Search Results - "parallel computational"

Medicine Meets Virtual Reality 21 : NextMed by Westwood, J. D.

Table of Contents: “…; ""Raven Surgical Robot Training in Preparation for da Vinci(R) Use: A Randomized Prospective Trial""; ""Real-Time Passive Tracking for Multi-Touch Medical Modeling and Simulation""; ""Commercial Videoconferencing for Use in Telementoring Laparoscopic Surgery""; ""pWeb: A High-Performance, Parallel-Computing Framework for Web-Browser-Based Medical Simulation""…”
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Advanced engineering solutions : selected peer reviewed papers from the 4th International Conference on Intelligent Structure and Vibration Control (ISVC 2014), July 25-28, 2014, C...

Table of Contents: “…Electromagnetic Spider Web Application in Earthquake Prediction Tracking Target Identification Model Based on Multiple Algorithms; Comparison of Gas Chromatography and Liquid Chromatogram Detecting Pesticide Residue; Fingerprint Identification Scheme Based on Distribution Density; GPU Parallel Computing Algorithm in Target Tracking of Space; Image Processing Algorithm Based on Solitary Wave; Image Restoration of Depth of Field Extension Imaging System Based on Genetic Algorithm; Research of Speech Recognition Based on Neural Network; Research on Improvement Algorithm of Image Edge Detection…”
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Studies in stemmatology by Reenen, Pieter Th. van

Table of Contents: “…The length of a Wagner network: criterion for reliability and guard againstcontamination and parallelism; Computer-Assisted Stemmatic Analysis and 'Best-Text' Historical Editing; 1. …”
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Getting Started with Julia Programming. by Balbaert, Ivo

Table of Contents: “…; Multiple dispatch example; Types and collections -- inner constructors; Type unions; Parametric types and methods; Standard modules and paths; Summary; Chapter 7: Metaprogramming in Julia; Expressions and symbols; Eval and interpolation; Defining macros; Built-in macros; Testing; Debugging; Benchmarking; Starting a task; Reflection capabilities; Summary; Chapter 8: I/O, Networking, and Parallel Computing; Basic input and output.…”
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Developments in teracomputing : proceedings of the ninth ECMWF Workshop on the Use of High Performance Computing in Meteorology

Table of Contents: “…Yoshida and S. Shingu -- Parallel computing at Canadian Meteorological Centre / J.…”
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Advances in meshfree and x-fem methods : proceedings of the 1 st Asian Workshop on Meshfree Methods, Singapore, 16-18 December, 2002

Table of Contents: “…Keynote Paper; 1.1 Seamless and Parallel Computing by Using Free Mesh Method: A Kind of Meshless Technique; Section 2. …”
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Linear Algebra : Ideas and Applications. by Penney, Richard C.

Table of Contents: “…2.1.1 Computer Projects -- Exercises -- 2.2 Dimension -- Exercises -- 2.2.1 Computer Projects -- Exercises -- 2.2.2 Applications to Differential Equations -- Exercises -- 2.3 Row Space and the rank-nullity theorem -- Bases for the Row Space -- Summary -- Computational Issues: Computing Rank -- Exercises -- 2.3.1 Computer Projects -- Exercises -- Chapter Summary -- Chapter 3 Linear Transformations -- 3.1 The Linearity Properties -- Exercises -- 3.1.1 Computer Projects -- Exercises -- 3.2 Matrix Multiplication (Composition) -- Partitioned Matrices -- Computational Issues: Parallel Computing…”
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A comprehensive guide on OpenCL Programming with examples by Banger, Ravishekhar

Table of Contents: “…; Renderscripts; Hybrid parallel computing model; Introduction to OpenCL; Hardware and software vendors; Advanced Micro Devices, Inc. …”
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Cloud Computing : an Introduction. by Chopra, Rajiv

Table of Contents: “…Cover; License, Disclaimer of Liability, and Limited Warranty; Title; Copyright; Contents; Preface; Acknowledgments; Chapter 1: Introduction to Cloud Computing; 1.1 Introduction; 1.2 Overview of Parallel Computing; 1.3 Grid Computing; 1.4 Distributed Computing And Its Variants: Manets, Peer-to-Peer, And The Cloud; 1.5 Introduction to Autonomic Computing; 1.6 Historical Development and Evolution of Cloud Computing; 1.7 Vision of Cloud Computing; 1.8 Properties and Characteristics of Cloud Computing; 1.9 Reference Model FOR Cloud Computing; 1.10 Cloud Computing Environments.…”
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Nonlinear systems and optimization for the chemical engineer : solving numerical problems by Buzzi-Ferraris, G. (Guido), Manenti, Flavio

Table of Contents: “…2.6 Gradient-Based Methods2.7 Combination of Algorithms in a General Program; 2.8 Parallel Computations; 2.9 Search for the Interval of Uncertainty; 2.10 Stop Criteria; 2.11 Classes for One-Dimensional Minimization; 2.12 Case Studies; 2.12.1 Optimization of Unimodal Functions; 2.12.2 Optimization of a Batch Reactor; 2.12.3 Maximum Level in a Gravity-Flow Tank in Transient Conditions; 2.13 Tests; 3 Unconstrained Optimization; 3.1 Introduction; 3.1.1 Necessary and Sufficient Conditions; 3.1.2 Quadratic Functions; 3.1.3 Directions of Function Decrease.…”
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Fundamentals of reliability engineering : applications in multistage interconnection networks by Gunawan, Indra

Table of Contents: “…3 Probability Distributions 3.1 Binomial; 3.2 Poisson; 3.3 Exponential; 3.4 Weibull; 3.5 Normal; 3.6 Lognormal; 3.7 Mean Time To Failure (MTTF); References; 4 Availability; 4.1 Definition; 4.2 Summary; 4.3 Availability of Systems with Repair; References; 5 Data Analysis; 5.1 Theoretical Model and Evidence; 5.2 Censored Samples; 5.3 Bayesian Theorem; References; 6 Introduction to Network Systems; 6.1 Parallel Computing and Networks; 6.2 Network Design Considerations; 6.3 Classification of Interconnection Networks; 6.3.1 Shared-Medium Networks; 6.3.2 Direct Networks; 6.3.3 Indirect Networks.…”
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Differential and Differential-Algebraic Systems for the Chemical Engineer : Solving Numerical Problems. by Buzzi-Ferraris, Guido

Table of Contents: “…1.10 Adaptive Methods1.10.1 Method Derived from the Gauss-Kronrod Algorithm; 1.10.2 Method Derived from the Extended Trapezoid Algorithm; 1.10.3 Method Derived from the Gauss-Lobatto Algorithm; 1.11 Parallel Computations; 1.12 Classes for Definite Integrals; 1.13 Case Study: Optimal Adiabatic Bed Reactors for Sulfur Dioxide with Cold Shot Cooling; 2 Ordinary Differential Equations Systems; 2.1 Introduction; 2.2 Algorithm Accuracy; 2.3 Equation and System Conditioning; 2.4 Algorithm Stability; 2.5 Stiff Systems; 2.6 Multistep and Multivalue Algorithms for Stiff Systems.…”
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Deep Learning : From Big Data to Artificial Intelligence with R. by Tuffery, Stephane S.

Table of Contents: “…2.1 Issues -- 2.2 The Search for a Parsimonious Model -- 2.3 Algorithmic Complexity -- 2.4 Parallel Computing -- 2.5 Distributed Computing -- 2.5.1 MapReduce -- 2.5.2 Hadoop -- 2.5.3 Computing Tools for Distributed Computing -- 2.5.4 Column-Oriented Databases -- 2.5.5 Distributed Architecture and "Analytics" -- 2.5.6 Spark -- 2.6 Computer Resources -- 2.6.1 Minimum Resources -- 2.6.2 Graphics Processing Units (GPU) and Tensor Processing Units (TPU) -- 2.6.3 Solutions in the Cloud -- 2.7 R and Python Software -- 2.8 Quantum Computing -- Notes -- Chapter 3 Reminders of Machine Learning…”
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Option pricing and estimation of financial models with R by Iacus, Stefano M. (Stefano Maria)

Table of Contents: “…How to Guide to R -- A.1 Something to Know Soon About R -- A.2 Objects -- A.3 S4 Objects -- A.4 Functions -- A.5 Vectorization -- A.6 Parallel Computing in R -- A.7 Bibliographic Notes -- References -- B.R in Finance -- B.1 Overview of Existing R Frameworks -- B.2 Summary of Main Time Series Objects in R -- B.3 Dates and Time Handling -- B.4 Binding of Time Series -- B.5 Loading Data From Financial Data Servers -- B.6 Bibliographic Notes -- References -- Index.…”
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Optimized cloud resource management and scheduling : theories and practice by Tian, Wenhong

Table of Contents: “…Front Cover; Optimized Cloud Resource Management and Scheduling; Copyright Page; Contents; Foreword; Preface; About the Authors; Acknowledgments; 1 An Introduction to Cloud Computing; Main Contents of this Chapter; 1.1 The background of Cloud computing; 1.2 Cloud computing is an integration of other advanced technologies; 1.2.1 Parallel computing; 1.2.2 Grid computing; 1.2.3 Utility computing; 1.2.4 Ubiquitous computing; 1.2.5 Software as a service; 1.2.6 Virtualization technology; 1.3 The driving forces of Cloud computing; 1.4 The development status and trends of Cloud computing.…”
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Understanding LTE with MATLAB : From Mathematical Modeling to Simulation and Prototyping. by Zarrinkoub, Houman

Table of Contents: “…Chapter 3 MATLAB® for Communications System Design -- 3.1 System Development Workflow -- 3.2 Challenges and Capabilities -- 3.3 Focus -- 3.4 Approach -- 3.5 PHY Models in MATLAB -- 3.6 MATLAB -- 3.7 MATLAB Toolboxes -- 3.8 Simulink -- 3.9 Modeling and Simulation -- 3.9.1 DSP System Toolbox -- 3.9.2 Communications System Toolbox -- 3.9.3 Parallel Computing Toolbox -- 3.9.4 Fixed-Point Designer -- 3.10 Prototyping and Implementation -- 3.10.1 MATLAB Coder -- 3.10.2 Hardware Implementation -- 3.11 Introduction to System Objects -- 3.11.1 System Objects of the Communications System Toolbox…”
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Cloud data centers and cost modeling : a complete guide to planning, designing and building a cloud data center by Wu, Caesar, Buyya, Rajkumar

Table of Contents: “…Cloud Computing Foundations and Business Requirements; 1 Cloud Computing; 1.1 Introduction; 1.1.1 Operation Cost Rationalization; 1.1.2 Revenue Estimation for Emerging Products; 1.2 Cloud Computing at a Glance; 1.3 Right Approach to Definition; 1.4 A Brief History of Cloud Computing Definitions; 1.5 Parallel Computing; 1.5.1 Hardware Parallelism; 1.5.1.1 Processor parallelism; 1.5.1.2 Memory parallelism; 1.5.2 Software Parallelism; 1.5.2.1 Algorithm parallelism.…”
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Big data : concepts, technology and architecture by Balusamy, Balamurugan, R, Nandhini Abirami, Kadry, Seifedine, 1977-, Gandomi, Amir Hossein

Table of Contents: “…<i>3</i>Big Data Analytics. 31</p> <p>1.7.4 Visualizing Big Data. 32</p> <p>1.8 Big Data Technology. 32</p> <p>1.8.1 Challenges faced by Big Data technology. 34</p> <p>1.8.1 Heterogeneity and incompleteness. 34</p> <p>1.8.2 Volume and velocity of the Data. 35</p> <p>1.8.3 Data Storage. 35</p> <p>1.8.4 Data Privacy. 36</p> <p>1.9 Big Data Applications. 36</p> <p>1.10 Big Data Use Cases. 37</p> <p>1.9. 1 Healthcare. 37</p> <p>1.9.2 Telecom.. 38</p> <p>1.9.3 Financial Services. 39</p> <p>Chapter 1 refresher: 40</p> <p>Conceptual short Questions with answers. 43</p> <p>Frequently asked Interview questions. 45</p> <p>Chapter Objective. 46</p> <p>Big Data Storage Concepts. 46</p> <p>2.1 Cluster computing. 47</p> <p>2.1.1 Types of cluster. 49</p> <p>2.1.1.1 High availability cluster. 50</p> <p>2.1.1.2 Load balancing cluster. 50</p> <p>2.1.2 Cluster structure. 51</p> <p>2.3 Distribution Models. 53</p> <p>2.3.1 Sharding. 54</p> <p>2.3.2 Data Replication. 56</p> <p>2.3.2.1 Master-Slave model 57</p> <p>2.3.2.2 Peer-to-Peer model 58</p> <p>2.3.3 Sharding and Replication. 59</p> <p>2.4 Distributed file system.. 60</p> <p>2.5 Relational and Non Relational Databases. 61</p> <p>CoursesOffered. 62</p> <p>Figure 2.12 Data divided across multiple related tables. 62</p> <p>2.4.2 RDBMS Databases. 63</p> <p>2.4.3 NoSQL Databases. 63</p> <p>2.4.4 NewSQL Databases. 64</p> <p>2.5 Scaling Up and Scaling Out Storage. 65</p> <p>Chapter 2 refresher. 67</p> <p>Conceptual short questions with answers. 69</p> <p>Chapter Objective. 72</p> <p>3.1 Introduction to NoSQL. 72</p> <p>3.2 Why NoSQL. 72</p> <p>3.3 CAP theorem.. 73</p> <p>3.4 ACID.. 75</p> <p>3.5 BASE. 76</p> <p>3.6 Schemaless Database. 77</p> <p>3.7 NoSQL (Not Only SQL) 77</p> <p>3.7.1 NoSQL Vs RDBMS. 78</p> <p>3.7.2Features of NoSQL database. 79</p> <p>3.7.3Types of NoSQL Technologies. 80</p> <p>3.7.3.1 Key-Value store database. 81</p> <p>3.7.3.2 Column-store database. 82</p> <p>3.7.3.3 Document Oriented Database. 84</p> <p>3.7.3.4 Graph-oriented Database. 86</p> <p>3.7.4 NoSQL Operations. 93</p> <p>3.9 Migrating from RDBMS to NoSQL. 98</p> <p>Chapter 3 refresher. 99</p> <p>Conceptual short questions with answers. 102</p> <p>Chapter Objective. 104</p> <p>4.1 Data Processing. 104</p> <p>4.2 Shared Everything Architecture. 106</p> <p>4.2.1 Symmetric multiprocessing architecture. 107</p> <p>4.2.2 Distributed Shared memory. 108</p> <p>4.3 Shared nothing architecture. 109</p> <p>4.4 Batch Processing. 110</p> <p>4.5 Real-Time Data Processing. 111</p> <p>4.6 Parallel Computing. 112</p> <p>4.7 Distributed Computing. 113</p> <p>4.8 Big Data Virtualization. 113</p> <p>4.8.1 Attributes of Virtualization. 114</p> <p>4.8.1.1 Encapsulation. 115</p> <p>4.8.1.2 Partitioning. 115</p> <p>4.8.1.3 Isolation. 115</p> <p>4.8.2Big Data Server Virtualization. 116</p> <p>4.9 Introduction. 116</p> <p>4.10 Cloud computing types. 118</p> <p>4.11Cloud Services. 120</p> <p>4.12 Cloud Storage. 121</p> <p>4.12.1 Architecture of GFS. 121</p> <p>4.12.1.1 Master. 123</p> <p>4.12.1.2 Client. 123</p> <p>4.13 Cloud Architecture. 127</p> <p>Cloud Challenges. 129</p> <p>Chapter 4 Refresher. 130</p> <p>Conceptual short questions with answers. 133</p> <p>Chapter Objective. 139</p> <p>5.1 Apache Hadoop. 139</p> <p>5.1.1 Architecture of Apache Hadoop. 140</p> <p>5.1.2Hadoop Ecosystem Components Overview.. 140</p> <p>5.2 Hadoop Storage. 142</p> <p>5.2.1HDFS (Hadoop Distributed File System). 142</p> <p>5.2.2Why HDFS?. …”
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Professional CUDA C programming by Cheng, John

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Topics in parallel and distributed computing : introducing concurrency in undergraduate courses

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