Download or read book HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS written by Humayun Kabir and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph analysis is widely used to study connectivity, centrality, community and path analysis of social networks, biological networks, communication networks and any interacting objects that can be represented as graphs. Graphs are ubiquitous and particularly they are common in social and physical sciences. The graphs are continuously becoming larger and complex; so scalable and parallel algorithms need to be developed to process and analyze such large graphs. Additionally, the high performance computing (HPC) systems are also becoming complex with multiple cores in a processor and multiple levels in the memory subsystems. We need to utilize HPC systems to develop scalable, parallel and high performing algorithmsto analyze large and complex graphs.To analyze connectivity, centrality and robustness of a graph, it is useful to find the densely connected subgraphs (cohesive subgraphs) of a graph. One of the contributions of this thesis is to design parallel algorithms for computing cohesive subgraphs and using them to analyze graphs. The cohesive subgraphs considered are k-core and k-truss of a graph. A parallel algorithm PKC is developed to computek-core decomposition on shared memory systems. PKC uses less memory and has less synchronization overhead as compared to state-of-the-art algorithms. A parallel k-truss decomposition algorithm PKT is also developed that computes trusses of a large social network graph in minutes where as state-of-the-art algorithms take hours. These algorithms are used to sparsify and reorder social networks.In centrality analysis and scientific computing, an important kernel is sparse matrix-vector multiplication (SpMV). Another contribution of this thesis, is to develop a multi-level data structure (CSR-k) to store sparse matrices/graphs to speedup sparse kernels. CSR-k represents the parallelism present in the sparsekernels and also decreases the work load imbalance among the threads. SpMV using CSR-k achieves a speedup of 2x compared to pOSKI on 32 cores. Sparse triangular solution (STS) is also a very useful kernel in scientific computing. We have used CSR-k and graph coloring to represent sparse triangular solution. STSusing CSR-k achieves 2x speedup compared to coloring.

Download or read book Cohesive Subgraph Computation over Large Sparse Graphs written by Lijun Chang and published by Springer. This book was released on 2018-12-24 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is considered the first extended survey on algorithms and techniques for efficient cohesive subgraph computation. With rapid development of information technology, huge volumes of graph data are accumulated. An availability of rich graph data not only brings great opportunities for realizing big values of data to serve key applications, but also brings great challenges in computation. Using a consistent terminology, the book gives an excellent introduction to the models and algorithms for the problem of cohesive subgraph computation. The materials of this book are well organized from introductory content to more advanced topics while also providing well-designed source codes for most algorithms described in the book. This is a timely book for researchers who are interested in this topic and efficient data structure design for large sparse graph processing. It is also a guideline book for new researchers to get to know the area of cohesive subgraph computation.

Download or read book Algorithms for Sparse Linear Systems written by Jennifer Scott and published by Springer Nature. This book was released on 2023-04-29 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines. This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers who are interested in understanding the theory and algorithms needed to tackle sparse systems. It is assumed that the reader has completed a basic course in linear algebra and numerical mathematics.

Download or read book Optimizing Sparse Matrix matrix Multiplication for Graph Computations on GPUs and Multi core Systems written by Vineeth Reddy Thumma and published by . This book was released on 2018 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block and a core component for many data analytics and graph algorithms. An efficient parallel SpGEMM implementation has to handle challenges such as irregular nature of the computation and determination of the non-zero entries in the result matrix. In order to overcome these challenges and to exploit the characteristics of the hardware, various algorithms are devised to improve SpGEMM performance on GPUs and multi-core systems. An experimental study is done on Regularized Markov Clustering(R-MCL) algorithm which has SpGEMM as an important primitive and a parallel algorithm has been devised to improve its performance. A new approach to do K-Truss decomposition of a Graph using a variant of SpGEMM has been proposed which uses adjacency matrix formulation.

Download or read book Euro Par 2016 Parallel Processing Workshops written by Frédéric Desprez and published by Springer. This book was released on 2017-05-26 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the workshops of the 23rd International Conference on Parallel and Distributed Computing, Euro-Par 2016, held in Grenoble, France in August 2016. The 65 full papers presented were carefully reviewed and selected from 95 submissions. The volume includes the papers from the following workshops: Euro-EDUPAR (Second European Workshop on Parallel and Distributed Computing Education for Undergraduate Students) – HeteroPar 2016 (the 14th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms) – IWMSE (5th International Workshop on Multicore Software Engineering) – LSDVE (Fourth Workshop on Large-Scale Distributed Virtual Environments) - PADABS (Fourth Workshop on Parallel and Distributed Agent-Based Simulations) – PBio (Fourth International Workshop on Parallelism in Bioinformatics) – PELGA (Second Workshop on Performance Engineering for Large-Scale Graph Analytics) – REPPAR (Third International Workshop on Reproducibility in Parallel Computing) – Resilience (9th Workshop in Resilience in High Performance Computing in Clusters, Clouds, and Grids) – ROME (Fourth Workshop on Runtime and Operating Systems for the Many-Core Era) – UCHPC (9th Workshop on UnConventional High-Performance Computing).

Download or read book High Performance Computing on Complex Environments written by Emmanuel Jeannot and published by John Wiley & Sons. This book was released on 2014-04-10 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. It is important to provide a comprehensive study on how to use such machines written by specialists of the domain. The book provides recent research results in high-performance computing on complex environments, information on how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems, detailed studies on the impact of applying heterogeneous computing practices to real problems, and applications varying from remote sensing to tomography. The content spans topics such as Numerical Analysis for Heterogeneous and Multicore Systems; Optimization of Communication for High Performance Heterogeneous and Hierarchical Platforms; Efficient Exploitation of Heterogeneous Architectures, Hybrid CPU+GPU, and Distributed Systems; Energy Awareness in High-Performance Computing; and Applications of Heterogeneous High-Performance Computing. • Covers cutting-edge research in HPC on complex environments, following an international collaboration of members of the ComplexHPC • Explains how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems • Twenty-three chapters and over 100 illustrations cover domains such as numerical analysis, communication and storage, applications, GPUs and accelerators, and energy efficiency

Download or read book High Performance Computing written by Julian M. Kunkel and published by Springer. This book was released on 2017-06-09 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 32nd International Conference, ISC High Performance 2017, held in Frankfurt, Germany, in June 2017. The 22 revised full papers presented in this book were carefully reviewed and selected from 66 submissions. The papers cover the following topics: applications and algorithms; proxy applications; architecture and system optimization; and energy-aware computing.

Download or read book High Performance Computing written by Julian M. Kunkel and published by Springer. This book was released on 2015-06-19 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 30th International Conference, ISC High Performance 2015, [formerly known as the International Supercomputing Conference] held in Frankfurt, Germany, in July 2015. The 27 revised full papers presented together with 10 short papers were carefully reviewed and selected from 67 submissions. The papers cover the following topics: cost-efficient data centers, scalable applications, advances in algorithms, scientific libraries, programming models, architectures, performance models and analysis, automatic performance optimization, parallel I/O and energy efficiency.

Download or read book Combinatorial Scientific Computing written by Uwe Naumann and published by CRC Press. This book was released on 2012-01-25 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial Scientific Computing explores the latest research on creating algorithms and software tools to solve key combinatorial problems on large-scale high-performance computing architectures. It includes contributions from international researchers who are pioneers in designing software and applications for high-performance computing systems. The book offers a state-of-the-art overview of the latest research, tool development, and applications. It focuses on load balancing and parallelization on high-performance computers, large-scale optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications in large-scale social networks. The authors unify these seemingly disparate areas through a common set of abstractions and algorithms based on combinatorics, graphs, and hypergraphs. Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations and their importance continues to grow with the demands of new applications and advanced architectures. By addressing current challenges in the field, this volume sets the stage for the accelerated development and deployment of fundamental enabling technologies in high-performance scientific computing.

Download or read book Graph Algorithms written by Mark Needham and published by "O'Reilly Media, Inc.". This book was released on 2019-05-16 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark

Download or read book Parallel Computing written by Barbara Chapman and published by IOS Press. This book was released on 2010 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: From Multicores and GPUs to Petascale. Parallel computing technologies have brought dramatic changes to mainstream computing the majority of todays PCs, laptops and even notebooks incorporate multiprocessor chips with up to four processors. Standard components are increasingly combined with GPUs Graphics Processing Unit, originally designed for high-speed graphics processing, and FPGAs Free Programmable Gate Array to build parallel computers with a wide spectrum of high-speed processing functions. The scale of this powerful hardware is limited only by factors such as energy consumption and thermal control. However, in addition to"

Download or read book High Performance Modelling and Simulation for Big Data Applications written by Joanna Kołodziej and published by Springer. This book was released on 2019-03-25 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.

Download or read book Software for Exascale Computing SPPEXA 2016 2019 written by Hans-Joachim Bungartz and published by Springer Nature. This book was released on 2020-07-30 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest.

Download or read book Numerical Computations with GPUs written by Volodymyr Kindratenko and published by Springer. This book was released on 2014-07-03 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together research on numerical methods adapted for Graphics Processing Units (GPUs). It explains recent efforts to adapt classic numerical methods, including solution of linear equations and FFT, for massively parallel GPU architectures. This volume consolidates recent research and adaptations, covering widely used methods that are at the core of many scientific and engineering computations. Each chapter is written by authors working on a specific group of methods; these leading experts provide mathematical background, parallel algorithms and implementation details leading to reusable, adaptable and scalable code fragments. This book also serves as a GPU implementation manual for many numerical algorithms, sharing tips on GPUs that can increase application efficiency. The valuable insights into parallelization strategies for GPUs are supplemented by ready-to-use code fragments. Numerical Computations with GPUs targets professionals and researchers working in high performance computing and GPU programming. Advanced-level students focused on computer science and mathematics will also find this book useful as secondary text book or reference.

Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.

Download or read book Parallel Processing for Scientific Computing written by Michael A. Heroux and published by SIAM. This book was released on 2006-01-01 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.

Download or read book Distributed Graph Analytics written by Unnikrishnan Cheramangalath and published by Springer Nature. This book was released on 2020-04-17 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together two important trends: graph algorithms and high-performance computing. Efficient and scalable execution of graph processing applications in data or network analysis requires innovations at multiple levels: algorithms, associated data structures, their implementation and tuning to a particular hardware. Further, programming languages and the associated compilers play a crucial role when it comes to automating efficient code generation for various architectures. This book discusses the essentials of all these aspects. The book is divided into three parts: programming, languages, and their compilation. The first part examines the manual parallelization of graph algorithms, revealing various parallelization patterns encountered, especially when dealing with graphs. The second part uses these patterns to provide language constructs that allow a graph algorithm to be specified. Programmers can work with these language constructs without worrying about their implementation, which is the focus of the third part. Implementation is handled by a compiler, which can specialize code generation for a backend device. The book also includes suggestive results on different platforms, which illustrate and justify the theory and practice covered. Together, the three parts provide the essential ingredients for creating a high-performance graph application. The book ends with a section on future directions, which offers several pointers to promising topics for future research. This book is intended for new researchers as well as graduate and advanced undergraduate students. Most of the chapters can be read independently by those familiar with the basics of parallel programming and graph algorithms. However, to make the material more accessible, the book includes a brief background on elementary graph algorithms, parallel computing and GPUs. Moreover it presents a case study using Falcon, a domain-specific language for graph algorithms, to illustrate the concepts.