Optimizing HPC Applications with Intel® Cluster Tools takes the reader on a tour of the fast-growing area of high performance computing and the optimization of hybrid programs. These programs typically combine distributed memory and shared memory programming models and use the Message Passing Interface (MPI) and OpenMP for multi-threading to achieve the ultimate goal of high performance at low power consumption on enterprise-class workstations and compute clusters. The book focuses on optimization for clusters consisting of the Intel® Xeon processor, but the optimization methodologies also apply to the Intel® Xeon Phi™ coprocessor and heterogeneous clusters mixing both architectures. Besides the tutorial and reference content, the authors address and refute many myths and misconceptions surrounding the topic. The text is augmented and enriched by descriptions of real-life situations.

This book constitutes the refereed proceedings of the Second Russian Supercomputing Days, RuSCDays 2016, held in Moscow, Russia, in September 2016. The 28 revised full papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in topical sections on the present of supercomputing: large tasks solving experience; the future of supercomputing: new technologies.

The 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.

A hands-on guide to writing a Message Passing Interface, this book takes the reader on a tour across major MPI implementations, best optimization techniques, application relevant usage hints, and a historical retrospective of the MPI world, all based on a quarter of a century spent inside MPI. Readers will learn to write MPI implementations from scratch, and to design and optimize communication mechanisms using pragmatic subsetting as the guiding principle. Inside the Message Passing Interface also covers MPI quirks and tricks to achieve best performance. Dr. Alexander Supalov created the Intel Cluster Tools product line, including the Intel MP Library that he designed and led between 2003 and 2015. He invented the common MPICH ABI and also guided Intel efforts in the MPI Forum during the development of the MPI-2.1, MPI-2.2, and MPI-3 standards. Before that, Alexander designed new finite-element mesh-generation methods, contributing to the PARMACS and PARASOL interfaces, and developed the first full MPI-2 and IMPI implementations in the world. He graduated from the Moscow Institute of Physics and Technology in 1990, and earned his PhD in applied mathematics at the Institute of Numerical Mathematics of the Russian Academy of Sciences in 1995. Alexander holds 26 patents (more pending worldwide).

Discover the future of high-performance computing with "Optimized Computing in C++: Mastering Concurrency, Multithreading, and Parallel Programming," a comprehensive guide designed to elevate your C++ programming skills to unparalleled heights. Whether you're an intermediate programmer eager to broaden your understanding or an experienced developer aiming to optimize your applications, this book is an invaluable resource for maximizing efficiency and speed using C++. Delve into the fundamental principles of high-performance computing (HPC) and grasp the pivotal role of C++ in building scalable, robust applications. Master the intricacies of concurrency, threading, and parallel programming through well-organized chapters, rich with code snippets, practical examples, and real-world case studies. Covering essential topics from basic thread management to advanced GPU programming and MPI for distributed computing, this book spans the full spectrum of HPC in C++. Leverage modern C++ standards and the latest features to simplify concurrent programming, ensuring your applications remain fast and future-proof. Confront real-world challenges head-on with confidence as you learn to debug and profile concurrent and parallel C++ programs, optimizing them for both performance and reliability. "Optimized Computing in C++: Mastering Concurrency, Multithreading, and Parallel Programming" is an indispensable guide for programmers, researchers, and engineers, offering the tools and knowledge needed to push the boundaries of computational performance. Harness the power of C++ and revolutionize your approach to high-performance applications.

"This reference presents a vital compendium of research detailing the latest case studies, architectures, frameworks, methodologies, and research on Grid and Cloud Computing"--

ICT technologies have contributed to the advances in wireless systems, which provide seamless connectivity for worldwide communication. The growth of interconnected devices and the need to store, manage, and process the data from them has led to increased research on the intersection of the internet of things and cloud computing. The Handbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization is a pivotal reference source that provides the latest research findings and solutions for the design and augmentation of wireless systems and cloud computing. The content within this publication examines data mining, machine learning, and software engineering, and is designed for IT specialists, software engineers, researchers, academicians, industry professionals, and students.

This proceedings volume highlights a selection of papers presented at the 7th International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam, during March 19-23, 2018. The conference has been organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology, the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.

The most powerful computers work by harnessing the combined computational power of millions of processors, and exploiting the full potential of such large-scale systems is something which becomes more difficult with each succeeding generation of parallel computers. Alternative architectures and computer paradigms are increasingly being investigated in an attempt to address these difficulties. Added to this, the pervasive presence of heterogeneous and parallel devices in consumer products such as mobile phones, tablets, personal computers and servers also demands efficient programming environments and applications aimed at small-scale parallel systems as opposed to large-scale supercomputers. This book presents a selection of papers presented at the conference: Parallel Computing (ParCo2017), held in Bologna, Italy, on 12 to 15 September 2017. The conference included contributions about alternative approaches to achieving High Performance Computing (HPC) to potentially surpass exa- and zetascale performances, as well as papers on the application of quantum computers and FPGA processors. These developments are aimed at making available systems better capable of solving intensive computational scientific/engineering problems such as climate models, security applications and classic NP-problems, some of which cannot currently be managed by even the most powerful supercomputers available. New areas of application, such as robotics, AI and learning systems, data science, the Internet of Things (IoT), and in-car systems and autonomous vehicles were also covered. As always, ParCo2017 attracted a large number of notable contributions covering present and future developments in parallel computing, and the book will be of interest to all those working in the field.