A guide to advanced features of MPI, reflecting the latest version of the MPI standard, that takes an example-driven, tutorial approach. This book offers a practical guide to the advanced features of the MPI (Message-Passing Interface) standard library for writing programs for parallel computers. It covers new features added in MPI-3, the latest version of the MPI standard, and updates from MPI-2. Like its companion volume, Using MPI, the book takes an informal, example-driven, tutorial approach. The material in each chapter is organized according to the complexity of the programs used as examples, starting with the simplest example and moving to more complex ones. Using Advanced MPI covers major changes in MPI-3, including changes to remote memory access and one-sided communication that simplify semantics and enable better performance on modern hardware; new features such as nonblocking and neighborhood collectives for greater scalability on large systems; and minor updates to parallel I/O and dynamic processes. It also covers support for hybrid shared-memory/message-passing programming; MPI_Message, which aids in certain types of multithreaded programming; features that handle very large data; an interface that allows the programmer and the developer to access performance data; and a new binding of MPI to Fortran.

Using MPI is a completely up-to-date version of the authors' 1994 introduction to the core functions of MPI. It adds material onthe new C++ and Fortran 90 bindings for MPI throughout the book. The Message Passing Interface (MPI) specification is widely used for solving significant scientific and engineering problems on parallel computers. There exist more than a dozen implementations on computer platforms ranging from IBM SP-2 supercomputers to clusters of PCs running Windows NT or Linux ("Beowulf" machines). The initial MPI Standard document, MPI-1, was recently updated by the MPI Forum. The new version, MPI-2, contains both significant enhancements to the existing MPI core and new features.Using MPI is a completely up-to-date version of the authors' 1994 introduction to the core functions of MPI. It adds material on the new C++ and Fortran 90 bindings for MPI throughout the book. It contains greater discussion of datatype extents, the most frequently misunderstood feature of MPI-1, as well as material on the new extensions to basic MPI functionality added by the MPI-2 Forum in the area of MPI datatypes and collective operations.Using MPI-2 covers the new extensions to basic MPI. These include parallel I/O, remote memory access operations, and dynamic process management. The volume also includes material on tuning MPI applications for high performance on modern MPI implementations.

The authors introduce the core function of the Message Printing Interface (MPI). This edition adds material on the C++ and Fortran 90 binding for MPI.

Mathematics of Computing -- Parallelism.

Numerical algorithms, modern programming techniques, and parallel computing are often taught serially across different courses and different textbooks. The need to integrate concepts and tools usually comes only in employment or in research - after the courses are concluded - forcing the student to synthesise what is perceived to be three independent subfields into one. This book provides a seamless approach to stimulate the student simultaneously through the eyes of multiple disciplines, leading to enhanced understanding of scientific computing as a whole. The book includes both basic as well as advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Some of the advanced topics include wavelets, high-order methods, non-symmetric systems, and parallelization of sparse systems. The material covered is suited to students from engineering, computer science, physics and mathematics.

This gentle introduction to High Performance Computing (HPC) for Data Science using the Message Passing Interface (MPI) standard has been designed as a first course for undergraduates on parallel programming on distributed memory models, and requires only basic programming notions. Divided into two parts the first part covers high performance computing using C++ with the Message Passing Interface (MPI) standard followed by a second part providing high-performance data analytics on computer clusters. In the first part, the fundamental notions of blocking versus non-blocking point-to-point communications, global communications (like broadcast or scatter) and collaborative computations (reduce), with Amdalh and Gustafson speed-up laws are described before addressing parallel sorting and parallel linear algebra on computer clusters. The common ring, torus and hypercube topologies of clusters are then explained and global communication procedures on these topologies are studied. This first part closes with the MapReduce (MR) model of computation well-suited to processing big data using the MPI framework. In the second part, the book focuses on high-performance data analytics. Flat and hierarchical clustering algorithms are introduced for data exploration along with how to program these algorithms on computer clusters, followed by machine learning classification, and an introduction to graph analytics. This part closes with a concise introduction to data core-sets that let big data problems be amenable to tiny data problems. Exercises are included at the end of each chapter in order for students to practice the concepts learned, and a final section contains an overall exam which allows them to evaluate how well they have assimilated the material covered in the book.

The era of practical parallel programming has arrived, marked by the popularity of the MPI and OpenMP software standards and the emergence of commodity clusters as the hardware platform of choice for an increasing number of organizations. This exciting new book,Parallel Programming in C with MPI and OpenMPaddresses the needs of students and professionals who want to learn how to design, analyze, implement, and benchmark parallel programs in C using MPI and/or OpenMP. It introduces a rock-solid design methodology with coverage of the most important MPI functions and OpenMP directives. It also demonstrates, through a wide range of examples, how to develop parallel programs that will execute efficiently on today’s parallel platforms. If you are an instructor who has adopted the book and would like access to the additional resources, please contact your local sales rep. or Michelle Flomenhoft at: [email protected].

In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.