SKU/Artículo: AMZ-B0FT3G98TM
Mastering Chapel for Parallel Systems: Practical Techniques for Scalable High-Performance Computing
Format:
Paperback
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En stock
En stock
Peso con empaque:
0.57 kg
0.57 kg
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Sí
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Nuevo
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Amazon
Amazon
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USA
USA
Sobre este producto
- Mastering Chapel for Parallel Systems: Practical Techniques for Scalable High-Performance Computing is a definitive, hands-on guide to Chapel—a modern parallel programming language designed to simplify the development of scalable, high-performance applications. Opening with the language’s origins and design philosophy, this book situates Chapel within the broader landscape of parallel computing and explains the technical motivations behind its productivity-focused abstractions. Readers gain a clear, practical foundation for thinking about task- and data-parallel computation across today’s heterogeneous and distributed systems. The core chapters delve deeply into Chapel’s type system, language constructs, and powerful models for expressing parallelism at both task and data levels. You will find practical treatments of synchronization, error handling, module and API design, and scalable data structures, together with advanced topics such as memory management, data distribution, remote execution, and interoperability with C, Fortran, and Python. Emphasis is placed on performance engineering—profiling, optimization strategies, and language idioms that help translate clear, maintainable Chapel code into efficient execution on real hardware. Grounded in real-world case studies, the book weaves theory and practice through rigorous debugging, testing methodologies, and reproducible workflows for parallel software. It concludes by surveying Chapel’s growing open-source ecosystem, practical deployment strategies for varied platforms, and its role in contemporary scientific and engineering applications. Whether you are a researcher, developer, or system architect, this book equips you with the techniques and insights needed to build resilient, scalable solutions with Chapel in production-grade high-performance computing environments.
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