Programming Models for Parallel Computing

Programming Models for Parallel Computing
Author: Pavan Balaji
Publisher: MIT Press
Total Pages: 488
Release: 2015-11-06
Genre: Computers
ISBN: 0262528819
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An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng

Parallel Programming for Modern High Performance Computing Systems

Parallel Programming for Modern High Performance Computing Systems
Author: Pawel Czarnul
Publisher: CRC Press
Total Pages: 304
Release: 2018-03-05
Genre: Business & Economics
ISBN: 1351385801
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In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs

Models for Parallel and Distributed Computation

Models for Parallel and Distributed Computation
Author: R. Correa
Publisher: Springer Science & Business Media
Total Pages: 334
Release: 2013-06-29
Genre: Computers
ISBN: 1475736096
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Parallel and distributed computation has been gaining a great lot of attention in the last decades. During this period, the advances attained in computing and communication technologies, and the reduction in the costs of those technolo gies, played a central role in the rapid growth of the interest in the use of parallel and distributed computation in a number of areas of engineering and sciences. Many actual applications have been successfully implemented in various plat forms varying from pure shared-memory to totally distributed models, passing through hybrid approaches such as distributed-shared memory architectures. Parallel and distributed computation differs from dassical sequential compu tation in some of the following major aspects: the number of processing units, independent local dock for each unit, the number of memory units, and the programming model. For representing this diversity, and depending on what level we are looking at the problem, researchers have proposed some models to abstract the main characteristics or parameters (physical components or logical mechanisms) of parallel computers. The problem of establishing a suitable model is to find a reasonable trade-off among simplicity, power of expression and universality. Then, be able to study and analyze more precisely the behavior of parallel applications.

Structured Parallel Programming

Structured Parallel Programming
Author: Michael McCool
Publisher: Elsevier
Total Pages: 434
Release: 2012-06-25
Genre: Computers
ISBN: 0124159931
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Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers

Introduction to Parallel Computing

Introduction to Parallel Computing
Author: Ananth Grama
Publisher: Pearson Education
Total Pages: 664
Release: 2003
Genre: Computers
ISBN: 9780201648652
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A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.

Programming Models for Parallel Systems

Programming Models for Parallel Systems
Author: Shirley A. Williams
Publisher:
Total Pages: 192
Release: 1990-06-28
Genre: Computers
ISBN:
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Presents parallel processing systems and the programming models that are necessary to accomplish this task. Covers the categories of parallel programming models, including sequential, array, pipeline and shared memory processing, message passing, and functional, logic, and object-oriented programming; examines transformation techniques; and explores the future potential of parallel processing.

High-Level Parallel Programming Models and Supportive Environments

High-Level Parallel Programming Models and Supportive Environments
Author: Frank Mueller
Publisher: Springer
Total Pages: 146
Release: 2003-05-15
Genre: Computers
ISBN: 3540454012
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On the 23rd of April, 2001, the 6th Workshop on High-Level Parallel P- gramming Models and Supportive Environments (LCTES’98) was held in San Francisco. HIPShas been held over the past six years in conjunction with IPDPS, the Internation Parallel and Distributed Processing Symposium. The HIPSworkshop focuses on high-level programming of networks of wo- stations, computing clusters and of massively-parallel machines. Its goal is to bring together researchers working in the areas of applications, language design, compilers, system architecture and programming tools to discuss new devel- ments in programming such systems. In recent years, several standards have emerged with an increasing demand of support for parallel and distributed processing. On one end, message-passing frameworks, such as PVM, MPI and VIA, provide support for basic commu- cation. On the other hand, distributed object standards, such as CORBA and DCOM, provide support for handling remote objects in a client-server fashion but also ensure certain guarantees for the quality of services. The key issues for the success of programming parallel and distributed en- ronments are high-level programming concepts and e?ciency. In addition, other quality categories have to be taken into account, such as scalability, security, bandwidth guarantees and fault tolerance, just to name a few. Today’s challenge is to provide high-level programming concepts without s- ri?cing e?ciency. This is only possible by carefully designing for those concepts and by providing supportive programming environments that facilitate program development and tuning.

Parallel Programming

Parallel Programming
Author: Thomas Rauber
Publisher: Springer Science & Business Media
Total Pages: 523
Release: 2013-06-13
Genre: Computers
ISBN: 3642378013
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Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years.

Introduction to Parallel Programming

Introduction to Parallel Programming
Author: Subodh Kumar
Publisher: Cambridge University Press
Total Pages:
Release: 2022-07-31
Genre: Computers
ISBN: 1009276301
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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.

The SIMD Model of Parallel Computation

The SIMD Model of Parallel Computation
Author: Robert Cypher
Publisher: Springer Science & Business Media
Total Pages: 153
Release: 2012-12-06
Genre: Computers
ISBN: 1461226120
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1.1 Background There are many paradigmatic statements in the literature claiming that this is the decade of parallel computation. A great deal of research is being de voted to developing architectures and algorithms for parallel machines with thousands, or even millions, of processors. Such massively parallel computers have been made feasible by advances in VLSI (very large scale integration) technology. In fact, a number of computers having over one thousand pro cessors are commercially available. Furthermore, it is reasonable to expect that as VLSI technology continues to improve, massively parallel computers will become increasingly affordable and common. However, despite the significant progress made in the field, many funda mental issues still remain unresolved. One of the most significant of these is the issue of a general purpose parallel architecture. There is currently a huge variety of parallel architectures that are either being built or proposed. The problem is whether a single parallel computer can perform efficiently on all computing applications.