Author: Pentti Kanerva
Publisher: MIT Press
ISBN: 9780262111324
Category : Computers
Languages : en
Pages : 194
Book Description
Motivated by the remarkable fluidity of memory the way in which items are pulled spontaneously and effortlessly from our memory by vague similarities to what is currently occupying our attention "Sparse Distributed Memory "presents a mathematically elegant theory of human long term memory.The book, which is self contained, begins with background material from mathematics, computers, and neurophysiology; this is followed by a step by step development of the memory model. The concluding chapter describes an autonomous system that builds from experience an internal model of the world and bases its operation on that internal model. Close attention is paid to the engineering of the memory, including comparisons to ordinary computer memories."Sparse Distributed Memory "provides an overall perspective on neural systems. The model it describes can aid in understanding human memory and learning, and a system based on it sheds light on outstanding problems in philosophy and artificial intelligence. Applications of the memory are expected to be found in the creation of adaptive systems for signal processing, speech, vision, motor control, and (in general) robots. Perhaps the most exciting aspect of the memory, in its implications for research in neural networks, is that its realization with neuronlike components resembles the cortex of the cerebellum.Pentti Kanerva is a scientist at the Research Institute for Advanced Computer Science at the NASA Ames Research Center and a visiting scholar at the Stanford Center for the Study of Language and Information. A Bradford Book.
Sparse Distributed Memory
Author: Pentti Kanerva
Publisher: MIT Press
ISBN: 9780262111324
Category : Computers
Languages : en
Pages : 194
Book Description
Motivated by the remarkable fluidity of memory the way in which items are pulled spontaneously and effortlessly from our memory by vague similarities to what is currently occupying our attention "Sparse Distributed Memory "presents a mathematically elegant theory of human long term memory.The book, which is self contained, begins with background material from mathematics, computers, and neurophysiology; this is followed by a step by step development of the memory model. The concluding chapter describes an autonomous system that builds from experience an internal model of the world and bases its operation on that internal model. Close attention is paid to the engineering of the memory, including comparisons to ordinary computer memories."Sparse Distributed Memory "provides an overall perspective on neural systems. The model it describes can aid in understanding human memory and learning, and a system based on it sheds light on outstanding problems in philosophy and artificial intelligence. Applications of the memory are expected to be found in the creation of adaptive systems for signal processing, speech, vision, motor control, and (in general) robots. Perhaps the most exciting aspect of the memory, in its implications for research in neural networks, is that its realization with neuronlike components resembles the cortex of the cerebellum.Pentti Kanerva is a scientist at the Research Institute for Advanced Computer Science at the NASA Ames Research Center and a visiting scholar at the Stanford Center for the Study of Language and Information. A Bradford Book.
Publisher: MIT Press
ISBN: 9780262111324
Category : Computers
Languages : en
Pages : 194
Book Description
Motivated by the remarkable fluidity of memory the way in which items are pulled spontaneously and effortlessly from our memory by vague similarities to what is currently occupying our attention "Sparse Distributed Memory "presents a mathematically elegant theory of human long term memory.The book, which is self contained, begins with background material from mathematics, computers, and neurophysiology; this is followed by a step by step development of the memory model. The concluding chapter describes an autonomous system that builds from experience an internal model of the world and bases its operation on that internal model. Close attention is paid to the engineering of the memory, including comparisons to ordinary computer memories."Sparse Distributed Memory "provides an overall perspective on neural systems. The model it describes can aid in understanding human memory and learning, and a system based on it sheds light on outstanding problems in philosophy and artificial intelligence. Applications of the memory are expected to be found in the creation of adaptive systems for signal processing, speech, vision, motor control, and (in general) robots. Perhaps the most exciting aspect of the memory, in its implications for research in neural networks, is that its realization with neuronlike components resembles the cortex of the cerebellum.Pentti Kanerva is a scientist at the Research Institute for Advanced Computer Science at the NASA Ames Research Center and a visiting scholar at the Stanford Center for the Study of Language and Information. A Bradford Book.
UPC
Author: Tarek El-Ghazawi
Publisher: John Wiley & Sons
ISBN: 0471478377
Category : Computers
Languages : en
Pages : 262
Book Description
This is the first book to explain the language Unified Parallel C and its use. Authors El-Ghazawi, Carlson, and Sterling are among the developers of UPC, with close links with the industrial members of the UPC consortium. Their text covers background material on parallel architectures and algorithms, and includes UPC programming case studies. This book represents an invaluable resource for the growing number of UPC users and applications developers. More information about UPC can be found at: http://upc.gwu.edu/ An Instructor Support FTP site is available from the Wiley editorial department.
Publisher: John Wiley & Sons
ISBN: 0471478377
Category : Computers
Languages : en
Pages : 262
Book Description
This is the first book to explain the language Unified Parallel C and its use. Authors El-Ghazawi, Carlson, and Sterling are among the developers of UPC, with close links with the industrial members of the UPC consortium. Their text covers background material on parallel architectures and algorithms, and includes UPC programming case studies. This book represents an invaluable resource for the growing number of UPC users and applications developers. More information about UPC can be found at: http://upc.gwu.edu/ An Instructor Support FTP site is available from the Wiley editorial department.
Using OpenMP
Author: Barbara Chapman
Publisher: MIT Press
ISBN: 0262533022
Category : Computers
Languages : en
Pages : 378
Book Description
A comprehensive overview of OpenMP, the standard application programming interface for shared memory parallel computing—a reference for students and professionals. "I hope that readers will learn to use the full expressibility and power of OpenMP. This book should provide an excellent introduction to beginners, and the performance section should help those with some experience who want to push OpenMP to its limits." —from the foreword by David J. Kuck, Intel Fellow, Software and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation OpenMP, a portable programming interface for shared memory parallel computers, was adopted as an informal standard in 1997 by computer scientists who wanted a unified model on which to base programs for shared memory systems. OpenMP is now used by many software developers; it offers significant advantages over both hand-threading and MPI. Using OpenMP offers a comprehensive introduction to parallel programming concepts and a detailed overview of OpenMP. Using OpenMP discusses hardware developments, describes where OpenMP is applicable, and compares OpenMP to other programming interfaces for shared and distributed memory parallel architectures. It introduces the individual features of OpenMP, provides many source code examples that demonstrate the use and functionality of the language constructs, and offers tips on writing an efficient OpenMP program. It describes how to use OpenMP in full-scale applications to achieve high performance on large-scale architectures, discussing several case studies in detail, and offers in-depth troubleshooting advice. It explains how OpenMP is translated into explicitly multithreaded code, providing a valuable behind-the-scenes account of OpenMP program performance. Finally, Using OpenMP considers trends likely to influence OpenMP development, offering a glimpse of the possibilities of a future OpenMP 3.0 from the vantage point of the current OpenMP 2.5. With multicore computer use increasing, the need for a comprehensive introduction and overview of the standard interface is clear. Using OpenMP provides an essential reference not only for students at both undergraduate and graduate levels but also for professionals who intend to parallelize existing codes or develop new parallel programs for shared memory computer architectures.
Publisher: MIT Press
ISBN: 0262533022
Category : Computers
Languages : en
Pages : 378
Book Description
A comprehensive overview of OpenMP, the standard application programming interface for shared memory parallel computing—a reference for students and professionals. "I hope that readers will learn to use the full expressibility and power of OpenMP. This book should provide an excellent introduction to beginners, and the performance section should help those with some experience who want to push OpenMP to its limits." —from the foreword by David J. Kuck, Intel Fellow, Software and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation OpenMP, a portable programming interface for shared memory parallel computers, was adopted as an informal standard in 1997 by computer scientists who wanted a unified model on which to base programs for shared memory systems. OpenMP is now used by many software developers; it offers significant advantages over both hand-threading and MPI. Using OpenMP offers a comprehensive introduction to parallel programming concepts and a detailed overview of OpenMP. Using OpenMP discusses hardware developments, describes where OpenMP is applicable, and compares OpenMP to other programming interfaces for shared and distributed memory parallel architectures. It introduces the individual features of OpenMP, provides many source code examples that demonstrate the use and functionality of the language constructs, and offers tips on writing an efficient OpenMP program. It describes how to use OpenMP in full-scale applications to achieve high performance on large-scale architectures, discussing several case studies in detail, and offers in-depth troubleshooting advice. It explains how OpenMP is translated into explicitly multithreaded code, providing a valuable behind-the-scenes account of OpenMP program performance. Finally, Using OpenMP considers trends likely to influence OpenMP development, offering a glimpse of the possibilities of a future OpenMP 3.0 from the vantage point of the current OpenMP 2.5. With multicore computer use increasing, the need for a comprehensive introduction and overview of the standard interface is clear. Using OpenMP provides an essential reference not only for students at both undergraduate and graduate levels but also for professionals who intend to parallelize existing codes or develop new parallel programs for shared memory computer architectures.
Distributed Shared Memory
Author: Jelica Protic
Publisher: John Wiley & Sons
ISBN: 9780818677373
Category : Computers
Languages : en
Pages : 384
Book Description
The papers present in this text survey both distributed shared memory (DSM) efforts and commercial DSM systems. The book discusses relevant issues that make the concept of DSM one of the most attractive approaches for building large-scale, high-performance multiprocessor systems. The authors provide a general introduction to the DSM field as well as a broad survey of the basic DSM concepts, mechanisms, design issues, and systems. The book concentrates on basic DSM algorithms, their enhancements, and their performance evaluation. In addition, it details implementations that employ DSM solutions at the software and the hardware level. This guide is a research and development reference that provides state-of-the art information that will be useful to architects, designers, and programmers of DSM systems.
Publisher: John Wiley & Sons
ISBN: 9780818677373
Category : Computers
Languages : en
Pages : 384
Book Description
The papers present in this text survey both distributed shared memory (DSM) efforts and commercial DSM systems. The book discusses relevant issues that make the concept of DSM one of the most attractive approaches for building large-scale, high-performance multiprocessor systems. The authors provide a general introduction to the DSM field as well as a broad survey of the basic DSM concepts, mechanisms, design issues, and systems. The book concentrates on basic DSM algorithms, their enhancements, and their performance evaluation. In addition, it details implementations that employ DSM solutions at the software and the hardware level. This guide is a research and development reference that provides state-of-the art information that will be useful to architects, designers, and programmers of DSM systems.
Parallel Programming Using C++
Author: Gregory V. Wilson
Publisher: MIT Press
ISBN: 9780262731188
Category : Computers
Languages : en
Pages : 796
Book Description
Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are routinely ported to platforms ranging from PCs to mainframes, most parallel programs only ever run on one type of machine. One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run. Those that have been platform-independent have usually also had poor performance. Many researchers now believe that object-oriented languages may offer a solution. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming. Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism. For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself. By comparing the implementations of the polygon overlay problem in each system, the reader can get a better sense of their expressiveness and functionality for a common problem. For the systems community, the chapters contain a discussion of the implementation of the various compilers and runtime systems. In addition to discussing the performance of polygon overlay, several of the contributors also discuss the performance of other, more substantial, applications. For the research community, the contributors discuss the motivations for and philosophy of their systems. As well, many of the chapters include critiques that complete the research arc by pointing out possible future research directions. Finally, for the object-oriented community, there are many examples of how encapsulation, inheritance, and polymorphism can be used to control the complexity of developing, debugging, and tuning parallel software.
Publisher: MIT Press
ISBN: 9780262731188
Category : Computers
Languages : en
Pages : 796
Book Description
Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are routinely ported to platforms ranging from PCs to mainframes, most parallel programs only ever run on one type of machine. One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run. Those that have been platform-independent have usually also had poor performance. Many researchers now believe that object-oriented languages may offer a solution. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming. Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism. For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself. By comparing the implementations of the polygon overlay problem in each system, the reader can get a better sense of their expressiveness and functionality for a common problem. For the systems community, the chapters contain a discussion of the implementation of the various compilers and runtime systems. In addition to discussing the performance of polygon overlay, several of the contributors also discuss the performance of other, more substantial, applications. For the research community, the contributors discuss the motivations for and philosophy of their systems. As well, many of the chapters include critiques that complete the research arc by pointing out possible future research directions. Finally, for the object-oriented community, there are many examples of how encapsulation, inheritance, and polymorphism can be used to control the complexity of developing, debugging, and tuning parallel software.
Algorithms and Parallel Computing
Author: Fayez Gebali
Publisher: John Wiley & Sons
ISBN: 0470934638
Category : Computers
Languages : en
Pages : 372
Book Description
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.
Publisher: John Wiley & Sons
ISBN: 0470934638
Category : Computers
Languages : en
Pages : 372
Book Description
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.
Parallel Computing on Distributed Memory Multiprocessors
Author: Füsun Özgüner
Publisher: Springer Science & Business Media
ISBN: 3642580661
Category : Computers
Languages : en
Pages : 327
Book Description
Advances in microelectronic technology have made massively parallel computing a reality and triggered an outburst of research activity in parallel processing architectures and algorithms. Distributed memory multiprocessors - parallel computers that consist of microprocessors connected in a regular topology - are increasingly being used to solve large problems in many application areas. In order to use these computers for a specific application, existing algorithms need to be restructured for the architecture and new algorithms developed. The performance of a computation on a distributed memory multiprocessor is affected by the node and communication architecture, the interconnection network topology, the I/O subsystem, and the parallel algorithm and communication protocols. Each of these parametersis a complex problem, and solutions require an understanding of the interactions among them. This book is based on the papers presented at the NATO Advanced Study Institute held at Bilkent University, Turkey, in July 1991. The book is organized in five parts: Parallel computing structures and communication, Parallel numerical algorithms, Parallel programming, Fault tolerance, and Applications and algorithms.
Publisher: Springer Science & Business Media
ISBN: 3642580661
Category : Computers
Languages : en
Pages : 327
Book Description
Advances in microelectronic technology have made massively parallel computing a reality and triggered an outburst of research activity in parallel processing architectures and algorithms. Distributed memory multiprocessors - parallel computers that consist of microprocessors connected in a regular topology - are increasingly being used to solve large problems in many application areas. In order to use these computers for a specific application, existing algorithms need to be restructured for the architecture and new algorithms developed. The performance of a computation on a distributed memory multiprocessor is affected by the node and communication architecture, the interconnection network topology, the I/O subsystem, and the parallel algorithm and communication protocols. Each of these parametersis a complex problem, and solutions require an understanding of the interactions among them. This book is based on the papers presented at the NATO Advanced Study Institute held at Bilkent University, Turkey, in July 1991. The book is organized in five parts: Parallel computing structures and communication, Parallel numerical algorithms, Parallel programming, Fault tolerance, and Applications and algorithms.
Introduction to Parallel Programming
Author: Subodh Kumar
Publisher: Cambridge University Press
ISBN: 1009276301
Category : Computers
Languages : en
Pages :
Book Description
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.
Publisher: Cambridge University Press
ISBN: 1009276301
Category : Computers
Languages : en
Pages :
Book Description
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.
Data Analytics with Hadoop
Author: Benjamin Bengfort
Publisher: "O'Reilly Media, Inc."
ISBN: 1491913762
Category : Computers
Languages : en
Pages : 288
Book Description
Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib
Publisher: "O'Reilly Media, Inc."
ISBN: 1491913762
Category : Computers
Languages : en
Pages : 288
Book Description
Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib
Shared Memory Application Programming
Author: Victor Alessandrini
Publisher: Morgan Kaufmann
ISBN: 0128038209
Category : Computers
Languages : en
Pages : 557
Book Description
Shared Memory Application Programming presents the key concepts and applications of parallel programming, in an accessible and engaging style applicable to developers across many domains. Multithreaded programming is today a core technology, at the basis of all software development projects in any branch of applied computer science. This book guides readers to develop insights about threaded programming and introduces two popular platforms for multicore development: OpenMP and Intel Threading Building Blocks (TBB). Author Victor Alessandrini leverages his rich experience to explain each platform's design strategies, analyzing the focus and strengths underlying their often complementary capabilities, as well as their interoperability. The book is divided into two parts: the first develops the essential concepts of thread management and synchronization, discussing the way they are implemented in native multithreading libraries (Windows threads, Pthreads) as well as in the modern C++11 threads standard. The second provides an in-depth discussion of TBB and OpenMP including the latest features in OpenMP 4.0 extensions to ensure readers' skills are fully up to date. Focus progressively shifts from traditional thread parallelism to modern task parallelism deployed by modern programming environments. Several chapter include examples drawn from a variety of disciplines, including molecular dynamics and image processing, with full source code and a software library incorporating a number of utilities that readers can adapt into their own projects. - Designed to introduce threading and multicore programming to teach modern coding strategies for developers in applied computing - Leverages author Victor Alessandrini's rich experience to explain each platform's design strategies, analyzing the focus and strengths underlying their often complementary capabilities, as well as their interoperability - Includes complete, up-to-date discussions of OpenMP 4.0 and TBB - Based on the author's training sessions, including information on source code and software libraries which can be repurposed
Publisher: Morgan Kaufmann
ISBN: 0128038209
Category : Computers
Languages : en
Pages : 557
Book Description
Shared Memory Application Programming presents the key concepts and applications of parallel programming, in an accessible and engaging style applicable to developers across many domains. Multithreaded programming is today a core technology, at the basis of all software development projects in any branch of applied computer science. This book guides readers to develop insights about threaded programming and introduces two popular platforms for multicore development: OpenMP and Intel Threading Building Blocks (TBB). Author Victor Alessandrini leverages his rich experience to explain each platform's design strategies, analyzing the focus and strengths underlying their often complementary capabilities, as well as their interoperability. The book is divided into two parts: the first develops the essential concepts of thread management and synchronization, discussing the way they are implemented in native multithreading libraries (Windows threads, Pthreads) as well as in the modern C++11 threads standard. The second provides an in-depth discussion of TBB and OpenMP including the latest features in OpenMP 4.0 extensions to ensure readers' skills are fully up to date. Focus progressively shifts from traditional thread parallelism to modern task parallelism deployed by modern programming environments. Several chapter include examples drawn from a variety of disciplines, including molecular dynamics and image processing, with full source code and a software library incorporating a number of utilities that readers can adapt into their own projects. - Designed to introduce threading and multicore programming to teach modern coding strategies for developers in applied computing - Leverages author Victor Alessandrini's rich experience to explain each platform's design strategies, analyzing the focus and strengths underlying their often complementary capabilities, as well as their interoperability - Includes complete, up-to-date discussions of OpenMP 4.0 and TBB - Based on the author's training sessions, including information on source code and software libraries which can be repurposed