Big Graph Analytics On Just A Single Pc
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Systems For Big Graph Analytics
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Author : Da Yan
language : en
Publisher: Springer
Release Date : 2017-05-31
Systems For Big Graph Analytics written by Da Yan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-31 with Computers categories.
There has been a surging interest in developing systems for analyzing big graphs generated by real applications, such as online social networks and knowledge graphs. This book aims to help readers get familiar with the computation models of various graph processing systems with minimal time investment. This book is organized into three parts, addressing three popular computation models for big graph analytics: think-like-a-vertex, think-likea- graph, and think-like-a-matrix. While vertex-centric systems have gained great popularity, the latter two models are currently being actively studied to solve graph problems that cannot be efficiently solved in vertex-centric model, and are the promising next-generation models for big graph analytics. For each part, the authors introduce the state-of-the-art systems, emphasizing on both their technical novelties and hands-on experiences of using them. The systems introduced include Giraph, Pregel+, Blogel, GraphLab, CraphChi, X-Stream, Quegel, SystemML, etc. Readers will learn how to design graph algorithms in various graph analytics systems, and how to choose the most appropriate system for a particular application at hand. The target audience for this book include beginners who are interested in using a big graph analytics system, and students, researchers and practitioners who would like to build their own graph analytics systems with new features.
Data Analytics
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Author : Mohiuddin Ahmed
language : en
Publisher: CRC Press
Release Date : 2018-09-21
Data Analytics written by Mohiuddin Ahmed and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-21 with Computers categories.
Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. Data analytics are becoming an essential component for every organization and technologies such as health care, financial trading, Internet of Things, Smart Cities or Cyber Physical Systems. However, these diverse application domains give rise to new research challenges. In this context, the book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. In addition, it serves as a single source of reference for acquiring the knowledge on emerging Big Data Analytics technologies.
Massive Graph Analytics
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Author : David A. Bader
language : en
Publisher: CRC Press
Release Date : 2022-07-20
Massive Graph Analytics written by David A. Bader and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-20 with Business & Economics categories.
"Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics." — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national laboratories, and industry who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive-scale graph analytics.
Big Graph Analytics On Just A Single Pc
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Author : Kai Wang
language : en
Publisher:
Release Date : 2019
Big Graph Analytics On Just A Single Pc written by Kai Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
As graph data becomes ubiquitous in modern computing, developing systems to efficiently process large graphs has gained increasing popularity. There are two major types of analytical problems over large graphs: graph computation and graph mining. Graph computation includes a set of problems that can be represented through liner algebra over an adjacency matrix based representation of the graph. Graph mining aims to discover complex structural patterns of a graph, for example, finding relationship patterns in social media network, detecting link spam in web data. Due to their importance in machine learning, web application and social media, graph analytical problems have been extensively studied in the past decade. Practical solutions have been implemented in a wide variety of graph analytical systems. However, most of the existing systems for graph analytics are distributed frameworks, which suffer from one or more of the following drawbacks: (1) many of the (current and future) users performing graph analytics will be domain experts with limited computer science background. They are faced with the challenge of managing a cluster, which involves tasks such as data partitioning and fault tolerance they are not familiar with; (2) not all users have access to enterprise cluster in their daily development tasks; (3) distributed graph systems commonly suffer from large startup and communication overhead; and (4) load balancing in a distributed system is another major challenge. Some graph algorithms have dynamic working sets and and it is thus hard to distribute the workload appropriately before the execution. In this dissertation, we identify three categories of graph workloads for which single-machine systems are more suitable than distributed systems: (1) analytical queries that do not need exact answers; (2) program analysis tasks that are widely used to find bugs in real-world software; and (3) graph mining algorithms that are important for many information-retrieval tasks. Based on these observations, we have developed a set of single-machine graph systems to deliver efficiency and scalability specifically for these workloads. In particular, this dissertation makes the following contributions. The first contribution is the design and implementation of a single-machine graph query system named GraphQ, which divides a large graph into partitions and merges them with the guidance from an abstraction graph. By using multiple levels of abstraction, it can quickly rule out infeasible solutions and identify mergeable partitions. GraphQ uses the memory capacity as a budget and tries its best to find solutions before exhausting the memory, making it possible to answer analytical queries over very large graphs with resources affordable to a single PC. The second contribution is the design and implementation of Graspan, a single-machine, disk-based graph processing system tailored for interprocedural static analyses. Given a program graph and a grammar specification of an analysis, Graspan uses an edge-pair centric computation model to compute dynamic transitive closures on very large program graphs. With the help of novel graph processing techniques, we turn sophisticated code analyses into scalable Big Graph analytics. The third contribution of this dissertation is a single-machine, out-of-core graph mining system, called RStream, which leverages disk support to support efficient edge streaming for mining very large graphs. RStream employs a rich programming model that exposes relational algebra for developers to express a wide variety of mining tasks and implements a runtime engine that delivers efficiency with tuple streaming. In conclusion, this dissertation attempts to explore the opportunities of building single-machine graph systems for scenarios where distributed systems do not work well. Our experimental results demonstrate that the techniques proposed in this dissertation can efficiently solve big graph analytical problems on a single consumer PC. We hope that these promising results will encourage future work to continue building affordable single-machine systems for a rich set of datasets and analytical tasks.
Computer Engineering And Technology
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Author : Weixia Xu
language : en
Publisher: Springer
Release Date : 2019-01-05
Computer Engineering And Technology written by Weixia Xu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-05 with Computers categories.
This book constitutes the refereed proceedings of the 22nd CCF Conference on Computer Engineering and Technology, NCCET 2018, held in Yinchuan, China, in August 2018. The 17 full papers presented were carefully reviewed and selected from 120 submissions. They address topics such as processor architecture; application specific processors; computer application and software optimization; technology on the horizon.
Advances In Intelligent Networking And Collaborative Systems
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Author : Leonard Barolli
language : en
Publisher: Springer
Release Date : 2017-08-14
Advances In Intelligent Networking And Collaborative Systems written by Leonard Barolli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-14 with Technology & Engineering categories.
The aim of this book is to provide the latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems, secure intelligent cloud systems, etc., and to reveal synergies among various paradigms in the multi-disciplinary field of intelligent collaborative systems. It presents the Proceedings of the 9th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2017), held on August 24–26, 2017 in Toronto, Canada. With the rapid evolution of the Internet, we are currently experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm that puts people at the very centre of networks and exploits the value of people’s connections, relations and collaborations. Social networks are also pla ying a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems. Virtual campuses, virtual communities and organizations effectively leverage intelligent networking and collaborative systems by tapping into a broad range of formal and informal electronic relations, such as business-to-business, peer-to-peer and many types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and autonomously. In addition, the latest and powerful technologies based on Grid and wireless infrastructure as well as Cloud computing are now greatly enhancing collaborative and networking applications, but are also facing new issues and challenges. The principal objective of the research and development community is to stimulate research that leads to the creation of responsive environments for networking and, in the longer-term, the developmen t of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning.
Big Data 2 0 Processing Systems
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Author : Sherif Sakr
language : en
Publisher: Springer
Release Date : 2016-08-24
Big Data 2 0 Processing Systems written by Sherif Sakr and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-24 with Computers categories.
This book provides readers the “big picture” and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and big data processing scenarios such as the large-scale processing of structured data, graph data and streaming data. Thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Lastly, Chapter 6 shares conclusions and an outlook on future research challenges. Overall, the book offers a valuable reference guide for students, researchers and professionals in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.
Large Scale Computational Physics On Massively Parallel Computers
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Author : Hans J Herrmann
language : en
Publisher: World Scientific
Release Date : 1993-12-27
Large Scale Computational Physics On Massively Parallel Computers written by Hans J Herrmann and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-12-27 with Science categories.
Contents:A Lattice Solid Model for the Nonlinear Dynamics of Earthquakes (P Mora & D Place)Vectorized and Parallelized Algorithms for Multi-Million Particle MD-Simulations (W Form et al)Green-Function Method for Electronic Structure of Periodic Crystals (R Zeller)Parallelization of the Ising Simulation (N Ito)A Nonlocal Approach to Vertex Models and Quantum Spin Systems (H G Evertz & M Marcu)The Static Quark-Antiquark-Potential: A ‘Classical’ Experiment on the Connection Machine CM-2 (K Schilling & G S Bali)Determination of Monopole Current Clusters in Four-Dimensional Quantum Electrodynamics (A Bode et al)QCD Calculations on the QCDPAX (K Kanaya)UKQCD — Recent Results and Future Prospects (R Kenway)Programming Tools for Parallel Computers (K J M Moriarity & T Trappenberg)Workstation Clusters: One Way to Parallel Computing (M Weber)APE100 and Beyond (R Tripiccione)and other papers Readership: Computational physicists. keywords:
Algorithms And Architectures For Parallel Processing
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Author : Sheng Wen
language : en
Publisher: Springer Nature
Release Date : 2020-01-21
Algorithms And Architectures For Parallel Processing written by Sheng Wen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-21 with Mathematics categories.
The two-volume set LNCS 11944-11945 constitutes the proceedings of the 19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019, held in Melbourne, Australia, in December 2019. The 73 full and 29 short papers presented were carefully reviewed and selected from 251 submissions. The papers are organized in topical sections on: Parallel and Distributed Architectures, Software Systems and Programming Models, Distributed and Parallel and Network-based Computing, Big Data and its Applications, Distributed and Parallel Algorithms, Applications of Distributed and Parallel Computing, Service Dependability and Security, IoT and CPS Computing, Performance Modelling and Evaluation.
Computers And Games
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Author : H. Jaap van den Herik
language : en
Publisher: Springer
Release Date : 2006-01-24
Computers And Games written by H. Jaap van den Herik and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-24 with Computers categories.
This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Computers and Games, CG 2004, held in July 2004. The 21 revised full papers presented together with one keynote article were carefully selected during two rounds of reviewing and improvement from 37 submissions. The papers cover all aspects of artificial intelligence in computer-game playing. Topics addressed include evaluation and learning, search, single-agent search and planning, and computer Go.