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Author: David B. Kirk Publisher: Newnes ISBN: 0123914183 Category : Computers Languages : en Pages : 519
Book Description
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
Author: David B. Kirk Publisher: Newnes ISBN: 0123914183 Category : Computers Languages : en Pages : 519
Book Description
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
Author: Eric L. Schwartz Publisher: MIT Press ISBN: 9780262691642 Category : Computers Languages : en Pages : 468
Book Description
The thirty original contributions in this book provide a working definition of"computational neuroscience" as the area in which problems lie simultaneously within computerscience and neuroscience. They review this emerging field in historical and philosophical overviewsand in stimulating summaries of recent results. Leading researchers address the structure of thebrain and the computational problems associated with describing and understanding this structure atthe synaptic, neural, map, and system levels.The overview chapters discuss the early days of thefield, provide a philosophical analysis of the problems associated with confusion between brainmetaphor and brain theory, and take up the scope and structure of computationalneuroscience.Synaptic-level structure is addressed in chapters that relate the properties ofdendritic branches, spines, and synapses to the biophysics of computation and provide a connectionbetween real neuron architectures and neural network simulations.The network-level chapters take upthe preattentive perception of 3-D forms, oscillation in neural networks, the neurobiologicalsignificance of new learning models, and the analysis of neural assemblies and local learningrides.Map-level structure is explored in chapters on the bat echolocation system, cat orientationmaps, primate stereo vision cortical cognitive maps, dynamic remapping in primate visual cortex, andcomputer-aided reconstruction of topographic and columnar maps in primates.The system-level chaptersfocus on the oculomotor system VLSI models of early vision, schemas for high-level vision,goal-directed movements, modular learning, effects of applied electric current fields on corticalneural activity neuropsychological studies of brain and mind, and an information-theoretic view ofanalog representation in striate cortex.Eric L. Schwartz is Professor of Brain Research and ResearchProfessor of Computer Science, Courant Institute of Mathematical Sciences, New York UniversityMedical Center. Computational Neuroscience is included in the System Development FoundationBenchmark Series.
Author: John A. Hertz Publisher: CRC Press ISBN: 0429968213 Category : Science Languages : en Pages : 352
Book Description
Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
Author: Karsten M. Decker Publisher: Springer Science & Business Media ISBN: 9783764350901 Category : Electronic data processing Languages : en Pages : 682
Book Description
The Cray Research MPP Fortran Programming Model.- Resource Optimisation via Structured Parallel Programming.- SYNAPS/3 - An Extension of C for Scientific Computations.- The Pyramid Programming System.- Intelligent Algorithm Decomposition for Parallelism with Alfer.- Symbolic Array Data Flow Analysis and Pattern Recognition in Numerical Codes.- A GUI for Parallel Code Generation.- Formal Techniques Based on Nets, Object Orientation and Reusability for Rapid Prototyping of Complex Systems.- Adaptor - A Transformation Tool for HPF Programs.- A Parallel Framework for Unstructured Grid Solvers.- A Study of Software Development for High Performance Computing.- Parallel Computational Frames: An Approach to Parallel Application Development based on Message Passing Systems.- A Knowledge-Based Scientific Parallel Programming Environment.- Parallel Distributed Algorithm Design Through Specification Transformation: The Asynchronous Vision System.- Steps Towards Reusability and Portability in Parallel Programming.- An Environment for Portable Distributed Memory Parallel Programming.- Reuse, Portability and Parallel Libraries.- Assessing the Usability of Parallel Programming Systems: The Cowichan Problems.- Experimentally Assessing the Usability of Parallel Programming Systems.- Experiences with Parallel Programming Tools.- The MPI Message Passing Interface Standard.- An Efficient Implementation of MPI.- Post: A New Postal Delivery Model.- Asynchronous Backtrackable Communications in the SLOOP Object-Oriented Language.- A Parallel I/O System for High-Performance Distributed Computing.- Language and Compiler Support for Parallel I/O.- Locality in Scheduling Models of Parallel Computation.- A Load Balancing Algorithm for Massively Parallel Systems.- Static Performance Prediction in PCASE: A Programming Environment for Parallel Supercomputers.- A Performance Tool for High-Level Parallel Programming Languages.- Implementation of a Scalable Trace Analysis Tool.- The Design of a Tool for Parallel Program Performance Analysis and Tuning.- The MPP Apprentice Performance Tool: Delivering the Performance of the Cray T3D.- Optimized Record-Replay Mechanism for RPC-based Parallel Programming.- Abstract Debugging of Distributed Applications.- Design of a Parallel Object-Oriented Linear Algebra Library.- A Library for Coarse Grain Macro-Pipelining in Distributed Memory Architectures.- An Improved Massively Parallel Implementation of Colored Petri-Net Specifications.- A Tool for Parallel System Configuration and Program Mapping based on Genetic Algorithms.- Emulating a Paragon XP/S on a Network of Workstations.- Evaluating VLIW-in-the-large.- Implementing a N-Mixed Memory Model on a Distributed Memory System.- Working Group Report: Reducing the Complexity of Parallel Software Development.- Working Group Report: Usability of Parallel Programming System.- Working Group Report: Skeletons/Templates.
Author: Alianna J. Maren Publisher: Academic Press ISBN: 148326484X Category : Computers Languages : en Pages : 472
Book Description
Handbook of Neural Computing Applications is a collection of articles that deals with neural networks. Some papers review the biology of neural networks, their type and function (structure, dynamics, and learning) and compare a back-propagating perceptron with a Boltzmann machine, or a Hopfield network with a Brain-State-in-a-Box network. Other papers deal with specific neural network types, and also on selecting, configuring, and implementing neural networks. Other papers address specific applications including neurocontrol for the benefit of control engineers and for neural networks researchers. Other applications involve signal processing, spatio-temporal pattern recognition, medical diagnoses, fault diagnoses, robotics, business, data communications, data compression, and adaptive man-machine systems. One paper describes data compression and dimensionality reduction methods that have characteristics, such as high compression ratios to facilitate data storage, strong discrimination of novel data from baseline, rapid operation for software and hardware, as well as the ability to recognized loss of data during compression or reconstruction. The collection can prove helpful for programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers related to programming, hardware interface, networking, engineering or design.
Author: Berndt Müller Publisher: Springer ISBN: 364297239X Category : Science Languages : en Pages : 278
Book Description
The mysteries of the human mind have fascinated scientists and philosophers alike for centuries. Descartes identified our ability to think as the foundation stone of ontological philosophy. Others have taken the human mind as evidence of the existence of supernatural powers, or even of God. Serious scientific in vestigation, which began about half a century ago, has partially answered some of the simpler questions (such as how the brain processes visual information), but has barely touched upon the deeper ones concerned with the nature of consciousness and the possible existence of mental features transcending the biological substance of the brain, often encapsulated in the concept "soul". Besides the physiological and philosophical approaches to these questions, so impressively presented and contrasted in the recent book by Popper and Ec cles [P077), studies of formal networks composed of binary-valued information processing units, highly abstracted versions of biological neurons, either by mathematical analysis or by computer simulation, have emerged as a third route towards a better understanding of the brain, and possibly of the human mind. Long remaining - with the exception of a brief period in the early 1960s - a rather obscure research interest of a small group of dedicated scientists scattered around the world, neural-network research has recently sprung into the limelight as a "fashionable" research field.
Author: Michail Zak Publisher: Springer Science & Business Media ISBN: 3540630554 Category : Science Languages : en Pages : 559
Book Description
This book deals with predictability and dynamical concepts in biology and physics. The main emphasis is on intrinsic stochasticity caused by the instability of dynamical equations. In particular, the authors present for the first time in book form their concept of terminal dynamics. They demonstrate that instability as an attribute of dynamical models can explain the paradox of irreversibility in thermodynamics, the phenomenon of chaos and turbulence in classical mechanics, and non-deterministic (multi-choice) behavior in biological and social systems. The first part of the book describes the basic properties of instability as an attribute of dynamical models and how their analysis is dependent upon frames of reference. The second part describes these instabilities and their usefullness in physics, biology, neural nets, creativity, intelligence, and social behavior (the "collective brain"). The book addresses researchers as well as students; it should also be of interest to philosophers of science.
Author: David B. Kirk
Author: David B. Kirk
Author: 
Author: Eric L. Schwartz
Author: Los Alamos National Laboratory
Author: John A. Hertz
Author: Karsten M. Decker
Author: Alianna J. Maren
Author: 
Author: Berndt Müller
Author: Michail Zak