies outside GPU were designed to break the resource limitation of the many-core GPU; data referencing approaches were provided to efficiently partition regularly spaced and irregularly spaced spatial data. Case studies involving different types of spatial analysis and different types of remotely sensed data were then conducted to demonstrate the algorithm implementation with the proposed parallelization strategy. By running the developed parallel algorithms on a many-core GPU, the computational efficiency of each case study was greatly improved with a computing speedup ranging from 10X to 40X over the serial algorithms. The parallel programs are able to handle data with a size much bigger than the size of the GPU memory, as long as it can be stored on the local hard disks. While bigger data were used, the computing speedup of parallel algorithms was increased up to 72X, which suggest that large datasets like Spatial Big Data should be used for parallel processing to take full advantage of the computing power of the many-core GPU.
Author : Wenwu Tang
Publisher : Springer Nature
ISBN 13 : 3030479986
Total Pages : 298 pages
Book Rating : 4.0/5 (34 download)
Download or read book High Performance Computing for Geospatial Applications written by Wenwu Tang and published by Springer Nature. This book was released on 2020-07-20 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study. The book begins by discussing theoretical aspects and methodological uses of HPC within a geospatial context, including parallel algorithms, geospatial data handling, spatial analysis and modeling, and cartography and geovisualization. Then, specific domain applications of HPC are addressed in the contexts of earth science, land use and land cover change, urban studies, transportation studies, and social science. The book will be of interest to scientists and engineers who are interested in applying cutting-edge HPC technologies in their respective fields, as well as students and faculty engaged in geography, environmental science, social science, and computer science.
Author : Yiqiu Wang (Computer scientist)
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)
Download or read book Fast Parallel Algorithms and Library for Spatial Clustering and Computational Geometry written by Yiqiu Wang (Computer scientist) and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents novel parallel shared-memory multi-core algorithms, implementations, and frameworks for efficiently solving large-scale spatial clustering and computational geometry problems. The primary focus is on designing theoretically-efficient and practical algorithms that can handle the increasing demand for faster processing speeds in spatial data sets. In the first part of the thesis, we introduce new parallel algorithms and framework for spatial clustering. We design new parallel algorithms for exact and approximate DBSCAN, which match the work complexity of the best sequential algorithms while maintaining low depth. Extensive experiments demonstrate that our algorithms achieve massive speedup over existing algorithms and can efficiently process large-scale data sets. We also present new parallel algorithms for hierarchical DBSCAN (HDBSCAN) and Euclidean minimum spanning tree (EMST), including several theoretical results and practical optimizations. Furthermore, we propose a method to generate a dendrogram from the minimum spanning tree (MST) of the HDBSCAN or EMST problem. The EMST also solves single-linkage clustering. Lastly, we also design a framework for implementing parallel grid-based clustering algorithms. The second part of the thesis introduces our contributions to parallel algorithms and a library for computational geometry. We contribute to three problems in computational geometry: a new parallel reservation-based algorithm that can express both randomized incremental convex hull and quickhull algorithms; a sampling-based algorithm to reduce work for the smallest enclosing ball problem; and a parallel batch-dynamic data structure for dynamic closest pair problem. We also introduce ParGeo, a library for parallel computational geometry that provides various parallel geometric algorithms, data structures, and graph generators. Our experimental evaluations show significant speedups achieved by our proposed algorithms across different problems. Overall, this thesis demonstrates that parallel shared-memory multi-core algorithms, implementations, and frameworks can efficiently solve large-scale spatial clustering and computational geometry problems both in theory and practice.
Author : Dianne Richardson
Publisher : Springer Science & Business Media
ISBN 13 : 3642560946
Total Pages : 584 pages
Book Rating : 4.6/5 (425 download)
Download or read book Advances in Spatial Data Handling written by Dianne Richardson and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, entitled Advances in Spatial Data Handling, is a compendium of papers resulting from the International Symposium on Spatial Data Handling (SDH), held in Ottawa, Canada, July 9-12, 2002. The SDH conference series has been organised as one of the main activities of the International Geographical Union (IGU) since it was first started in Zurich in 1984. In the late 1990’s the IGU Commission of Geographic Information Systems was discontinued and a study group was formed to succeed it in 1997. Much like the IGU Commission, the objectives of the Study Group are to create a network of people and research centres addressing geographical information science and to facilitate exchange of information. The International Symposium on Spatial Data Handling, which is the most important activity of the IGU Study Group, has, throughout its 18 year history been highly regarded as one of the most important GIS conferences in the world.
Author : Jason Laura
Publisher :
ISBN 13 :
Total Pages : 178 pages
Book Rating : 4.:/5 (933 download)
Download or read book A Taxonomy of Parallel Vector Spatial Analysis Algorithms written by Jason Laura and published by . This book was released on 2015 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nearly 25 years ago, parallel computing techniques were first applied to vector spatial analysis methods. This initial research was driven by the desire to reduce computing times in order to support scaling to larger problem sets. Since this initial work, rapid technological advancement has driven the availability of High Performance Computing (HPC) resources, in the form of multi-core desktop computers, distributed geographic information processing systems, e.g. computational grids, and single site HPC clusters. In step with increases in computational resources, significant advancement in the capabilities to capture and store large quantities of spatially enabled data have been realized. A key component to utilizing vast data quantities in HPC environments, scalable algorithms, have failed to keep pace. The National Science Foundation has identified the lack of scalable algorithms in codified frameworks as an essential research product. Fulfillment of this goal is challenging given the lack of a codified theoretical framework mapping atomic numeric operations from the spatial analysis stack to parallel programming paradigms, the diversity in vernacular utilized by research groups, the propensity for implementations to tightly couple to under- lying hardware, and the general difficulty in realizing scalable parallel algorithms. This dissertation develops a taxonomy of parallel vector spatial analysis algorithms with classification being defined by root mathematical operation and communication pattern, a computational dwarf. Six computational dwarfs are identified, three being drawn directly from an existing parallel computing taxonomy and three being created to capture characteristics unique to spatial analysis algorithms. The taxonomy provides a high-level classification decoupled from low-level implementation details such as hardware, communication protocols, implementation language, decomposition method, or file input and output. By taking a high-level approach implementation specifics are broadly proposed, breadth of coverage is achieved, and extensibility is ensured. The taxonomy is both informed and informed by five case studies im- plemented across multiple, divergent hardware environments. A major contribution of this dissertation is a theoretical framework to support the future development of concrete parallel vector spatial analysis frameworks through the identification of computational dwarfs and, by extension, successful implementation strategies.
Author : Yike Guo
Publisher : Springer Science & Business Media
ISBN 13 : 030647011X
Total Pages : 109 pages
Book Rating : 4.3/5 (64 download)
Download or read book High Performance Data Mining written by Yike Guo and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: High Performance Data Mining: Scaling Algorithms, Applications and Systems brings together in one place important contributions and up-to-date research results in this fast moving area. High Performance Data Mining: Scaling Algorithms, Applications and Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Author : Sandra Arlinghaus
Publisher : CRC Press
ISBN 13 : 1000144321
Total Pages : 328 pages
Book Rating : 4.0/5 (1 download)
Download or read book Practical Handbook of Spatial Statistics written by Sandra Arlinghaus and published by CRC Press. This book was released on 2020-08-27 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The guidance and special techniques provided in this handbook will allow you to understand and use complex spatial statistical techniques. You will learn how to apply proper spatial analysis techniques and why they are generally different from conventional statistical analyses. Clear and concise information on weighting, aggregation effects, sampling, spatial statistics and GIS, and visualization of spatial dependence is provided. Discussions on specific applications using actual data sets fill obvious gaps in the literature, and coverage of critical research frontiers allows readers to explore current areas of active research.
Author : Thor Bestul
Publisher :
ISBN 13 :
Total Pages : 444 pages
Book Rating : 4.:/5 (27 download)
Download or read book Parallel Paradigms and Practices for Spatial Data written by Thor Bestul and published by . This book was released on 1992 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second part proposes a new model for data-parallel programming which utilizes conventional scans, string-wise scans, and monotonic mappings, and justifies the model's practicality. This part demonstrates the mapping into the SAM model of algorithms presented in the first part in terms of the abstract paradigms. The third part discusses the realization of the SAM model on the hypercube and grid architectures, providing proof of the highly efficient nature of the operations allowed in the model."
Author : Rahil Sharma
Publisher :
ISBN 13 :
Total Pages : 126 pages
Book Rating : 4.:/5 (1 download)
Download or read book Shared and Distributed Memory Parallel Algorithms to Solve Big Data Problems in Biological, Social Network and Spatial Domain Applications written by Rahil Sharma and published by . This book was released on 2016 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing size of social networks, community detection has become even more difficult, since network size can reach up to hundreds of millions of vertices and edges. Processing such massive networks requires several hundred gigabytes of RAM, which is only possible by adopting distributed infrastructure. To address this, we develop a novel hybrid (shared + distributed memory) parallel algorithm to efficiently detect high quality communities in massive Twitter and .uk domain networks. The second group of problems deals with the issue of effciently processing spatial Light Detection and Ranging (LiDAR) data. LiDAR data is widely used in forest and agricultural crop studies, landscape classification, 3D urban modeling, etc. Technological advancements in building LiDAR sensors have enabled highly accurate and dense LiDAR point clouds resulting in massive data volumes, which pose computing issues with processing and storage. We develop the first published landscape driven data reduction algorithm, which uses the slope-map of the terrain as a filter to reduce the data without sacrificing its accuracy. Our algorithm is highly scalable and adopts shared memory based parallel architecture. We also develop a parallel interpolation technique that is used to generate highly accurate continuous terrains, i.e. Digital Elevation Models (DEMs), from discrete LiDAR point clouds.
Author : Yosoon Choi
Publisher : MDPI
ISBN 13 : 3039364898
Total Pages : 264 pages
Book Rating : 4.0/5 (393 download)
Download or read book Recent Advances in Geographic Information System for Earth Sciences written by Yosoon Choi and published by MDPI. This book was released on 2020-06-23 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geographic information systems (GISs) have played a vital role in Earth sciences by providing a powerful means of observing the world and various tools for solving complex problems. The scientific community has used GISs to reveal fascinating details about the Earth and other planets. This book on recent advances in GIS for Earth sciences includes 12 publications from esteemed research groups worldwide. The research and review papers in this book belong to the following broad categories: Earth science informatics (geoinformatics), mining, hydrology, natural hazards, and society.
Author : John P. Wilson
Publisher : John Wiley & Sons
ISBN 13 : 0470766530
Total Pages : 656 pages
Book Rating : 4.4/5 (77 download)
Download or read book The Handbook of Geographic Information Science written by John P. Wilson and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook is an essential reference and a guide to the rapidly expanding field of Geographic Information Science. Designed for students and researchers who want an in-depth treatment of the subject, including background information Comprises around 40 substantial essays, each written by a recognized expert in a particular area Covers the full spectrum of research in GIS Surveys the increasing number of applications of GIS Predicts how GIS is likely to evolve in the near future
