Description

Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products.

This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture.

Key Features

• A practical guide to the essentials of the Intel Xeon Phi coprocessor
• Presents best practices for portable, high-performance computing and a familiar and proven threaded, scalar-vector programming model
• Includes simple but informative code examples that explain the unique aspects of this new highly parallel and high performance computational product
• Covers wide vectors, many cores, many threads and high bandwidth cache/memory architecture

Who Should Read This Book

Software engineers,  High Performance and Super Computing developers, scientific researchers in need of high-performance computing resources.

Table of Contents

1. Introduction
2. High Performance examples
3. Benchmarking Apps
4. Real-world Situations
5. Lots of Data (Vectors)
6. Lots of Tasks (not Threads)
7. Processing Parallelism
8. Coprocessor Architecture
9. Coprocessor System Software
10. Linux on the Coprocessor
11. Math Library
12. MPI
13. Profiling
14. Summary

ISBN: 9780124104143 ¦ Visit in bookstore

Description

Analyzing the Social Web provides a framework for the analysis of public data currently available and being generated by social networks and social media, like Facebook, Twitter, and Foursquare. Access and analysis of this public data about people and their connections to one another allows for new applications of traditional social network analysis techniques that let us identify things like who are the most important or influential people in a network, how things will spread through the network, and the nature of peoples’ relationships. Analyzing the Social Web introduces you to these techniques, shows you their application to many different types of social media, and discusses how social media can be used as a tool for interacting with the online public.

Key Features

• Presents interactive social applications on the web, and the types of analysis that are currently conducted in the study of social media.
• Covers the basics of network structures for beginners, including measuring methods for describing nodes, edges, and parts of the network.
• Discusses the major categories of social media applications or phenomena and shows how the techniques presented can be applied to analyze and understand the underlying data.
• Provides an introduction to information visualization, particularly network visualization techniques, and methods for using them to identify interesting features in a network, generate hypotheses for analysis, and recognize patterns of behavior.
• Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book.

Who Should Read This Book

Researchers, academics, practitioners, and students in HCI, user experience design, data Information analysts, information and data warehouse and systems engineers.

Table of Contents

1. Introduction
2. Nodes, Edges, and Network Measures
3. Network Structure and Measures
4. Network Visualization
5. Tie Strength
6. Trust
7. Understanding Structure Through User Attributes and Behavior
8. Building Networks
9. Propagation in Networks
10. Community-Maintained Resources
11. Location-Based Social Interaction
12. Social Information Filtering
13. Social Media in the Public Sector
14. Business Use of Social Media
15. Privacy
16. Case Study: Social Network Strategies for Surviving the Zombie Apocalypse

ISBN: 9780124055315 ¦ Visit in bookstore

Description

Managing Data in Motion includes the techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling a scalable data architecture. Author April Reeve brings over two decades of experience to present a vendor-neutral approach that can be understood by IT and business managers as well as programmers and architects.Learn the different techniques, technologies, and best practices used to manage the passing of data between computer systems and integrating disparate data together in an enterprise environment.

Key Features

• Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types
• Explains, in non-technical terms, the architecture and components required for an organization to perform Data Integration
• Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of “Big Data”

Who Should Read This Book

Data Warehouse Professionals; Data Modelers and Architects; Database and Network Administrators; ETL and Application Programmers; Project Managers; IT and Data Center Managers; CIO/CTO.

Table of Contents

Part 1: Introduction
• An Explosion of New Technologies for Managing the Movement and Integration of Big Data, Cloud Processing, and Virtual Data
• The Importance of Data Integration in Data and Application Management
• The Differences and Similarities in Managing Data in Motion and Persistant Data
• Types and Complexity of Data Integration
Part 2: Batch Data Integration
• Extract, Transformation, and Load
• Data Warehousing
• Data Conversion
• Data Archiving
• Batch Data Integration Architecture and Metadata
Part 3: Real-Time Data Integration
• Data Integration Patterns
• Enterprise Service Bus (ESB)
• Service Oriented Architecture (SOA)
• Extensible Markup Language (XML) and other formats
• Data Replication
• Modeling
• Master Data Management
• Data Warehousing with Real Time Updates
• Real Time Data Integration Architecture and Metadata
• Interactions with Legacy Systems
• External Interaction
Part 4: Cloud and Big Data Integration
• Cloud Architecture and Data Integration
• Big Data Integration
• Data Virtualization
• In-Memory Data

ISBN: 9780123971678 ¦ Visit in bookstore

Description

Brainstorming and Beyond describes the techniques for generating ideas verbally, in writing, or through sketches. The first chapter focuses on brainstorming, the foundation method for ideation, which is a complex social process building off of social psychology principles, motivational constructs, and corporate culture. Brainstorming is commonly portrayed as an easy way to generate ideas, but in reality, it is a complex social process that is often flawed in ways that are not self-evident. Chapter 2 discusses Brainwriting, which is a variation on brainstorming in which each person writes ideas down on paper and then passes the paper to a new person who reads the first set of ideas and adds new ones. Since there is no group shouting out of ideas, strong facilitation skills are not required, and more often than not, Brainwriting results greatly exceed those of group brainstorming in a shorter time because ideas are generated in a parallel, rather than serial, fashion. Brainwriting is useful when time is limited, groups are hostile, or you are dealing with a culture where shouting out wild or divergent ideas might be difficult. Finally, in Chapter 3, readers learn about Braindrawing, a method of visual brainstorming that helps practitioners generate ideas for icons, other graphics, user interface layouts, or Web page designs. Each of these methods provides readers with ways to generate, present, and evaluate ideas so they can begin building a strong foundation for product success.

Who Should Read This Book

User experience architects, designers, researchers, and specialists.

Table of Contents

Chapter 1. Brainstorming

Overview of Brainstorming

When Should You Use Brainstorming?

Procedures and Practical Advice on Brainstorming

Variations and Extensions to Brainstorming

Reverse (Negative) Brainstorming

Data Analysis for Brainstorming

What Do You Need for Brainstorming?

Recommended Readings

References

Chapter 2. Brainwriting

Overview of Brainwriting

When Should You Use Brainwriting?

Procedures and Practical Advice on Interactive Brainwriting

After the Brainwriting Session

Variations and Extensions to Brainwriting

Major Issues in the Use of Brainwriting

Data Analysis

What Do You Need to Use The Brainwriting Method?

Recommended Readings

References

Chapter 3. Braindrawing

Overview of Braindrawing

When Should You Use Braindrawing?

Procedures and Practical Advice on the Braindrawing Method

Variations and Extensions to Braindrawing

Major Issues in the Use of Braindrawing

Data Analysis

What Do You Need to Use Braindrawing?

Recommended Readings

References

ISBN: 9780124071575 ¦ Visit in bookstore

Description

Computation and Storage in the Cloud is the first comprehensive and systematic work investigating the issue of computation and storage trade-off in the cloud in order to reduce the overall application cost. Scientific applications are usually computation and data intensive, where complex computation tasks take a long time for execution and the generated datasets are often terabytes or petabytes in size. Storing valuable generated application datasets can save their regeneration cost when they are reused, not to mention the waiting time caused by regeneration. However, the large size of the scientific datasets is a big challenge for their storage. By proposing innovative concepts, theorems and algorithms, this book will help bring the cost down dramatically for both cloud users and service providers to run computation and data intensive scientific applications in the cloud.

Key Features

• Covers cost models and benchmarking that explain the necessary tradeoffs for both cloud providers and users
• Describes several novel strategies for storing application datasets in the cloud
• Includes real-world case studies of scientific research applications

Who Should Read This Book

Researchers, practitioners, and graduate students in scientific computing seeking guidance for managing application datasets.

Table of Contents

1. Introduction
2. Data management and cost-effectiveness
3. Motivating example and research
4. Cost model of dataset storage in the cloud
5. Minimum cost benchmarking approaches
6. Cost-effective dataset storage strategies
7. Evaluations
8. Conclusions

ISBN: 9780124077676 ¦ Visit in bookstore

Description

Human-Computer Interaction: An Empirical Research Perspective is the definitive guide to empirical research in HCI. The book begins with foundational topics including an historical context, the human factor, interaction elements, and the fundamentals of science and research. From there, you’ll progress to learning about the methods for conducting an experiment to evaluate a new computer interface or interaction technique. There are detailed discussions and how-to analyses on models of interaction, focusing on descriptive models and predictive models. Writing and publishing a research paper is explored with helpful tips for success. Throughout the book, you’ll find hands-on exercises, checklists, and real-world examples. This is your must-have, comprehensive guide to empirical and experimental research in HCI – an essential addition to your HCI library.

Key Features

• Master empirical and experimental research with this comprehensive, A-to-Z guide in a concise, hands-on reference
• Discover the practical and theoretical ins-and-outs of user studies
• Find exercises, takeaway points, and case studies throughout

Who Should Read This Book

HCI/UX researchers and professionals interested in user studies, as well as university students in academia and industry human-computer interaction.

Table of Contents

1. Historical Context
2. The Human Factor
3. Interaction Elements
4. Scientific Foundations
5. Designing HCI Experiments
6. Hypothesis Testing
7. Modeling Interaction
8. Writing and Publishing a Research Paper

Description

One of the biggest challenges for data quality practitioners is defining how to measure the quality of data over time. There are many discussions about dimensions of data quality, but little advice on how to measure and monitor. Measuring Data Quality for Ongoing Improvement: A Data Quality Measurement Framework presents a complete approach to measuring data that can be understood by both business and IT. It recognizes that improving data quality depends not simply on profiling but on the ability to continuously measure whether data meets business expectations. Laura Sebastian-Coleman starts with general concepts of measurement and works through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. The framework’s focus is on ongoing measurement rather than one-time activities, such as profiling and inspection. The framework presents a new and valuable perspective on data quality measurement, and the book provides practical guidance on how to apply the DQMF within an organization, including how to prioritize measurements and report on results.

Key Features

• Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges
• Enables discussions between business and IT with a non-technical vocabulary for data quality measurement
• Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Who Should Read This Book

Data quality engineers, managers and analysts, application program managers and developers, data stewards, data managers and analysts, compliance analysts, Business intelligence professionals, Database designers and administrators, Business and IT managers.

Table of Contents

Section One: Concepts and Definitions

Chapter 1: Data

Chapter 2: Data, People, and Systems

Chapter 3: Data Management, Models, and Metadata

Chapter 4: Data Quality and Measurement

Section Two: DQAF Concepts and Measurement Types

Chapter 5: DQAF Concepts

Chapter 6: DQAF Measurement Types

Section Three: Data Assessment Scenarios

Chapter 7: Initial Data Assessment

Chapter 8 Assessment in Data Quality Improvement Projects

Chapter 9: Ongoing Measurement

Section Four: Applying the DQAF to Data Requirements

Chapter 10: Requirements, Risk, Criticality

Chapter 11: Asking Questions

Section Five: A Strategic Approach to Data Quality

Chapter 12: Data Quality Strategy

Chapter 13: Quality Improvement and Data Quality

Chapter 14: Directives for Data Quality Strategy

Section Six: The DQAF in Depth

Chapter 15: Functions of Measurement: Collection, Calculation, Comparison

Chapter 16: Features of the DQAF Measurement Logical

Chapter 17: Facets of the DQAF Measurement Types

Appendix A: Measuring the Value of Data

Appendix B: Data Quality Dimensions

Appendix C: Completeness, Consistency, and Integrity of the Data Model

Appendix D: Prediction, Error, and Shewhart’s lost disciple, Kristo Ivanov

Glossary

Bibliography

ISBN: 9780123970336 ¦ Visit in Amazon

Description

This book begins with a high-level example of how an average person might interact with a service-oriented architecture. As the book progresses, more technical detail is added in a “peeling of the onion” approach. The leadership opportunities within this technology are also explained. At the end of the book, there is a Quick Reference Guide to related technologies.

Key Features

• Only web services book to cover both data management and software engineering perspectives, excellent resource for ALL members of IT teams
• Jargon free, highly illustrated, with introduction that anyone can read that then leads into increasing technical detail
• Provides a set of leadership principles and suggested application for using this technology.

Who Should Read This Book

IT managers, technical leads, analysts, programmers, and consultants.

Table of Contents

Introduction

Part I: Overview of Web Services, Service-Oriented Architecture, and Cloud Computing

1. A Business Trip in the Not-Too-Distant Future

2. Information Technology Used in This Trip

3. Web Services and Service-Oriented Architectures

4. Cloud Computing

Part II: Technical Forces Driving the Adoption of Web Services, Service-Oriented Architectures, and Cloud Computing

5. Technical Forces Driving the Adoption of Webservices

6. Technical Forces Driving the Adoption of a Service-Oriented Architecture

7. Technical Forces Driving the Adoption of Cloud Computing

Part III: Managing Change Needed for Web Services, Service-Oriented Architectures, and Cloud Computing

8. Change Issues Affecting the Adoption of Web Services, Service-Oriented Architectures, and Cloud Computing

9. Tips for Managing Change Issues during Development

10. Managing Change with an Incremental Service-Oriented Architecture

Part IV: Getting Started with Web Services, Service-Oriented Architectures, and Cloud Computing

11. Getting Started with Web Services

12. Getting Started with Service-Oriented Architectures

13. Getting Started with Cloud Computing

14. Revisiting the Business Trip in the Not-Too-Distant Future

Part V: Reference Guide

15. Semantic Vocabularies

16. Terminology

ISBN: 9780123983572 ¦ Visit on Amazon

Description

Do you navigate websites by navigation or search for what you’re looking for? Increasingly, the answer to this question is by search and while search is the future of discovering meaning in the digital universe, search results rarely meet user expectations.

Despite the growing importance of search in the daily lives of users, few non-academic books have been published on the topic. While there are hundreds of titles about designing website navigation, books about designing search can be counted on one hand, with no definitive work having yet emerged.

Designing the Search Experience presents a theoretical framework of the search experience seamlessly integrated with practical design considerations. It will help readers understand both search as a whole, as well as the nuances of design patterns and the relationships among them. Rooted in academic literature but infused with over 2 decades of experience, it will be the formative work on designing search.

Key Features

• Understand how people search, and how the concepts of information seeking, information foraging, and sensemaking underpin the search process.
• Apply the principles of user-centered design to the search box, search results, faceted navigation, mobile interfaces, social search, and much more.
• Design the cross-channel search experiences of tomorrow that span desktop, tablet, mobile, and other devices.

Who Should Read This Book

Information architects, user experience designers, search engineers, project developers and managers, researchers and students in information retrieval, human-information interaction, and HCI.

Table of Contents

PART 1: A Framework for Search and Discovery

Chapter 1 The User
Chapter 2 Information Seeking
Chapter 3 Context
Chapter 4 Modes of Search and Discovery

PART 2: Design Solutions

Chapter 5 Formulating the Query
Chapter 6 Displaying and Manipulating Results
Chapter 7 Faceted Search
Chapter 8 Mobile Search
Chapter 9 Social Search

Part 3: Designing the Future

Chapter 10 Cross-Channel Information Interaction

ISBN: 9780123969811 ¦ Visit in bookstore

Description

This new edition of the bestselling Programming Massively Parallel Processors: A Hands-On Approach has been thoroughly updated with new and updated content on parallel computing techniques and technologies, now more than 50% larger than the first edition. Designed as a general introduction to parallel computing, this textbook shows how professionals and students alike can utilize “computational thinking,” a valuable approach for parallelizing and optimizing applications for significant performance improvements. Kirk and Hwu’s concise, intuitive, practical approach is based on years of road testing in their own parallel computing courses.

Chapters added to this 2e:

• Coverage of several parallel patterns, which are the basis of many parallel algorithms that appear in parallel applications
• CUDA Fortran, a programming interface to the CUDA architecture, including multiple examples illustrating CUDA Fortran programming
• OpenACC for parallel programmers familiar with CUDA C introduces this new interface for parallel computing designed to simplify parallel programming
• How to leverage the Thrust parallel template library to implement high-performance applications with minimal programming effort
• The new programming features of Kepler, NVIDIA’s new high-performing, power-efficient GPU architecture

Key Features

Updates in this edition include:

• 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 explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.

Who Should Read This Book

Advanced students, software engineers, programmers, hardware engineers.

Table of Contents

1. Introduction
2. History of GPU Computing
3. Introduction to Data Parallelism and CUDA C4. Data-Parallel Execution Model
5. CUDA Memories
6. Performance Considerations
7. Floating-Point Considerations
8. Parallel Patterns: Convolutions
9. Parallel Patterns: Prefix Sum
10. Parallel Patterns: Sparse Matrix-Vector Multiplication
11. Application Case Study: Advanced MRI Reconstruction
12. Application Case Study: Molecular Visualization and Analysis
13. Parallel Programming and Computational Thinking
14. An Introduction to OpenCL
15. Parallel Programming with OpenACC
16. Thrust: A Productivity-Oriented Library for CUDA
17. CUDA FORTRAN
18. An Introduction to C++ AMP
19. Programming a Heterogeneous Computing Cluster
20. CUDA Dynamic Parallelism
21. Conclusions and Future Outlook

Appendix A: Matrix Multiplication Host-Only Version Source Code
Appendix B: GPU Compute Capabilities

ISBN: 9780124159921 ¦ Visit on Amazon