SR (Synchronizing Resources) is a powerful and flexible language for concurrent programming. With its explicit mechanisms and concurrency, communication, and synchronization, programmers can easily learn to write programs for both shared- and distributed-memory applications and machines.This book, written by the language designers, provides a complete introduction to SR and gives the reader the tools for learning about and experimenting with concurrency. Features Provides an accessible, clear introduction to SR by the language designers. Teaches practical techniques through numerous realistic examples of parallel and distributed programming problems. Examines 'classic' concurrent programming problems as well as many important parallel and distributed programming problems. Illustrates trade-offs between language mechanisms to help the reader understand and make optimum design decisions Reinforces key points with numerous end-of-chapter exercises Includes six appendices that summarize the language for quick reference, show how to develop and execute programs, and describe the implementation. The SR language implementation is available, free, from the SR Project, University of Arizona, at ftp://cs.arizona.edu/sr/. 0805300880B04062001

High dimensional integration arises naturally in two major sub-fields of statistics: multivariate and Bayesian statistics. Indeed, the most common measures of central tendency, variation, and loss are defined by integrals over the sample space, the parameter space, or both. Recent advances in computational power have stimulated significant new advances in both Bayesian and classical multivariate statistics. In many statistical problems, however, multiple integration can be the major obstacle to solutions. This volume contains the proceedings of an AMS-IMS-SIAM Joint Summer Research Conference on Statistical Multiple Integration, held in June 1989 at Humboldt State University in Arcata, California. The conference represents an attempt to bring together mathematicians, statisticians, and computational scientists to focus on the many important problems in statistical multiple integration. The papers document the state of the art in this area with respect to problems in statistics, potential advances blocked by problems with multiple integration, and current work directed at expanding the capability to integrate over high dimensional surfaces.

This book offers a fresh perspective on the fundamentals of programming languages through the use of type theory.