"The Grid is an emerging infrastructure that will fundamentally change the way we think about-and use-computing. The word Grid is used by analogy with the electric power grid, which provides pervasive access to electricity and has had a dramatic impact on human capabilities and society. Many believe that by allowing all components of our information technology infrastructure-computational capabilities, databases, sensors, and people-to be shared flexibly as true collaborative tools the Grid will have a similar transforming effect, allowing new classes of applications to emerge."
-From the Preface
In 1998, Ian Foster and Carl Kesselman introduced a whole new concept in computing with the first edition of this book. Today there is a broader and deeper understanding of the nature of the opportunities offered by Grid computing and the technologies needed to realize those opportunities. In Grid 2, the editors reveal the revolutionary impact of large-scale resource sharing and virtualization within science and industry, the intimate relationships between organization and resource sharing structures and the new technologies required to enable secure, reliable, and efficient resource sharing on large scale.
Foster and Kesselman have once again assembled a team of experts to present an up-to-date view of Grids that reports on real experiences and explains the available technologies and new technologies emerging from labs, companies and standards bodies. Grid 2, like its predecessor, serves as a manifesto, design blueprint, user guide and research agenda for future Grid systems.
*30 chapters including more than a dozen completely new chapters.
*Web access to 13 unchanged chapters from the first edition.
*Three personal essays by influential thinkers on the significance of Grids from the perspectives of infrastructure, industry, and science.
*A foundational overview of the central Grid concepts and architectural principles.
*Twelve application vignettes showcase working Grids in science, engineering, industry, and commerce.
*Detailed discussions of core architecture and services, data and knowledge management, and higher-level tools.
*Focused presentations on production Grid deployment, computing platforms, peer-to-peer technologies, and network infrastructures.
*Extensive bibliography and glossary.

Parallel Computing is a compelling vision of how computation can seamlessly scale from a single processor to virtually limitless computing power. Unfortunately, the scaling of application performance has not matched peak speed, and the programming burden for these machines remains heavy. The applications must be programmed to exploit parallelism in the most efficient way possible. Today, the responsibility for achieving the vision of scalable parallelism remains in the hands of the application developer.

This book represents the collected knowledge and experience of over 60 leading parallel computing researchers. They offer students, scientists and engineers a complete sourcebook with solid coverage of parallel computing hardware, programming considerations, algorithms, software and enabling technologies, as well as several parallel application case studies. The Sourcebook of Parallel Computing offers extensive tutorials and detailed documentation of the advanced strategies produced by research over the last two decades
application case studies. The Sourcebook of Parallel Computing offers extensive tutorials and detailed documentation of the advanced strategies produced by research over the last two decades
* Provides a solid background in parallel computing technologies
* Examines the technologies available and teaches students and practitioners how to select and apply them
* Presents case studies in a range of application areas including Chemistry, Image Processing, Data Mining, Ocean Modeling and Earthquake Simulation
* Considers the future development of parallel computing technologies and the kinds of applications they will support

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.

This book constitutes the thoroughly referred post-proceedings of the International Provenance and Annotation Workshops, IPAW 2006, held in Chicago, Il, USA in May 2006. The 26 revised full papers presented together with two keynote papers were carefully selected for presentation during two rounds of reviewing and improvement. The papers are organized in topical sections.

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.

This volume of The ANNALS outlines the infrastructures that will need to be built to make sure data providers and empirical researchers can best serve national policy needs. The volume is organized around three topics: privacy and confidentiality, data providers, and comprehensive strategies.

In Conscripts of Migration: Neoliberal Globalization, Nationalism, and the Literature of New African Diasporas, author Christopher Ian Foster analyzes increasingly urgent questions regarding crises of global immigration by redefining migration in terms of conscription and by studying contemporary literature. Reporting on immigration, whether liberal or conservative, popular or scholarly, leaves out the history in which the Global North helped create outward migration in the Global South. From histories of racial capitalism, the trans-Atlantic slave trade, and imperialism to contemporary neoliberal globalization and the resurgence of xenophobic nationalism, countries in the Global North continue to devastate and destabilize the Global South. Britain, France, Italy, and the United States, in different ways, police the effects of their own global policies at their borders. Foster provides a substantial study of a new body of contemporary African diasporic literature called migritude literature. Migritude indicates the work and ideas of a disparate yet distinct group of younger African authors born after independence in the 1960s. Most often migritude authors have lived both in and outside Africa and narrate the experiences of migration under the pressures of globalization. They also emphasize that immigration itself and stereotypes of the immigrant are entangled with the history of colonialism. Authors like Fatou Diome, Shailja Patel, Abdourahman Waberi, Cristina Ali Farah, and others confront critical issues of migrancy, diaspora, departure, return, racism, identity, gender, sexuality, and postcoloniality.

In Conscripts of Migration: Neoliberal Globalization, Nationalism, and the Literature of New African Diasporas, author Christopher Ian Foster analyzes increasingly urgent questions regarding crises of global immigration by redefining migration in terms of conscription and by studying contemporary literature. Reporting on immigration, whether liberal or conservative, popular or scholarly, leaves out the history in which the Global North helped create outward migration in the Global South. From histories of racial capitalism, the trans-Atlantic slave trade, and imperialism to contemporary neoliberal globalization and the resurgence of xenophobic nationalism, countries in the Global North continue to devastate and destabilize the Global South. Britain, France, Italy, and the United States, in different ways, police the effects of their own global policies at their borders. Foster provides a substantial study of a new body of contemporary African diasporic literature called migritude literature. Migritude indicates the work and ideas of a disparate yet distinct group of younger African authors born after independence in the 1960s. Most often migritude authors have lived both in and outside Africa and narrate the experiences of migration under the pressures of globalization. They also emphasize that immigration itself and stereotypes of the immigrant are entangled with the history of colonialism. Authors like Fatou Diome, Shailja Patel, Abdourahman Waberi, Cristina Ali Farah, and others confront critical issues of migrancy, diaspora, departure, return, racism, identity, gender, sexuality, and postcoloniality.