Автор: Matthias S. M?ller; Bronis R. de Supinski; Barbara Название: Evolving OpenMP in an Age of Extreme Parallelism ISBN: 3642022847 ISBN-13(EAN): 9783642022845 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Constitutes the refereed proceedings of the 5th International Workshop on OpenMP, IWOMP 2009, held in Dresden, Germany in June 2009.
Автор: Jeffers Jim Название: High Performance Parallelism Pearls Two ISBN: 0128038195 ISBN-13(EAN): 9780128038192 Издательство: Elsevier Science Рейтинг: Цена: 66240.00 T 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: Julian Shun Название: Shared-Memory Parallelism Can Be Simple, Fast, and Scalable ISBN: 1970001887 ISBN-13(EAN): 9781970001884 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 77370.00 T 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: 94850.00 T 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: 259950.00 T 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: Aiken, Alex Banerjee, Utpal Kejariwal, Arun Nicolau, Alexandru Название: Instruction level parallelism ISBN: 1489977953 ISBN-13(EAN): 9781489977953 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book precisely formulates and simplifies the presentation of Instruction Level Parallelism (ILP) compilation techniques.
Автор: Milfeld Kent, de Supinski Bronis R., Koesterke Lars Название: Openmp: Portable Multi-Level Parallelism on Modern Systems: 16th International Workshop on Openmp, Iwomp 2020, Austin, Tx, Usa, September 22-24, 2020, ISBN: 3030581438 ISBN-13(EAN): 9783030581435 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: 65210.00 T 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.
Автор: Burkhard Freitag; Cliff B. Jones; Christian Lengau Название: Object Orientation with Parallelism and Persistence ISBN: 0792397703 ISBN-13(EAN): 9780792397700 Издательство: Springer Рейтинг: Цена: 167660.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Both object orientation and parallelism are modern programming paradigms. Object orientation raises hopes for increased productivity of software generation and maintenance methods. Parallelism can serve to structure a problem but also promises faster program execution. This work is of interest to researchers working in software engineering.
Название: Sequential and Parallel Algorithms and Data Structures ISBN: 3030252086 ISBN-13(EAN): 9783030252083 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: 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: 74530.00 T 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: Guojin Wang; Albert Zomaya; Gregorio Martinez; Ken Название: Algorithms and Architectures for Parallel Processing ISBN: 3319271601 ISBN-13(EAN): 9783319271606 Издательство: Springer Рейтинг: Цена: 89440.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Trust, security and privacy for Big Data.- Trust, security and privacy for emerging applications.- Network optimization and performance evaluation.- Sensor-cloud systems.- Security and privacy protection in computer and network Systems.- Dependability in sensor, cloud, and Big Data systems.
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