Chapel Programming And Parallel Computation
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Chapel Programming and Parallel Computation
"Chapel Programming and Parallel Computation" "Chapel Programming and Parallel Computation" is a definitive and comprehensive guide to mastering the Chapel programming language—a modern parallel language purpose-built to simplify and empower scalable software development. The book opens with an exploration of Chapel’s origins and design philosophy, providing historical context and technical motivation behind its unique abstractions for productive parallel programming. Grounded in the realities of today’s high-performance computing, it meticulously introduces readers to a broad spectrum of parallel programming models, semantic foundations, and practical installation strategies for diverse computing platforms. Structured for both depth and clarity, the subsequent chapters traverse Chapel’s advanced type system, core language constructs, and robust mechanisms for expressing parallelism at both the task and data levels. Readers will discover nuanced guidance on synchronization, error handling, module design, and scalable data structures—equipping them to model, implement, and optimize complex concurrent algorithms and workflows. With specialized topics covering memory management, distributed data distribution, remote execution, and interoperability with C, Fortran, and Python, the book addresses the needs of professionals seeking both productivity and high performance in parallel software engineering. Emphasizing actionable expertise, the text weaves together theory and practice through real-world case studies, performance engineering techniques, and rigorous debugging and testing methodologies for parallel software. It concludes by examining Chapel’s role within contemporary scientific applications, its growing open-source ecosystem, and the evolving landscape of parallel language research. Whether you are a researcher, developer, or architect, this book is an essential resource for harnessing Chapel’s full capabilities to meet the demands of scalable, reproducible, and resilient computation in modern computing environments.
Programming Models for Parallel Computing
An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng
Languages and Compilers for Parallel Computing
This book constitutes the thoroughly refereed post-conference proceedings of the 34th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2020, held in Delaware, NE, USA, in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 9 revised full papers were carefully reviewed and selected from 11 submissions. The conference covers all aspects of languages, compiler techniques, run-time environments, and compiler-related performance evaluation for parallel and high-performance computing. The scope of the workshop encompasses foundational results, as well as practical experience reports and bold new ideas for future systems.