Описание: and memory.The chapters `A Case Study on Addressing Complex Load Imbalance in OpenMP` and `A Study of Memory Anomalies in OpenMP Applications` are available open access under a Creative Commons Attribution 4.0 License via link.springer.com.
Автор: Mitsuhisa Sato; Toshihiro Hanawa; Matthias S. M?ll Название: Beyond Loop Level Parallelism in OpenMP: Accelerators, Tasking and More ISBN: 3642132162 ISBN-13(EAN): 9783642132162 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 6th International Workshop on OpenMP, IWOMP 2010, held in Tsukuba City, Japan, in June 2010.
Описание: This undergraduate textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems.
Автор: Ioannis Vlahavas; Panagiotis Tsarchopoulos; Ilias Название: Parallel and Constraint Logic Programming ISBN: 0792383710 ISBN-13(EAN): 9780792383710 Издательство: Springer Рейтинг: Цена: 25149.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constraint Logic Programming (CLP) extends the semantics of Prolog in such a way that the combinatorial explosion, a characteristic of most problems in the field of Artificial Intelligence, can be tackled efficiently. This book presents parallel and constraint logic programming, offering a basic understanding of the two fields.
Автор: Julian Shun Название: Shared-Memory Parallelism Can Be Simple, Fast, and Scalable ISBN: 1970001887 ISBN-13(EAN): 9781970001884 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Parallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era.The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra , which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression.The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2–5x speedup over the best existing algorithms on 40 cores.This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.
Автор: Julian Shun Название: Shared-Memory Parallelism Can Be Simple, Fast, and Scalable ISBN: 1970001917 ISBN-13(EAN): 9781970001914 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14227.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Parallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era.The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra , which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression.The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2–5x speedup over the best existing algorithms on 40 cores.This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.
Автор: B.R. Rau; J.A. Fisher Название: Instruction-Level Parallelism ISBN: 0792393678 ISBN-13(EAN): 9780792393672 Издательство: Springer Рейтинг: Цена: 38992.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting a collection of papers chronicling significant work that took place during the 1980s in the area of instruction-level (ILP) parallel processing, this book discusses both compiler techniques and implementation experience on very long instruction word (VLIW) and superscalar architectures.
Автор: Jeffers Jim Название: High Performance Parallelism Pearls Two ISBN: 0128038195 ISBN-13(EAN): 9780128038192 Издательство: Elsevier Science Рейтинг: Цена: 9936.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming - illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating "success stories" demonstrating not just the features of Xeon-powered systems, but also how to leverage parallelism across these heterogeneous systems.
Promotes write-once, run-anywhere coding, showing how to code for high performance on multicore processors and Xeon Phi
Examples from multiple vertical domains illustrating real-world use of Xeon Phi coprocessors
Source code available for download to facilitate further exploration
Автор: Jean Pierre Banatre; Daniel Le Metayer Название: Research Directions in High-Level Parallel Programming Languages ISBN: 3540551603 ISBN-13(EAN): 9783540551607 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume contains most of the papers presented at a workshop on research directions in high-level parallel programming languages. New formalisms for describing parallel computations are discussed.
Автор: Quan Chen; Minyi Guo Название: Task Scheduling for Multi-core and Parallel Architectures ISBN: 9811348359 ISBN-13(EAN): 9789811348358 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Поставка под заказ.
Описание: This book presents task-scheduling techniques for emerging complex parallel architectures including heterogeneous multi-core architectures, warehouse-scale datacenters, and distributed big data processing systems.
Автор: Takayasu Ito; Robert H. Jr. Halstead; Christian Qu Название: Parallel Symbolic Languages and Systems ISBN: 3540611436 ISBN-13(EAN): 9783540611431 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Parallel symbolic computing has gained in importance for high-performance computing. These conference proceedings are organized into sections covering evaluation strategies, programming tools, irregular data structures and applications, systems, and distributed.
Описание: This book provides an overview of and essential insights on invasive computing. The book provides extensive experimental evaluations, investigating the benefits of applying invasive computing and hybrid application mapping to give guarantees on non-functional properties such as timing, energy, and security.
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