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The aim of this workshop is to bring together researchers, from industry and academia, concerned with the qualitative and quantitative evaluation and modeling of high performance computing systems Authors are invited to submit novel research in all areas of performance modeling, benchmarking and simulation, and we welcome research that brings together current theory and practice We recognize that the coverage of the term performance has broadened to include power consumption and reliability, and that performance modeling is practiced through analytical methods and approaches based on software tools and simulators.

Parallel programming (Computer science) --- High performance computing

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Enhance your enterprise application development skills by mastering parallel programming techniques in .NET and C# Key Features Write efficient, fine-grained, and scalable parallel code with C# and .NET Core Experience how parallel programming works by building a powerful application Learn the fundamentals of multithreading by working with IIS and Kestrel Book Description In today's world, every CPU has a multi-core processor. However, unless your application has implemented parallel programming, it will fail to utilize the hardware's full processing capacity. This book will show you how to write modern software on the optimized and high-performing .NET Core 3 framework using C# 8. Hands-On Parallel Programming with C# 8 and .NET Core 3 covers how to build multithreaded, concurrent, and optimized applications that harness the power of multi-core processors. Once you've understood the fundamentals of threading and concurrency, you'll gain insights into the data structure in .NET Core that supports parallelism. The book will then help you perform asynchronous programming in C# and diagnose and debug parallel code effectively. You'll also get to grips with the new Kestrel server and understand the difference between the IIS and Kestrel operating models. Finally, you'll learn best practices such as test-driven development, and run unit tests on your parallel code. By the end of the book, you'll have developed a deep understanding of the core concepts of concurrency and asynchrony to create responsive applications that are not CPU-intensive. What you will learn Analyze and break down a problem statement for parallelism Explore the APM and EAP patterns and how to move legacy code to Task Apply reduction techniques to get aggregated results Create PLINQ queries and study the factors that impact their performance Solve concurrency problems caused by producer-consumer race conditions Discover the synchronization primitives available in .NET Core Understand how the threading model works with IIS and Kestrel Find out how you can make the most of server resources Who this book is for If you want to learn how task parallelism is used to build robust and scalable enterprise architecture, this book is for you. Whether you are a beginner to parallelism in C# or an experienced architect, you'll find this book useful to gain insights into the different threading models supported in .NET Standard and .NET Core. Prior knowledge of C# is required to understand the...

Parallel programming (Computer science) --- Microsoft Visual studio. --- Microsoft .NET Framework.

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This book describes several approaches to adaptability that are applied for the optimization of parallel applications, such as thread-level parallelism exploitation and dynamic voltage and frequency scaling on multicore systems. This book explains how software developers can apply a novel technique to adapt the number of threads at runtime without any modification in the source code nor recompilation. This book is useful for software developers in general since it offers realistic examples throughout to demonstrate various techniques presented.

Computer organization. --- Software engineering. --- Computer Systems Organization and Communication Networks. --- Software Engineering. --- Computer software engineering --- Engineering --- Organization, Computer --- Electronic digital computers --- Parallel processing (Electronic computers) --- High performance computing --- Multiprocessors --- Parallel programming (Computer science) --- Supercomputers

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Parallel programming (Computer science) --- Electronic data processing --- Network computers --- Distributed processing --- NCs (Network computers) --- Network access devices --- Network PCs --- Thin clients (Network computers) --- Window-based terminals (Network computers) --- Microcomputers --- Computer networks

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This edited book aims to present the state of the art in research and development of the convergence of high-performance computing and parallel programming for various engineering and scientific applications. The book has consolidated algorithms, techniques, and methodologies to bridge the gap between the theoretical foundations of academia and implementation for research, which might be used in business and other real-time applications in the future.The book outlines techniques and tools used for emergent areas and domains, which include acceleration of large-scale electronic structure simulations with heterogeneous parallel computing, characterizing power and energy efficiency of a data-centric high-performance computing runtime and applications, security applications of GPUs, parallel implementation of multiprocessors on MPI using FDTD, particle-based fused rendering, design and implementation of particle systems for mesh-free methods with high performance, and evolving topics on heterogeneous computing. In the coming days the need to converge HPC, IoT, cloud-based applications will be felt and this volume tries to bridge that gap.

Information technology. --- Parallel processing (Electronic computers) --- Parallel programming (Computer science) --- Computer programming --- High performance computing --- Multiprocessors --- Supercomputers --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Physical Sciences --- Engineering and Technology --- Computer and Information Science --- Distributed Computing --- Computer Science and Engineering