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Parallel Problem Solving from Nature – PPSN XVI: 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II (Lecture Notes in Computer Science #12270)
by Thomas Bäck Mike Preuss André Deutz Hao Wang Carola Doerr Michael Emmerich Heike TrautmannThis two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.
Parallel Problem Solving from Nature – PPSN XVI: 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I (Lecture Notes in Computer Science #12269)
by Thomas Bäck Mike Preuss André Deutz Hao Wang Carola Doerr Michael Emmerich Heike TrautmannThis two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.
Parallel Problem Solving from Nature – PPSN XVII: 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022, Proceedings, Part I (Lecture Notes in Computer Science #13398)
by Günter Rudolph Anna V. Kononova Hernán Aguirre Pascal Kerschke Gabriela Ochoa Tea TušarThis two-volume set LNCS 13398 and LNCS 13399 constitutes the refereed proceedings of the 17th International Conference on Parallel Problem Solving from Nature, PPSN 2022, held in Dortmund, Germany, in September 2022.The 87 revised full papers were carefully reviewed and selected from numerous submissions. The conference presents a study of computing methods derived from natural models. Amorphous Computing, Artificial Life, Artificial Ant Systems, Artificial Immune Systems, Artificial Neural Networks, Cellular Automata, Evolutionary Computation, Swarm Computing, Self-Organizing Systems, Chemical Computation, Molecular Computation, Quantum Computation, Machine Learning, and Artificial Intelligence approaches using Natural Computing methods are just some of the topics covered in this field.
Parallel Problem Solving from Nature – PPSN XVII: 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022, Proceedings, Part II (Lecture Notes in Computer Science #13399)
by Günter Rudolph Anna V. Kononova Hernán Aguirre Pascal Kerschke Gabriela Ochoa Tea TušarThis two-volume set LNCS 13398 and LNCS 13399 constitutes the refereed proceedings of the 17th International Conference on Parallel Problem Solving from Nature, PPSN 2022, held in Dortmund, Germany, in September 2022.The 87 revised full papers were carefully reviewed and selected from numerous submissions. The conference presents a study of computing methods derived from natural models. Amorphous Computing, Artificial Life, Artificial Ant Systems, Artificial Immune Systems, Artificial Neural Networks, Cellular Automata, Evolutionary Computation, Swarm Computing, Self-Organizing Systems, Chemical Computation, Molecular Computation, Quantum Computation, Machine Learning, and Artificial Intelligence approaches using Natural Computing methods are just some of the topics covered in this field.
Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part IV (Lecture Notes in Computer Science #15151)
by Michael Affenzeller Stephan M. Winkler Anna V. Kononova Heike Trautmann Tea Tušar Penousal Machado Thomas BäckThis multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024. The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections: Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis. Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization. Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics. Part IV: Multi-Objective Optimization; Real-World Applications.
Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part II (Lecture Notes in Computer Science #15149)
by Michael Affenzeller Stephan M. Winkler Anna V. Kononova Heike Trautmann Tea Tušar Penousal Machado Thomas BäckThis multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024. The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections: Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis. Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization. Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics. Part IV: Multi-Objective Optimization; Real-World Applications.
Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part III (Lecture Notes in Computer Science #15150)
by Thomas Bäck Penousal Machado Heike Trautmann Anna V. Kononova Tea Tušar Michael Affenzeller Stephan M. WinklerThis multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024. The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections: Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis. Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization. Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics. Part IV: Multi-Objective Optimization; Real-World Applications.
Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part I (Lecture Notes in Computer Science #15148)
by Thomas Bäck Penousal Machado Heike Trautmann Anna V. Kononova Tea Tušar Michael Affenzeller Stephan M. WinklerThis multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024. The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections: Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis. Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization. Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics. Part IV: Multi-Objective Optimization; Real-World Applications.
Parallel Processing and Applied Mathematics: 4th International Conference, Ppam 2001, Naleczow, Poland, September 9-12, 2001, Revised Papers (Lecture Notes in Computer Science #2328)
by Konrad Karczewski Ewa Deelman Jack Dongarra Roman WyrzykowskiThe two-volume set LNCS 10777 and 10778 constitutes revised selected papers from the 12th International Conference on Parallel Processing and Applied Mathematics, PPAM 2017, held in Lublin, Poland, in September 2017.The 49 regular papers presented in this volume were selected from 98 submissions. For the workshops and special sessions, that were held as integral parts of the PPAM 2017 conference, a total of 51 papers was accepted from 75 submissions. The papers were organized in topical sections named as follows:Part I: numerical algorithms and parallel scientific computing; particle methods in simulations; task-based paradigm of parallel computing; GPU computing; parallel non-numerical algorithms; performance evaluation of parallel algorithms and applications; environments and frameworks for parallel/distributed/cloud computing; applications of parallel computing; soft computing with applications; and special session on parallel matrix factorizations. Part II: workshop on models, algorithms and methodologies for hybrid parallelism in new HPC systems; workshop power and energy aspects of computations (PEAC 2017); workshop on scheduling for parallel computing (SPC 2017); workshop on language-based parallel programming models (WLPP 2017); workshop on PGAS programming; minisymposium on HPC applications in physical sciences; minisymposium on high performance computing interval methods; workshop on complex collective systems.
Parallel Processing and Applied Mathematics
by Kazimierz Wiatr Jacek Kitowski Konrad Karczewski Jack Dongarra Ewa Deelman Roman WyrzykowskiThis two-volume set LNCS 9573 and LNCS 9574 constitutes the refereed proceedings of the 11th International Conference of Parallel Processing and Applied Mathematics, PPAM 2015, held in Krakow, Poland, in September 2015. The 111 revised full papers presented in both volumes were carefully reviewed and selected from 196 submissions. The focus of PPAM 2015 was on models, algorithms, and software tools which facilitate efficient and convenient utilization of modern parallel and distributed computing architectures, as well as on large-scale applications, including big data problems.
Parallel Processing and Applied Mathematics: 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part I (Lecture Notes in Computer Science #12043)
by Roman Wyrzykowski Ewa Deelman Jack Dongarra Konrad KarczewskiThe two-volume set LNCS 12043 and 12044 constitutes revised selected papers from the 13th International Conference on Parallel Processing and Applied Mathematics, PPAM 2019, held in Bialystok, Poland, in September 2019.The 91 regular papers presented in these volumes were selected from 161 submissions. For regular tracks of the conference, 41 papers were selected from 89 submissions. The papers were organized in topical sections named as follows: Part I: numerical algorithms and parallel scientific computing; emerging HPC architectures; performance analysis and scheduling in HPC systems; environments and frameworks for parallel/distributed/cloud computing; applications of parallel computing; parallel non-numerical algorithms; soft computing with applications; special session on GPU computing; special session on parallel matrix factorizations. Part II: workshop on language-based parallel programming models (WLPP 2019); workshop on models algorithms and methodologies for hybrid parallelism in new HPC systems; workshop on power and energy aspects of computations (PEAC 2019); special session on tools for energy efficient computing; workshop on scheduling for parallel computing (SPC 2019); workshop on applied high performance numerical algorithms for PDEs; minisymposium on HPC applications in physical sciences; minisymposium on high performance computing interval methods; workshop on complex collective systems. Chapters "Parallel Adaptive Cross Approximation for the Multi-trace Formulation of Scattering Problems" and "A High-Order Discontinuous Galerkin Solver with Dynamic Adaptive Mesh Refinement to Simulate Cloud Formation Processes" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Parallel Processing and Applied Mathematics: 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part II (Lecture Notes in Computer Science #12044)
by Roman Wyrzykowski Ewa Deelman Jack Dongarra Konrad KarczewskiThe two-volume set LNCS 12043 and 12044 constitutes revised selected papers from the 13th International Conference on Parallel Processing and Applied Mathematics, PPAM 2019, held in Bialystok, Poland, in September 2019.The 91 regular papers presented in these volumes were selected from 161 submissions. For regular tracks of the conference, 41 papers were selected from 89 submissions. The papers were organized in topical sections named as follows: Part I: numerical algorithms and parallel scientific computing; emerging HPC architectures; performance analysis and scheduling in HPC systems; environments and frameworks for parallel/distributed/cloud computing; applications of parallel computing; parallel non-numerical algorithms; soft computing with applications; special session on GPU computing; special session on parallel matrix factorizations. Part II: workshop on language-based parallel programming models (WLPP 2019); workshop on models algorithms and methodologies for hybrid parallelism in new HPC systems; workshop on power and energy aspects of computations (PEAC 2019); special session on tools for energy efficient computing; workshop on scheduling for parallel computing (SPC 2019); workshop on applied high performance numerical algorithms for PDEs; minisymposium on HPC applications in physical sciences; minisymposium on high performance computing interval methods; workshop on complex collective systems. Chapters "Parallel adaptive cross approximation for the multi-trace formulation of scattering problems" and "A High-Order Discontinuous Galerkin Solver with Dynamic Adaptive Mesh Refinement to Simulate Cloud Formation Processes" of LNCS 12043 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Parallel Processing and Applied Mathematics: 4th International Conference, Ppam 2001, Naleczow, Poland, September 9-12, 2001, Revised Papers (Lecture Notes in Computer Science #2328)
by Roman Wyrzykowski Jack Dongarra Ewa Deelman Konrad KarczewskiThe two-volume set LNCS 10777 and 10778 constitutes revised selected papers from the 12th International Conference on Parallel Processing and Applied Mathematics, PPAM 2017, held in Lublin, Poland, in September 2017.The 49 regular papers presented in the proceedings were selected from 98 submissions. For the workshops and special sessions, that were held as integral parts of the PPAM 2017 conference, a total of 51 papers was accepted from 75 submissions. The papers were organized in topical sections named as follows:Part I: numerical algorithms and parallel scientific computing; particle methods in simulations; task-based paradigm of parallel computing; GPU computing; parallel non-numerical algorithms; performance evaluation of parallel algorithms and applications; environments and frameworks for parallel/distributed/cloud computing; applications of parallel computing; soft computing with applications; and special session on parallel matrix factorizations.Part II: workshop on models, algorithms and methodologies for hybrid parallelism in new HPC systems; workshop power and energy aspects of computations (PEAC 2017); workshop on scheduling for parallel computing (SPC 2017); workshop on language-based parallel programming models (WLPP 2017); workshop on PGAS programming; minisymposium on HPC applications in physical sciences; minisymposium on high performance computing interval methods; workshop on complex collective systems.
Parallel Processing and Applied Mathematics: 14th International Conference, PPAM 2022, Gdansk, Poland, September 11–14, 2022, Revised Selected Papers, Part I (Lecture Notes in Computer Science #13826)
by Roman Wyrzykowski Jack Dongarra Ewa Deelman Konrad KarczewskiThis two-volume set, LNCS 13826 and LNCS 13827, constitutes the proceedings of the 14th International Conference on Parallel Processing and Applied Mathematics, PPAM 2022, held in Gdansk, Poland, in September 2022.The 77 regular papers presented in these volumes were selected from 132 submissions. For regular tracks of the conference, 33 papers were selected from 62 submissions.The papers were organized in topical sections named as follows:Part I: numerical algorithms and parallel scientific computing; parallel non-numerical algorithms; GPU computing; performance analysis and prediction in HPC systems; scheduling for parallel computing; environments and frameworks for parallel/cloud computing; applications of parallel and distributed computing; soft computing with applications and special session on parallel EVD/SVD and its application in matrix computations.Part II: 9th Workshop on Language-Based Parallel Programming (WLPP 2022); 6th Workshop on Models, Algorithms and Methodologies for Hybrid Parallelism in New HPC Systems (MAMHYP 2022); first workshop on quantum computing and communication; First Workshop on Applications of Machine Learning and Artificial Intelligence in High Performance Computing (WAML 2022); 4th workshop on applied high performance numerical algorithms for PDEs; 5th minisymposium on HPC applications in physical sciences; 8th minisymposium on high performance computing interval methods; 7th workshop on complex collective systems.
Parallel Processing and Applied Mathematics: 14th International Conference, PPAM 2022, Gdansk, Poland, September 11–14, 2022, Revised Selected Papers, Part II (Lecture Notes in Computer Science #13827)
by Roman Wyrzykowski Jack Dongarra Ewa Deelman Konrad KarczewskiThis two-volume set, LNCS 13826 and LNCS 13827, constitutes the proceedings of the 14th International Conference on Parallel Processing and Applied Mathematics, PPAM 2022, held in Gdansk, Poland, in September 2022.The 77 regular papers presented in these volumes were selected from 132 submissions. For regular tracks of the conference, 33 papers were selected from 62 submissions.The papers were organized in topical sections named as follows:Part I: numerical algorithms and parallel scientific computing; parallel non-numerical algorithms; GPU computing; performance analysis and prediction in HPC systems; scheduling for parallel computing; environments and frameworks for parallel/cloud computing; applications of parallel and distributed computing; soft computing with applications and special session on parallel EVD/SVD and its application in matrix computations.Part II: 9th Workshop on Language-Based Parallel Programming (WLPP 2022); 6th Workshop on Models, Algorithms and Methodologies for Hybrid Parallelism in New HPC Systems (MAMHYP 2022); first workshop on quantum computing and communication; First Workshop on Applications of Machine Learning and Artificial Intelligence in High Performance Computing (WAML 2022); 4th workshop on applied high performance numerical algorithms for PDEs; 5th minisymposium on HPC applications in physical sciences; 8th minisymposium on high performance computing interval methods; 7th workshop on complex collective systems.
Parallel Processing and Applied Mathematics
by Roman Wyrzykowski Jack Dongarra Konrad Karczewski Jerzy WaśniewskiThis two-volume-set (LNCS 8384 and 8385) constitutes the refereed proceedings of the 10th International Conference of Parallel Processing and Applied Mathematics, PPAM 2013, held in Warsaw, Poland, in September 2013. The 143 revised full papers presented in both volumes were carefully reviewed and selected from numerous submissions. The papers cover important fields of parallel/distributed/cloud computing and applied mathematics, such as numerical algorithms and parallel scientific computing; parallel non-numerical algorithms; tools and environments for parallel/distributed/cloud computing; applications of parallel computing; applied mathematics, evolutionary computing and metaheuristics.
Parallel Processing and Applied Mathematics
by Roman Wyrzykowski Jack Dongarra Konrad Karczewski Jerzy WaśniewskiThis two-volume-set (LNCS 8384 and 8385) constitutes the refereed proceedings of the 10th International Conference of Parallel Processing and Applied Mathematics, PPAM 2013, held in Warsaw, Poland, in September 2013. The 143 revised full papers presented in both volumes were carefully reviewed and selected from numerous submissions. The papers cover important fields of parallel/distributed/cloud computing and applied mathematics, such as numerical algorithms and parallel scientific computing; parallel non-numerical algorithms; tools and environments for parallel/distributed/cloud computing; applications of parallel computing; applied mathematics, evolutionary computing and metaheuristics.
Parallel Processing in Computational Mechanics (New Generation Computing Ser. #2)
by Hojjat AdeliIntroduces mechanical engineers to high-performance computing using the new generation of computers with vector and parallel processing capabilities that allow the solution to problems beyond the ken of traditional computers. The chapters present an introduction and overview, explain several methodo
Parallel Programming
by Thomas Rauber Gudula RüngerInnovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The presented material has been used for courses in parallel programming at different universities for many years.
Parallel Programming: for Multicore and Cluster Systems
by Gudula Rünger Thomas RauberInnovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years.
Parallel Programming and Concurrency with C# 10 and .NET 6: A modern approach to building faster, more responsive, and asynchronous .NET applications using C#
by Alvin AshcraftLeverage the latest parallel and concurrency features in .NET 6 when building your next application and explore the benefits and challenges of asynchrony, parallelism, and concurrency in .NET via practical examplesKey FeaturesLearn to implement parallel programming and handle concurrency in .NET efficientlySwitch threads while debugging and learn how to monitor specific threads in Visual StudioDiscover how to cancel tasks with callbacks, by polling, or by using a task with wait handlesBook Description.NET has included managed threading capabilities since the beginning, but early techniques had inherent risks: memory leaks, thread synchronization issues, and deadlocks. This book will help you avoid those pitfalls and leverage the modern constructs available in .NET 6 and C# 10, while providing recommendations on patterns and best practices for parallelism and concurrency. Parallel, concurrent, and asynchronous programming are part of every .NET application today, and it becomes imperative for modern developers to understand how to effectively use these techniques.This book will teach intermediate-level .NET developers how to make their applications faster and more responsive with parallel programming and concurrency in .NET and C# with practical examples. The book starts with the essentials of multi-threaded .NET development and explores how the language and framework constructs have evolved along with .NET. You will later get to grips with the different options available today in .NET 6, followed by insights into best practices, debugging, and unit testing.By the end of this book, you will have a deep understanding of why, when, and how to employ parallelism and concurrency in any .NET application.What you will learnPrevent deadlocks and race conditions with managed threadingUpdate Windows app UIs without causing exceptionsExplore best practices for introducing asynchronous constructs to existing codeAvoid pitfalls when introducing parallelism to your codeImplement the producer-consumer pattern with Dataflow blocksEnforce data sorting when processing data in parallel and safely merge data from multiple sourcesUse concurrent collections that help synchronize data across threadsDebug an everyday parallel app with the Parallel Stacks and Parallel Tasks windowsWho this book is forThis book is for beginner to intermediate-level .NET developers who want to employ the latest parallel and concurrency features in .NET when building their applications. Readers should have a solid understanding of the C# language and any version of the .NET Framework or .NET Core.
Parallel Programming for Modern High Performance Computing Systems
by Pawel CzarnulIn view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs
Parallel Programming with C# and .NET: Fundamentals of Concurrency and Asynchrony Behind Fast-Paced Applications
by Vaskaran SarcarIf you need to understand concurrency, this book is your guide to the fundamentals behind the advanced software you seek to implement to achieve highly responsive and scalable code. Support for parallel computation is an essential part of concurrency. Concurrency is an advanced concept and solutions are not straightforward. Many developers have been burned by it and are still being burned by it. This book aims to simplify the concept for C# developers. It tries to simplify the concept using the Task Parallel Library (TPL), Concurrent Collections, Parallel LINQ (PLINQ), Asynchronous Programming Patterns, and related topics. The book starts with an overview of TPL and discusses Tasks. Understanding these areas is necessary to learn the concepts that follow in the book. You will go through special scenarios, such as handling exceptions and cancellations, followed by demonstrations of synchronization techniques and concurrent collections. You will see demonstrations of parallel loops to speed up the computations. And you'll understand PLINQ in detail. Finally, you'll learn how to simplify asynchronous programming with async and await keywords is discussed. The book contains “Q&A sessions”, review questions, and exercises (in .NET 8 and C#12). After reading the book, you will be able to understand advanced concepts in parallel programming and implement them in your code. What You Will Learn Understand concurrent and multi-threaded development Understand how some modern-day C# features can promote parallel programming Demonstrate the latest patterns for parallel development Who This Book Is For Developers familiar with C# but are absolute beginners for parallel programming.
Parallel Programming with Co-arrays (Chapman & Hall/CRC Computational Science)
by Robert NumrichParallel Programming with Co-Arrays describes the basic techniques used to design parallel algorithms for high-performance, scientific computing. It is intended for upper-level undergraduate students and graduate students who need to develop parallel codes with little or no previous introduction to parallel computing. It is also intended as a reference manual for researchers active in the field of scientific computing. All the algorithms in the book are based on partition operators. These operators provide a unifying principle that fits seemingly disparate techniques into an overall framework for algorithm design. The book uses the co-array programming model to illustrate how to write code for concrete examples, but it emphasizes that the important concepts for algorithm design are independent of the programming model. With these concepts in mind, the reader can write algorithms in different programming models based on personal taste and comfort.
Parallel Programming with Intel Parallel Studio XE
by Stephen Blair-Chappell Andrew StokesOptimize code for multi-core processors with Intel's Parallel Studio Parallel programming is rapidly becoming a "must-know" skill for developers. Yet, where to start? This teach-yourself tutorial is an ideal starting point for developers who already know Windows C and C++ and are eager to add parallelism to their code. With a focus on applying tools, techniques, and language extensions to implement parallelism, this essential resource teaches you how to write programs for multicore and leverage the power of multicore in your programs. Sharing hands-on case studies and real-world examples, the authors examine the challenges of each project and show you how to overcome them. Explores conversion of serial code to parallel Focuses on implementing Intel Parallel Studio Highlights the benefits of using parallel code Addresses error and performance optimization of code Includes real-world scenarios that illustrate the techniques of advanced parallel programming situations Parallel Programming with Intel Parallel Studio dispels any concerns of difficulty and gets you started creating faster code with Intel Parallel Studio.