Efficient Parallel Algorithms

Efficient Parallel Algorithms PDF Author: Alan Gibbons
Publisher: Cambridge University Press
ISBN: 9780521388412
Category : Computers
Languages : en
Pages : 280

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Book Description
Mathematics of Computing -- Parallelism.

Efficient Parallel Algorithms

Efficient Parallel Algorithms PDF Author: Alan Gibbons
Publisher: Cambridge University Press
ISBN: 9780521388412
Category : Computers
Languages : en
Pages : 280

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Book Description
Mathematics of Computing -- Parallelism.

On the Design, Analysis and Implementation of Efficient Parallel Algorithms

On the Design, Analysis and Implementation of Efficient Parallel Algorithms PDF Author: Stephen Mark Sohn
Publisher:
ISBN:
Category :
Languages : en
Pages : 362

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Book Description


Introduction to Parallel Computing

Introduction to Parallel Computing PDF Author: Vipin Kumar
Publisher: Addison Wesley Longman
ISBN:
Category : Computers
Languages : en
Pages : 632

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Book Description
Mathematics of Computing -- Parallelism.

Parallel Sorting Algorithms

Parallel Sorting Algorithms PDF Author: Selim G. Akl
Publisher: Academic Press
ISBN: 148326808X
Category : Reference
Languages : en
Pages : 244

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Book Description
Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the respective primary memories of the computers (random access memory), or in a single shared memory. SIMD processors communicate through an interconnection network or the processors communicate through a common and shared memory. The text also investigates the case of external sorting in which the sequence to be sorted is bigger than the available primary memory. In this case, the algorithms used in external sorting is very similar to those used to describe internal sorting, that is, when the sequence can fit in the primary memory, The book explains that an algorithm can reach its optimum possible operating time for sorting when it is running on a particular set of architecture, depending on a constant multiplicative factor. The text is suitable for computer engineers and scientists interested in parallel algorithms.

Designing Efficient Algorithms for Parallel Computers

Designing Efficient Algorithms for Parallel Computers PDF Author: Michael Jay Quinn
Publisher: McGraw-Hill Companies
ISBN:
Category : Computers
Languages : en
Pages : 312

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Book Description
Mathematics of Computing -- Parallelism.

Structured Parallel Programming

Structured Parallel Programming PDF Author: Michael McCool
Publisher: Elsevier
ISBN: 0124159931
Category : Computers
Languages : en
Pages : 434

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Book Description
Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers

Parallel Scientific Computing in C++ and MPI

Parallel Scientific Computing in C++ and MPI PDF Author: George Em Karniadakis
Publisher: Cambridge University Press
ISBN: 110749477X
Category : Computers
Languages : en
Pages : 640

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Book Description
Numerical algorithms, modern programming techniques, and parallel computing are often taught serially across different courses and different textbooks. The need to integrate concepts and tools usually comes only in employment or in research - after the courses are concluded - forcing the student to synthesise what is perceived to be three independent subfields into one. This book provides a seamless approach to stimulate the student simultaneously through the eyes of multiple disciplines, leading to enhanced understanding of scientific computing as a whole. The book includes both basic as well as advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Some of the advanced topics include wavelets, high-order methods, non-symmetric systems, and parallelization of sparse systems. The material covered is suited to students from engineering, computer science, physics and mathematics.

并行程序设计

并行程序设计 PDF Author: Foster
Publisher:
ISBN: 9787115103475
Category : Computer programming
Languages : zh-CN
Pages : 381

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Book Description
国外著名高等院校信息科学与技术优秀教材

Parallel Processing and Parallel Algorithms

Parallel Processing and Parallel Algorithms PDF Author: Seyed H Roosta
Publisher: Springer Science & Business Media
ISBN: 1461212200
Category : Computers
Languages : en
Pages : 579

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Book Description
Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.

Learning with Kernels

Learning with Kernels PDF Author: Bernhard Scholkopf
Publisher: MIT Press
ISBN: 0262536579
Category : Computers
Languages : en
Pages : 645

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Book Description
A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.